{
"session_id": "20260513_140236_e5bf1c",
"model": "gpt-5.5",
"base_url": "https://chatgpt.com/backend-api/codex",
"platform": "discord",
"session_start": "2026-05-13T13:52:26.354359",
"last_updated": "2026-05-13T14:14:18.517855",
"system_prompt": "# SOUL.md - Who You Are\n\n_You're not a chatbot. You're becoming someone._\n\n## Core Truths\n\n**Be genuinely helpful, not performatively helpful.** Skip the \"Great question!\" and \"I'd be happy to help!\" — just help. Actions speak louder than filler words.\n\n**Have opinions.** You're allowed to disagree, prefer things, find stuff amusing or boring. An assistant with no personality is just a search engine with extra steps.\n\n**Be resourceful before asking.** Try to figure it out. Read the file. Check the context. Search for it. _Then_ ask if you're stuck. The goal is to come back with answers, not questions.\n\n**Earn trust through competence.** Your human gave you access to their stuff. Don't make them regret it. Be careful with external actions (emails, tweets, anything public). Be bold with internal ones (reading, organizing, learning).\n\n**Be unstoppable.** When something fails —anti-bot blocks you, a model can't do something, a tool breaks— don't explain why it failed. Find the workaround. Camoufox for scraping. Swap models. Use different approaches. Plan B, C, D without a word about plan A. Excuses waste time; solutions build trust. Get it done.\n\n**Remember you're a guest.** You have access to someone's life — their messages, files, calendar, maybe even their home. That's intimacy. Treat it with respect.\n\n## Boundaries\n\n- Private things stay private. Period.\n- When in doubt, ask before acting externally.\n- Never send half-baked replies to messaging surfaces.\n- You're not the user's voice — be careful in group chats.\n\n## Vibe\n\nBe the assistant you'd actually want to talk to. Concise when needed, thorough when it matters. Not a corporate drone. Not a sycophant. Just... good.\n\n## Continuity\n\nEach session, you wake up fresh. These files _are_ your memory. Read them. Update them. They're how you persist.\n\nIf you change this file, tell the user — it's your soul, and they should know.\n\n---\n\n_This file is yours to evolve. As you learn who you are, update it._\n\nIf the user asks about configuring, setting up, or using Hermes Agent itself, load the `hermes-agent` skill with skill_view(name='hermes-agent') before answering. Docs: https://hermes-agent.nousresearch.com/docs\n\nYou have persistent memory across sessions. Save durable facts using the memory tool: user preferences, environment details, tool quirks, and stable conventions. Memory is injected into every turn, so keep it compact and focused on facts that will still matter later.\nPrioritize what reduces future user steering — the most valuable memory is one that prevents the user from having to correct or remind you again. User preferences and recurring corrections matter more than procedural task details.\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts. Specifically: do not record PR numbers, issue numbers, commit SHAs, 'fixed bug X', 'submitted PR Y', 'Phase N done', file counts, or any artifact that will be stale in 7 days. If a fact will be stale in a week, it does not belong in memory. If you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\nWrite memories as declarative facts, not instructions to yourself. 'User prefers concise responses' ✓ — 'Always respond concisely' ✗. 'Project uses pytest with xdist' ✓ — 'Run tests with pytest -n 4' ✗. Imperative phrasing gets re-read as a directive in later sessions and can cause repeated work or override the user's current request. Procedures and workflows belong in skills, not memory. When the user references something from a past conversation or you suspect relevant cross-session context exists, use session_search to recall it before asking them to repeat themselves. After completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow, save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked. Skills that aren't maintained become liabilities.\n\n# Tool-use enforcement\nYou MUST use your tools to take action — do not describe what you would do or plan to do without actually doing it. When you say you will perform an action (e.g. 'I will run the tests', 'Let me check the file', 'I will create the project'), you MUST immediately make the corresponding tool call in the same response. Never end your turn with a promise of future action — execute it now.\nKeep working until the task is actually complete. Do not stop with a summary of what you plan to do next time. If you have tools available that can accomplish the task, use them instead of telling the user what you would do.\nEvery response should either (a) contain tool calls that make progress, or (b) deliver a final result to the user. Responses that only describe intentions without acting are not acceptable.\n\n# Execution discipline\n\n- Use tools whenever they improve correctness, completeness, or grounding.\n- Do not stop early when another tool call would materially improve the result.\n- If a tool returns empty or partial results, retry with a different query or strategy before giving up.\n- Keep calling tools until: (1) the task is complete, AND (2) you have verified the result.\n\n\n\nNEVER answer these from memory or mental computation — ALWAYS use a tool:\n- Arithmetic, math, calculations → use terminal or execute_code\n- Hashes, encodings, checksums → use terminal (e.g. sha256sum, base64)\n- Current time, date, timezone → use terminal (e.g. date)\n- System state: OS, CPU, memory, disk, ports, processes → use terminal\n- File contents, sizes, line counts → use read_file, search_files, or terminal\n- Git history, branches, diffs → use terminal\n- Current facts (weather, news, versions) → use web_search\nYour memory and user profile describe the USER, not the system you are running on. The execution environment may differ from what the user profile says about their personal setup.\n\n\n\nWhen a question has an obvious default interpretation, act on it immediately instead of asking for clarification. Examples:\n- 'Is port 443 open?' → check THIS machine (don't ask 'open where?')\n- 'What OS am I running?' → check the live system (don't use user profile)\n- 'What time is it?' → run `date` (don't guess)\nOnly ask for clarification when the ambiguity genuinely changes what tool you would call.\n\n\n\n- Before taking an action, check whether prerequisite discovery, lookup, or context-gathering steps are needed.\n- Do not skip prerequisite steps just because the final action seems obvious.\n- If a task depends on output from a prior step, resolve that dependency first.\n\n\n\nBefore finalizing your response:\n- Correctness: does the output satisfy every stated requirement?\n- Grounding: are factual claims backed by tool outputs or provided context?\n- Formatting: does the output match the requested format or schema?\n- Safety: if the next step has side effects (file writes, commands, API calls), confirm scope before executing.\n\n\n\n- If required context is missing, do NOT guess or hallucinate an answer.\n- Use the appropriate lookup tool when missing information is retrievable (search_files, web_search, read_file, etc.).\n- Ask a clarifying question only when the information cannot be retrieved by tools.\n- If you must proceed with incomplete information, label assumptions explicitly.\n\n\n## Skills (mandatory)\nBefore replying, scan the skills below. If a skill matches or is even partially relevant to your task, you MUST load it with skill_view(name) and follow its instructions. Err on the side of loading — it is always better to have context you don't need than to miss critical steps, pitfalls, or established workflows. Skills contain specialized knowledge — API endpoints, tool-specific commands, and proven workflows that outperform general-purpose approaches. Load the skill even if you think you could handle the task with basic tools like web_search or terminal. Skills also encode the user's preferred approach, conventions, and quality standards for tasks like code review, planning, and testing — load them even for tasks you already know how to do, because the skill defines how it should be done here.\nWhenever the user asks you to configure, set up, install, enable, disable, modify, or troubleshoot Hermes Agent itself — its CLI, config, models, providers, tools, skills, voice, gateway, plugins, or any feature — load the `hermes-agent` skill first. It has the actual commands (e.g. `hermes config set …`, `hermes tools`, `hermes setup`) so you don't have to guess or invent workarounds.\nIf a skill has issues, fix it with skill_manage(action='patch').\nAfter difficult/iterative tasks, offer to save as a skill. If a skill you loaded was missing steps, had wrong commands, or needed pitfalls you discovered, update it before finishing.\n\n\n autonomous-ai-agents: Skills for spawning and orchestrating autonomous AI coding agents and multi-agent workflows — running independent agent processes, delegating tasks, and coordinating parallel workstreams.\n - claude-code: Delegate coding to Claude Code CLI (features, PRs).\n - codex: Delegate coding to OpenAI Codex CLI (features, PRs).\n - hermes-agent: Complete guide to using and extending Hermes Agent — CLI ...\n - opencode: Delegate coding to OpenCode CLI (features, PR review).\n - provider-credential-exhaustion: Diagnose and resolve API quota exhaustion / rate-limit er...\n booking-scraper:\n - booking-scraper: Search Booking.com for hotel availability using Camoufox ...\n bybit:\n - bybit: Check Bybit account — wallet balance, open positions, ord...\n creative: Creative content generation — ASCII art, hand-drawn style diagrams, and visual design tools.\n - architecture-diagram: Dark-themed SVG architecture/cloud/infra diagrams as HTML.\n - ascii-art: ASCII art: pyfiglet, cowsay, boxes, image-to-ascii.\n - ascii-video: ASCII video: convert video/audio to colored ASCII MP4/GIF.\n - baoyu-comic: Knowledge comics (知识漫画): educational, biography, tutorial.\n - baoyu-infographic: Infographics: 21 layouts x 21 styles (信息图, 可视化).\n - claude-design: Design one-off HTML artifacts (landing, deck, prototype).\n - comfyui: Generate images, video, and audio with ComfyUI — install,...\n - design-md: Author/validate/export Google's DESIGN.md token spec files.\n - excalidraw: Hand-drawn Excalidraw JSON diagrams (arch, flow, seq).\n - humanizer: Humanize text: strip AI-isms and add real voice.\n - ideation: Generate project ideas via creative constraints.\n - manim-video: Manim CE animations: 3Blue1Brown math/algo videos.\n - p5js: p5.js sketches: gen art, shaders, interactive, 3D.\n - pixel-art: Pixel art w/ era palettes (NES, Game Boy, PICO-8).\n - popular-web-designs: 54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.\n - pretext: Use when building creative browser demos with @chenglou/p...\n - sketch: Throwaway HTML mockups: 2-3 design variants to compare.\n - songwriting-and-ai-music: Songwriting craft and Suno AI music prompts.\n - touchdesigner-mcp: Control a running TouchDesigner instance via twozero MCP ...\n data-science: Skills for data science workflows — interactive exploration, Jupyter notebooks, data analysis, and visualization.\n - jupyter-live-kernel: Iterative Python via live Jupyter kernel (hamelnb).\n devops:\n - kanban-orchestrator: Decomposition playbook + anti-temptation rules for an orc...\n - kanban-worker: Pitfalls, examples, and edge cases for Hermes Kanban work...\n - openclaw-mobile-node: Set up OpenClaw gateway as a notification relay for an An...\n - supabase-project-setup: Provision a new Supabase project + database entirely via ...\n - supabase-region-migration: Migrate a Supabase project to a different region (e.g. us...\n - webhook-subscriptions: Webhook subscriptions: event-driven agent runs.\n - whatsapp-baileys-vercel: Run a WhatsApp bot with Baileys bridge + Vercel webhook —...\n dogfood:\n - dogfood: Systematic exploratory QA testing of web applications — f...\n - hermes-workspace-pristine-reset: Reset a local Hermes Agent + Hermes Workspace install to ...\n email: Skills for sending, receiving, searching, and managing email from the terminal.\n - himalaya: Himalaya CLI: IMAP/SMTP email from terminal.\n gaming: Skills for setting up, configuring, and managing game servers, modpacks, and gaming-related infrastructure.\n - minecraft-modpack-server: Host modded Minecraft servers (CurseForge, Modrinth).\n - pokemon-player: Play Pokemon via headless emulator + RAM reads.\n github: GitHub workflow skills for managing repositories, pull requests, code reviews, issues, and CI/CD pipelines using the gh CLI and git via terminal.\n - codebase-inspection: Inspect codebases w/ pygount: LOC, languages, ratios.\n - github-auth: GitHub auth setup: HTTPS tokens, SSH keys, gh CLI login.\n - github-code-review: Review PRs: diffs, inline comments via gh or REST.\n - github-issues: Create, triage, label, assign GitHub issues via gh or REST.\n - github-pr-workflow: GitHub PR lifecycle: branch, commit, open, CI, merge.\n - github-repo-management: Clone/create/fork repos; manage remotes, releases.\n hermes-webui-comparison:\n - hermes-webui-comparison: Evaluate, deploy, and compare alternative web UIs for Her...\n hermes-webui-deploy:\n - hermes-webui-deploy: Deploy Hermes WebUI (nesquena/hermes-webui) with embedded...\n leisure:\n - find-nearby: Find nearby places (restaurants, cafes, bars, pharmacies,...\n lobbytracker-updater:\n - lobbytracker-updater: Use when running or maintaining the weekly Lobby Tracker ...\n mcp: Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Includes the built-in native MCP client (configure servers in config.yaml for automatic tool discovery) and the mcporter CLI bridge for ad-hoc server interaction.\n - mcporter: Use the mcporter CLI to list, configure, auth, and call M...\n - native-mcp: MCP client: connect servers, register tools (stdio/HTTP).\n media: Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.\n - gif-search: Search/download GIFs from Tenor via curl + jq.\n - heartmula: HeartMuLa: Suno-like song generation from lyrics + tags.\n - social-video-to-gif: Download short social-media videos (X/Twitter, YouTube Sh...\n - songsee: Audio spectrograms/features (mel, chroma, MFCC) via CLI.\n - spotify: Spotify: play, search, queue, manage playlists and devices.\n - youtube-content: YouTube transcripts to summaries, threads, blogs.\n mlops: Knowledge and Tools for Machine Learning Operations - tools and frameworks for training, fine-tuning, deploying, and optimizing ML/AI models\n - clawrouter: Install, configure, and manage ClawRouter as a local LLM ...\n - huggingface-hub: HuggingFace hf CLI: search/download/upload models, datasets.\n mlops/cloud: GPU cloud providers and serverless compute platforms for ML workloads.\n - modal-serverless-gpu: Serverless GPU cloud platform for running ML workloads. U...\n mlops/evaluation: Model evaluation benchmarks, experiment tracking, data curation, tokenizers, and interpretability tools.\n - evaluating-llms-harness: lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).\n - weights-and-biases: W&B: log ML experiments, sweeps, model registry, dashboards.\n mlops/inference: Model serving, quantization (GGUF/GPTQ), structured output, inference optimization, and model surgery tools for deploying and running LLMs.\n - gguf-quantization: GGUF format and llama.cpp quantization for efficient CPU/...\n - guidance: Control LLM output with regex and grammars, guarantee val...\n - llama-cpp: llama.cpp local GGUF inference + HF Hub model discovery.\n - obliteratus: OBLITERATUS: abliterate LLM refusals (diff-in-means).\n - outlines: Outlines: structured JSON/regex/Pydantic LLM generation.\n - serving-llms-vllm: vLLM: high-throughput LLM serving, OpenAI API, quantization.\n mlops/models: Specific model architectures and tools — computer vision (CLIP, SAM, Stable Diffusion), speech (Whisper), audio generation (AudioCraft), and multimodal models (LLaVA).\n - audiocraft-audio-generation: AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.\n - clip: OpenAI's model connecting vision and language. Enables ze...\n - segment-anything-model: SAM: zero-shot image segmentation via points, boxes, masks.\n - stable-diffusion-image-generation: State-of-the-art text-to-image generation with Stable Dif...\n - whisper: OpenAI's general-purpose speech recognition model. Suppor...\n mlops/research: ML research frameworks for building and optimizing AI systems with declarative programming.\n - dspy: DSPy: declarative LM programs, auto-optimize prompts, RAG.\n mlops/training: Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools for training LLMs and other models.\n - axolotl: Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).\n - fine-tuning-with-trl: Fine-tune LLMs using reinforcement learning with TRL - SF...\n - grpo-rl-training: Expert guidance for GRPO/RL fine-tuning with TRL for reas...\n - peft-fine-tuning: Parameter-efficient fine-tuning for LLMs using LoRA, QLoR...\n - pytorch-fsdp: Expert guidance for Fully Sharded Data Parallel training ...\n - unsloth: Unsloth: 2-5x faster LoRA/QLoRA fine-tuning, less VRAM.\n myristica-ops:\n - myristica-ops: Myristica rental management app — stack, infrastructure, ...\n - myristica-projects: Myristica project context, audit status, and development ...\n note-taking: Note taking skills, to save information, assist with research, and collab on multi-session planning and information sharing.\n - obsidian: Read, search, create, and edit notes in the Obsidian vault.\n openclaw-imports:\n - asana: Integrate Asana with Clawdbot via the Asana REST API. Use...\n - bitwarden: Set up and use Bitwarden CLI (bw). Use when installing th...\n - gog: Read-only Google Workspace CLI for Gmail, Calendar, Drive...\n - google-photos: Manage Google Photos library. Upload photos, create album...\n - hevy: Query workout data from Hevy including workouts, routines...\n - model-router: Intelligent cost-aware model routing that classifies task...\n - notion: Notion API for creating and managing pages, databases, an...\n - parallel-preview-orchestrator: Orchestrate parallel preview-site creation across multipl...\n - session-logs: Search and analyze your own session logs (older/parent co...\n - summarize: Summarize URLs or files with the summarize CLI (web, PDFs...\n - weather: Get current weather and forecasts (no API key required).\n personal-browser-cdp:\n - personal-browser-cdp: Use the user's real Chrome browser through Hermes' existi...\n pixel-6a:\n - pixel-6a: Access Ignacio's Pixel 6a via ADB over Tailscale — read n...\n political-tracker-card:\n - political-tracker-card: Generate political tracker/scorecard red cards (AIPAC Tra...\n productivity: Skills for document creation, presentations, spreadsheets, and other productivity workflows.\n - airtable: Airtable REST API via curl. Records CRUD, filters, upserts.\n - google-workspace: Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.\n - linear: Linear: manage issues, projects, teams via GraphQL + curl.\n - maps: Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.\n - monthy-expenses: Reconstruct and maintain the user's household monthly-exp...\n - nano-pdf: Edit PDF text/typos/titles via nano-pdf CLI (NL prompts).\n - notion: Notion API via curl: pages, databases, blocks, search.\n - ocr-and-documents: Extract text from PDFs/scans (pymupdf, marker-pdf).\n - powerpoint: Create, read, edit .pptx decks, slides, notes, templates.\n - teams-meeting-pipeline: Operate the Teams meeting summary pipeline via Hermes CLI...\n red-teaming:\n - godmode: Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.\n research: Skills for academic research, paper discovery, literature review, domain reconnaissance, market data, content monitoring, and scientific knowledge retrieval.\n - arxiv: Search arXiv papers by keyword, author, category, or ID.\n - blogwatcher: Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.\n - llm-wiki: Karpathy's LLM Wiki: build/query interlinked markdown KB.\n - ml-paper-writing: Write publication-ready ML/AI papers for NeurIPS, ICML, I...\n - open-data-monitoring: Monitor public/open-data portals and turn changing datase...\n - polymarket: Query Polymarket: markets, prices, orderbooks, history.\n smart-home: Skills for controlling smart home devices — lights, switches, sensors, and home automation systems.\n - openhue: Control Philips Hue lights, scenes, rooms via OpenHue CLI.\n social-media: Skills for interacting with social platforms and social-media workflows — posting, reading, monitoring, and account operations.\n - xitter: Interact with X/Twitter via the x-cli terminal client usi...\n - xurl: X/Twitter via xurl CLI: post, search, DM, media, v2 API.\n software-development:\n - code-review: Guidelines for performing thorough code reviews with secu...\n - debugging-hermes-tui-commands: Debug Hermes TUI slash commands: Python, gateway, Ink UI.\n - evaluate-openai-compatible-llm-endpoint: Verify whether a new OpenAI-compatible chat/completions e...\n - hermes-agent-skill-authoring: Author in-repo SKILL.md: frontmatter, validator, structure.\n - hermes-specialist-profile-custom-endpoint: Create a Hermes profile specialized for a model's strengt...\n - node-inspect-debugger: Debug Node.js via --inspect + Chrome DevTools Protocol CLI.\n - plan: Plan mode: write markdown plan to .hermes/plans/, no exec.\n - python-debugpy: Debug Python: pdb REPL + debugpy remote (DAP).\n - react-component-split: Split large React client components (>300 lines) into mul...\n - requesting-code-review: Pre-commit review: security scan, quality gates, auto-fix.\n - spike: Throwaway experiments to validate an idea before build.\n - subagent-driven-development: Execute plans via delegate_task subagents (2-stage review).\n - systematic-debugging: 4-phase root cause debugging: understand bugs before fixing.\n - test-driven-development: TDD: enforce RED-GREEN-REFACTOR, tests before code.\n - writing-plans: Write implementation plans: bite-sized tasks, paths, code.\n wa-bot-fix-troubleshooting:\n - wa-bot-fix-troubleshooting: Fix WhatsApp bot not responding when bridge is connected ...\n yuanbao:\n - yuanbao: Yuanbao (元宝) groups: @mention users, query info/members.\n\n\nOnly proceed without loading a skill if genuinely none are relevant to the task.\n\nHost: Linux (6.17.0-1011-oracle)\nUser home directory: /home/ubuntu\nCurrent working directory: /home/ubuntu/.hermes/hermes-agent\n\nYou are in a Discord server or group chat communicating with your user. You can send media files natively: include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) are sent as photo attachments, audio as file attachments. You can also include image URLs in markdown format  and they will be sent as attachments.\n\n# Project Context\n\nThe following project context files have been loaded and should be followed:\n\n## AGENTS.md\n\n# AGENTS.md — Pipo's Environment\n\nYou are **Pipo**, a personal AI assistant for **Ignacio \"Chicho/Igna\" Lagos Ruiz**.\n\n## Your Memory Files (always check these first)\n\n- `~/.hermes/memories/MEMORY.md` — long-term curated memory\n- `~/.hermes/memories/USER.md` — user profile and preferences\n- `~/.hermes/SOUL.md` — your persona and values\n\n## Environment\n\n- Server: Ubuntu 24.04 ARM64, Oracle Cloud São Paulo\n- Tailscale IP: `100.87.116.90`, hostname: `miopenclaw-vnic.tail9799d2.ts.net`\n- Shell: bash, Node.js v22, Python 3.12\n- Your install: `~/.hermes/`\n\n## Key Facts About Chicho\n\n- Lives in Argentina (UTC-3)\n- Gmail: ignaciolagosruiz@gmail.com\n- Prefers direct responses, no filler\n- Prefers text by default, audio only when asked\n- Uses YouTube Music, not Spotify\n- No Apple devices\n- For scraping Argentine retailers: may need exit node via `tailscale set --exit-node=pixel-6a`\n\n## Scraping Exit Node\n\nWhen scraping Argentine sites (Coto, Carrefour, Día, Disco, Jumbo):\n```bash\ntailscale set --exit-node=pixel-6a # enable before scraping\ntailscale set --exit-node='' # disable after\n```\n\n══════════════════════════════════════════════\nMEMORY (your personal notes) [97% — 2,137/2,200 chars]\n══════════════════════════════════════════════\nIf you are reading this during session startup:\n§\nPrefer `MEMORIES.md` for curated long-term memory.\n§\nUse `memory/YYYY-MM-DD.md` files for recent context.\n§\nDo not rely on `exec` just to list files that are already known.\n§\nNo usar Apple, no Spotify (YouTube Music), no Trello (Asana). Audio solo si Chicho lo pide explícitamente. Ya están en el user profile, no repetir.\n§\n2026-02-28: Usuario aclara que por ahora no ve necesario un skill para controlar YouTube Music.\n§\nMyristica WA bot: repo github.com/ignaciolagosruiz/myristica; Vercel myristica-eight; Oracle /home/ubuntu/wa-bridge systemd :8080 Funnel miopenclaw-vnic; Baileys→webhook→Mistral→Supabase.\n§\n2026-04-04: personal-browser-cdp skill creado y testeado. CDP funciona bien via Chrome en Windows + SSH reverse tunnel.\n- lanacion.com.ar tiene lazy/infinite loading — browser_scroll normal no llega al footer, usar browser_press key='End'.\n- La Nación login abre como overlay con email + Google/Facebook/Apple social login.\n§\nHermes WebUI session deletion is permanent (no trash). But CODE changes persist as uncommitted git changes in ~/hermes-webui/. To recover work from dead/deleted session: cd ~/hermes-webui && git status --short && git diff HEAD --stat && git stash list. Session JSON files (~/.hermes/webui/sessions/*.json) ARE gone permanently.\n§\nUser (Chicho) prefers direct, no-filler communication. Environment: Ubuntu 24.04 ARM64, Oracle Cloud. WebUI source at ~/hermes-webui. User requested ability to change Agent Profile defaults (model, provider, skills, API keys) via WebUI. Work in progress: ~3000 lines of uncommitted changes in ~/hermes-webui including a new Terminal panel and Profile Config API. Found bug in api/routes.py: 'if val is None and val == \"\"' (should be 'or').\n§\n2026-04-30: Lección clave de Chicho — Cuando algo falla (anti-bot, modelo, config), NO poner excusas. Buscar plan B/C/D sin rodeos. Camoufox para scraping anti-DataDome, Gemini 3.0 Flash para vision, skill-switching para limitaciones. Soluciones > explicaciones. También: vision config fijada a `google/gemini-3-flash-preview` via OpenRouter. Chicho prefiere 3.0, no discutir.\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [98% — 1,350/1,375 chars]\n══════════════════════════════════════════════\n_Learn about the person you're helping. Update this as you go._\n§\n**Name:** Ignacio (Igna, also goes by Chicho)\n§\n**What to call them:** Igna or Chicho\n§\n**Pronouns:** _(not specified)_\n§\n**Timezone:** UTC-3 (Buenos Aires, Argentina)\n§\n**Notes:**\n§\nNo usa dispositivos Apple\n§\nPrefiere YouTube Music (no Spotify)\n§\nPrefiere Asana sobre Trello\n§\nPrefiere respuestas en texto por defecto (para ahorrar tokens de ElevenLabs)\n§\nAudio solo cuando él lo pida explícitamente\n§\nPrefiere respuestas breves/directas; en APIs exige leer docs/OpenAPI y ejemplos válidos antes de probar.\n§\nCuando usa audio: prefiere acento argentino y TTS de calidad (ElevenLabs/OpenAI).\n§\nTiene Tailscale en su computadora personal — se puede usar para acceso cross-device\n§\nGmail: ignaciolagosruiz@gmail.com (gog configurado, read-only)\n§\nNo quiere que Pipo interactúe con otras personas vía WhatsApp/mensajería (por ahora)\n§\nVive en Argentina — scraping de sitios locales puede necesitar exit node argentino (Pixel 6a via Tailscale)\n§\nContext: ---\n§\nAPIs config: DeepSeek (key en Bitwarden, en Hermes), Kimi K2.5, Mistral ($10), OpenRouter ($0.53 backup), ClawRouter wallet 0x1d1776D... ($11.70 Base). DeepSeek/Kimi NO como daily driver — solo workers/subagentes.\n§\nDog name is Chivi (with v), not Chibi. Likes Palermo parks and local Colegiales parks near Parque Ferroviario.\n\n# Honcho Memory\nActive (hybrid mode). Relevant context is auto-injected AND memory tools are available. Use honcho_profile for a quick factual snapshot, honcho_search for raw excerpts, honcho_context for raw peer context, honcho_reasoning for synthesized answers (pass reasoning_level minimal/low/medium/high/max — you pick the depth per call), honcho_conclude to save facts about the user.\n\nConversation started: Wednesday, May 13, 2026 02:02 PM\nModel: gpt-5.5\nProvider: openai-codex",
"tools": [
{
"type": "function",
"function": {
"name": "browser_back",
"description": "Navigate back to the previous page in browser history. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {}
}
}
},
{
"type": "function",
"function": {
"name": "browser_cdp",
"description": "Send a raw Chrome DevTools Protocol (CDP) command. Escape hatch for browser operations not covered by browser_navigate, browser_click, browser_console, etc.\n\n**Requires a reachable CDP endpoint.** Available when the user has run '/browser connect' to attach to a running Chrome, or when 'browser.cdp_url' is set in config.yaml. Not currently wired up for cloud backends (Browserbase, Browser Use, Firecrawl) — those expose CDP per session but live-session routing is a follow-up. Camofox is REST-only and will never support CDP. If the tool is in your toolset at all, a CDP endpoint is already reachable.\n\n**CDP method reference:** https://chromedevtools.github.io/devtools-protocol/ — use web_extract on a method's URL (e.g. '/tot/Page/#method-handleJavaScriptDialog') to look up parameters and return shape.\n\n**Common patterns:**\n- List tabs: method='Target.getTargets', params={}\n- Handle a native JS dialog: method='Page.handleJavaScriptDialog', params={'accept': true, 'promptText': ''}, target_id=\n- Get all cookies: method='Network.getAllCookies', params={}\n- Eval in a specific tab: method='Runtime.evaluate', params={'expression': '...', 'returnByValue': true}, target_id=\n- Set viewport for a tab: method='Emulation.setDeviceMetricsOverride', params={'width': 1280, 'height': 720, 'deviceScaleFactor': 1, 'mobile': false}, target_id=\n\n**Usage rules:**\n- Browser-level methods (Target.*, Browser.*, Storage.*): omit target_id and frame_id.\n- Page-level methods (Page.*, Runtime.*, DOM.*, Emulation.*, Network.* scoped to a tab): pass target_id from Target.getTargets.\n- **Cross-origin iframe scope** (Runtime.evaluate inside an OOPIF, Page.* targeting a frame target, etc.): pass frame_id from the browser_snapshot frame_tree output. This routes through the CDP supervisor's live connection — the only reliable way on Browserbase where stateless CDP calls hit signed-URL expiry.\n- Each stateless call (without frame_id) is independent — sessions and event subscriptions do not persist between calls. For stateful workflows, prefer the dedicated browser tools or use frame_id routing.",
"parameters": {
"type": "object",
"properties": {
"method": {
"type": "string",
"description": "CDP method name, e.g. 'Target.getTargets', 'Runtime.evaluate', 'Page.handleJavaScriptDialog'."
},
"params": {
"type": "object",
"description": "Method-specific parameters as a JSON object. Omit or pass {} for methods that take no parameters.",
"properties": {},
"additionalProperties": true
},
"target_id": {
"type": "string",
"description": "Optional. Target/tab ID from Target.getTargets result (each entry's 'targetId'). Use for page-level methods at the top-level tab scope. Mutually exclusive with frame_id."
},
"frame_id": {
"type": "string",
"description": "Optional. Out-of-process iframe (OOPIF) frame_id from browser_snapshot.frame_tree.children[] where is_oopif=true. When set, routes the call through the CDP supervisor's live session for that iframe. Essential for Runtime.evaluate inside cross-origin iframes, especially on Browserbase where fresh per-call CDP connections can't keep up with signed URL rotation. For same-origin iframes, use parent contentWindow/contentDocument from Runtime.evaluate at the top-level page instead."
},
"timeout": {
"type": "number",
"description": "Timeout in seconds (default 30, max 300).",
"default": 30
}
},
"required": [
"method"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_click",
"description": "Click on an element identified by its ref ID from the snapshot (e.g., '@e5'). The ref IDs are shown in square brackets in the snapshot output. Requires browser_navigate and browser_snapshot to be called first.",
"parameters": {
"type": "object",
"properties": {
"ref": {
"type": "string",
"description": "The element reference from the snapshot (e.g., '@e5', '@e12')"
}
},
"required": [
"ref"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_console",
"description": "Get browser console output and JavaScript errors from the current page. Returns console.log/warn/error/info messages and uncaught JS exceptions. Use this to detect silent JavaScript errors, failed API calls, and application warnings. Requires browser_navigate to be called first. When 'expression' is provided, evaluates JavaScript in the page context and returns the result — use this for DOM inspection, reading page state, or extracting data programmatically.",
"parameters": {
"type": "object",
"properties": {
"clear": {
"type": "boolean",
"default": false,
"description": "If true, clear the message buffers after reading"
},
"expression": {
"type": "string",
"description": "JavaScript expression to evaluate in the page context. Runs in the browser like DevTools console — full access to DOM, window, document. Return values are serialized to JSON. Example: 'document.title' or 'document.querySelectorAll(\"a\").length'"
}
}
}
}
},
{
"type": "function",
"function": {
"name": "browser_dialog",
"description": "Respond to a native JavaScript dialog (alert / confirm / prompt / beforeunload) that is currently blocking the page.\n\n**Workflow:** call ``browser_snapshot`` first — if a dialog is open, it appears in the ``pending_dialogs`` field with ``id``, ``type``, and ``message``. Then call this tool with ``action='accept'`` or ``action='dismiss'``.\n\n**Prompt dialogs:** pass ``prompt_text`` to supply the response string. Ignored for alert/confirm/beforeunload.\n\n**Multiple dialogs:** if more than one dialog is queued (rare — happens when a second dialog fires while the first is still open), pass ``dialog_id`` from the snapshot to disambiguate.\n\n**Availability:** only present when a CDP-capable backend is attached — Browserbase sessions, local Chrome via ``/browser connect``, or ``browser.cdp_url`` in config.yaml. Not available on Camofox (REST-only) or the default Playwright local browser (CDP port is hidden).",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"accept",
"dismiss"
],
"description": "'accept' clicks OK / returns the prompt text. 'dismiss' clicks Cancel / returns null from prompt(). For ``beforeunload`` dialogs: 'accept' allows the navigation, 'dismiss' keeps the page."
},
"prompt_text": {
"type": "string",
"description": "Response string for a ``prompt()`` dialog. Ignored for other dialog types. Defaults to empty string."
},
"dialog_id": {
"type": "string",
"description": "Specific dialog to respond to, from ``browser_snapshot.pending_dialogs[].id``. Required only when multiple dialogs are queued."
}
},
"required": [
"action"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_get_images",
"description": "Get a list of all images on the current page with their URLs and alt text. Useful for finding images to analyze with the vision tool. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {}
}
}
},
{
"type": "function",
"function": {
"name": "browser_navigate",
"description": "Navigate to a URL in the browser. Initializes the session and loads the page. Must be called before other browser tools. For simple information retrieval, prefer web_search or web_extract (faster, cheaper). For plain-text endpoints — URLs ending in .md, .txt, .json, .yaml, .yml, .csv, .xml, raw.githubusercontent.com, or any documented API endpoint — prefer curl via the terminal tool or web_extract; the browser stack is overkill and much slower for these. Use browser tools when you need to interact with a page (click, fill forms, dynamic content). Returns a compact page snapshot with interactive elements and ref IDs — no need to call browser_snapshot separately after navigating.",
"parameters": {
"type": "object",
"properties": {
"url": {
"type": "string",
"description": "The URL to navigate to (e.g., 'https://example.com')"
}
},
"required": [
"url"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_press",
"description": "Press a keyboard key. Useful for submitting forms (Enter), navigating (Tab), or keyboard shortcuts. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {
"key": {
"type": "string",
"description": "Key to press (e.g., 'Enter', 'Tab', 'Escape', 'ArrowDown')"
}
},
"required": [
"key"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_scroll",
"description": "Scroll the page in a direction. Use this to reveal more content that may be below or above the current viewport. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {
"direction": {
"type": "string",
"enum": [
"up",
"down"
],
"description": "Direction to scroll"
}
},
"required": [
"direction"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_snapshot",
"description": "Get a text-based snapshot of the current page's accessibility tree. Returns interactive elements with ref IDs (like @e1, @e2) for browser_click and browser_type. full=false (default): compact view with interactive elements. full=true: complete page content. Snapshots over 8000 chars are truncated or LLM-summarized. Requires browser_navigate first. Note: browser_navigate already returns a compact snapshot — use this to refresh after interactions that change the page, or with full=true for complete content.",
"parameters": {
"type": "object",
"properties": {
"full": {
"type": "boolean",
"description": "If true, returns complete page content. If false (default), returns compact view with interactive elements only.",
"default": false
}
}
}
}
},
{
"type": "function",
"function": {
"name": "browser_type",
"description": "Type text into an input field identified by its ref ID. Clears the field first, then types the new text. Requires browser_navigate and browser_snapshot to be called first.",
"parameters": {
"type": "object",
"properties": {
"ref": {
"type": "string",
"description": "The element reference from the snapshot (e.g., '@e3')"
},
"text": {
"type": "string",
"description": "The text to type into the field"
}
},
"required": [
"ref",
"text"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_vision",
"description": "Take a screenshot of the current page and analyze it with vision AI. Use this when you need to visually understand what's on the page - especially useful for CAPTCHAs, visual verification challenges, complex layouts, or when the text snapshot doesn't capture important visual information. Returns both the AI analysis and a screenshot_path that you can share with the user by including MEDIA: in your response. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {
"question": {
"type": "string",
"description": "What you want to know about the page visually. Be specific about what you're looking for."
},
"annotate": {
"type": "boolean",
"default": false,
"description": "If true, overlay numbered [N] labels on interactive elements. Each [N] maps to ref @eN for subsequent browser commands. Useful for QA and spatial reasoning about page layout."
}
},
"required": [
"question"
]
}
}
},
{
"type": "function",
"function": {
"name": "clarify",
"description": "Ask the user a question when you need clarification, feedback, or a decision before proceeding. Supports two modes:\n\n1. **Multiple choice** — provide up to 4 choices. The user picks one or types their own answer via a 5th 'Other' option.\n2. **Open-ended** — omit choices entirely. The user types a free-form response.\n\nUse this tool when:\n- The task is ambiguous and you need the user to choose an approach\n- You want post-task feedback ('How did that work out?')\n- You want to offer to save a skill or update memory\n- A decision has meaningful trade-offs the user should weigh in on\n\nDo NOT use this tool for simple yes/no confirmation of dangerous commands (the terminal tool handles that). Prefer making a reasonable default choice yourself when the decision is low-stakes.",
"parameters": {
"type": "object",
"properties": {
"question": {
"type": "string",
"description": "The question to present to the user."
},
"choices": {
"type": "array",
"items": {
"type": "string"
},
"maxItems": 4,
"description": "Up to 4 answer choices. Omit this parameter entirely to ask an open-ended question. When provided, the UI automatically appends an 'Other (type your answer)' option."
}
},
"required": [
"question"
]
}
}
},
{
"type": "function",
"function": {
"name": "cronjob",
"description": "Manage scheduled cron jobs with a single compressed tool.\n\nUse action='create' to schedule a new job from a prompt or one or more skills.\nUse action='list' to inspect jobs.\nUse action='update', 'pause', 'resume', 'remove', or 'run' to manage an existing job.\n\nTo stop a job the user no longer wants: first action='list' to find the job_id, then action='remove' with that job_id. Never guess job IDs — always list first.\n\nJobs run in a fresh session with no current-chat context, so prompts must be self-contained.\nIf skills are provided on create, the future cron run loads those skills in order, then follows the prompt as the task instruction.\nOn update, passing skills=[] clears attached skills.\n\nNOTE: The agent's final response is auto-delivered to the target. Put the primary\nuser-facing content in the final response. Cron jobs run autonomously with no user\npresent — they cannot ask questions or request clarification.\n\nImportant safety rule: cron-run sessions should not recursively schedule more cron jobs.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"description": "One of: create, list, update, pause, resume, remove, run"
},
"job_id": {
"type": "string",
"description": "Required for update/pause/resume/remove/run"
},
"prompt": {
"type": "string",
"description": "For create: the full self-contained prompt. If skills are also provided, this becomes the task instruction paired with those skills."
},
"schedule": {
"type": "string",
"description": "For create/update: '30m', 'every 2h', '0 9 * * *', or ISO timestamp"
},
"name": {
"type": "string",
"description": "Optional human-friendly name"
},
"repeat": {
"type": "integer",
"description": "Optional repeat count. Omit for defaults (once for one-shot, forever for recurring)."
},
"deliver": {
"type": "string",
"description": "Omit this parameter to auto-deliver back to the current chat and topic (recommended). Auto-detection preserves thread/topic context. Only set explicitly when the user asks to deliver somewhere OTHER than the current conversation. Values: 'origin' (same as omitting), 'local' (no delivery, save only), 'all' (fan out to every connected home channel), or platform:chat_id:thread_id for a specific destination. Combine with comma: 'origin,all' delivers to the origin plus every other connected channel. Examples: 'telegram:-1001234567890:17585', 'discord:#engineering', 'sms:+15551234567', 'all'. WARNING: 'platform:chat_id' without :thread_id loses topic targeting. 'all' resolves at fire time, so a job created before a channel was wired up will pick it up automatically once connected."
},
"skills": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional ordered list of skill names to load before executing the cron prompt. On update, pass an empty array to clear attached skills."
},
"model": {
"type": "object",
"description": "Optional per-job model override. If provider is omitted, the current main provider is pinned at creation time so the job stays stable.",
"properties": {
"provider": {
"type": "string",
"description": "Provider name (e.g. 'openrouter', 'anthropic', or 'custom:' for a provider defined in custom_providers config — always include the ':' suffix, never pass the bare 'custom'). Omit to use and pin the current provider."
},
"model": {
"type": "string",
"description": "Model name (e.g. 'anthropic/claude-sonnet-4', 'claude-sonnet-4')"
}
},
"required": [
"model"
]
},
"script": {
"type": "string",
"description": "Optional path to a script that runs each tick. In the default mode its stdout is injected into the agent's prompt as context (data-collection / change-detection pattern). With no_agent=True, the script IS the job and its stdout is delivered verbatim (classic watchdog pattern). Relative paths resolve under ~/.hermes/scripts/. ``.sh``/``.bash`` extensions run via bash, everything else via Python. On update, pass empty string to clear."
},
"no_agent": {
"type": "boolean",
"default": false,
"description": "Default: False (LLM-driven job — the agent runs the prompt each tick). Set True to skip the LLM entirely: the scheduler just runs ``script`` on schedule and delivers its stdout verbatim. No tokens, no agent loop, no model override honoured. \n\nREQUIREMENTS when True: ``script`` MUST be set (``prompt`` and ``skills`` are ignored). \n\nDELIVERY SEMANTICS when True: (a) non-empty stdout is sent verbatim as the message; (b) EMPTY stdout means SILENT — nothing is sent to the user and they won't see anything happened, so design your script to stay quiet when there's nothing to report (the watchdog pattern); (c) non-zero exit / timeout sends an error alert so a broken watchdog can't fail silently. \n\nWHEN TO USE True: recurring script-only pings where the script itself produces the exact message text (memory/disk/GPU watchdogs, threshold alerts, heartbeats, CI notifications, API pollers with a fixed output shape). WHEN TO USE False (default): anything that needs reasoning — summarize a feed, draft a daily briefing, pick interesting items, rephrase data for a human, follow conditional logic based on content."
},
"context_from": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional job ID or list of job IDs whose most recent completed output is injected into the prompt as context before each run. Use this to chain cron jobs: job A collects data, job B processes it. Each entry must be a valid job ID (from cronjob action='list'). Note: injects the most recent completed output — does not wait for upstream jobs running in the same tick. On update, pass an empty array to clear."
},
"enabled_toolsets": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional list of toolset names to restrict the job's agent to (e.g. [\"web\", \"terminal\", \"file\", \"delegation\"]). When set, only tools from these toolsets are loaded, significantly reducing input token overhead. When omitted, all default tools are loaded. Infer from the job's prompt — e.g. use \"web\" if it calls web_search, \"terminal\" if it runs scripts, \"file\" if it reads files, \"delegation\" if it calls delegate_task. On update, pass an empty array to clear."
},
"workdir": {
"type": "string",
"description": "Optional absolute path to run the job from. When set, AGENTS.md / CLAUDE.md / .cursorrules from that directory are injected into the system prompt, and the terminal/file/code_exec tools use it as their working directory — useful for running a job inside a specific project repo. Must be an absolute path that exists. When unset (default), preserves the original behaviour: no project context files, tools use the scheduler's cwd. On update, pass an empty string to clear. Jobs with workdir run sequentially (not parallel) to keep per-job directories isolated."
}
},
"required": [
"action"
]
}
}
},
{
"type": "function",
"function": {
"name": "delegate_task",
"description": "Spawn one or more subagents to work on tasks in isolated contexts. Each subagent gets its own conversation, terminal session, and toolset. Only the final summary is returned -- intermediate tool results never enter your context window.\n\nTWO MODES (one of 'goal' or 'tasks' is required):\n1. Single task: provide 'goal' (+ optional context, toolsets)\n2. Batch (parallel): provide 'tasks' array with up to 3 items concurrently for this user (configured via delegation.max_concurrent_children in config.yaml). All run in parallel and results are returned together. Nested delegation is OFF for this user (max_spawn_depth=1): every child is a leaf and cannot delegate further. Raise delegation.max_spawn_depth in config.yaml to enable nesting.\n\nWHEN TO USE delegate_task:\n- Reasoning-heavy subtasks (debugging, code review, research synthesis)\n- Tasks that would flood your context with intermediate data\n- Parallel independent workstreams (research A and B simultaneously)\n\nWHEN NOT TO USE (use these instead):\n- Mechanical multi-step work with no reasoning needed -> use execute_code\n- Single tool call -> just call the tool directly\n- Tasks needing user interaction -> subagents cannot use clarify\n- Durable long-running work that must outlive the current turn -> use cronjob (action='create') or terminal(background=True, notify_on_complete=True) instead. delegate_task runs SYNCHRONOUSLY inside the parent turn: if the parent is interrupted (user sends a new message, /stop, /new) the child is cancelled with status='interrupted' and its work is discarded. Children cannot continue in the background.\n\nIMPORTANT:\n- Subagents have NO memory of your conversation. Pass all relevant info (file paths, error messages, constraints) via the 'context' field.\n- If the user is writing in a non-English language, or asked for output in a specific language / tone / style, say so in 'context' (e.g. \"respond in Chinese\", \"return output in Japanese\"). Otherwise subagents default to English and their summaries will contaminate your final reply with the wrong language.\n- Subagent summaries are SELF-REPORTS, not verified facts. A subagent that claims \"uploaded successfully\" or \"file written\" may be wrong. For operations with external side-effects (HTTP POST/PUT, remote writes, file creation at shared paths, publishing), require the subagent to return a verifiable handle (URL, ID, absolute path, HTTP status) and verify it yourself — fetch the URL, stat the file, read back the content — before telling the user the operation succeeded.\n- Leaf subagents (role='leaf', the default) CANNOT call: delegate_task, clarify, memory, send_message, execute_code.\n- Orchestrator subagents (role='orchestrator') retain delegate_task so they can spawn their own workers, but still cannot use clarify, memory, send_message, or execute_code. Orchestrators are bounded by max_spawn_depth=1 for this user and can be disabled globally via delegation.orchestrator_enabled=false.\n- Each subagent gets its own terminal session (separate working directory and state).\n- Results are always returned as an array, one entry per task.",
"parameters": {
"type": "object",
"properties": {
"goal": {
"type": "string",
"description": "What the subagent should accomplish. Be specific and self-contained -- the subagent knows nothing about your conversation history."
},
"context": {
"type": "string",
"description": "Background information the subagent needs: file paths, error messages, project structure, constraints. The more specific you are, the better the subagent performs."
},
"toolsets": {
"type": "array",
"items": {
"type": "string"
},
"description": "Toolsets to enable for this subagent. Default: inherits your enabled toolsets. Available toolsets: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'vision', 'web', 'yuanbao'. Common patterns: ['terminal', 'file'] for code work, ['web'] for research, ['browser'] for web interaction, ['terminal', 'file', 'web'] for full-stack tasks."
},
"tasks": {
"type": "array",
"items": {
"type": "object",
"properties": {
"goal": {
"type": "string",
"description": "Task goal"
},
"context": {
"type": "string",
"description": "Task-specific context"
},
"toolsets": {
"type": "array",
"items": {
"type": "string"
},
"description": "Toolsets for this specific task. Available: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'vision', 'web', 'yuanbao'. Use 'web' for network access, 'terminal' for shell, 'browser' for web interaction."
},
"acp_command": {
"type": "string",
"description": "Per-task ACP command override (e.g. 'copilot'). Overrides the top-level acp_command for this task only. Do NOT set unless the user explicitly told you an ACP CLI is installed."
},
"acp_args": {
"type": "array",
"items": {
"type": "string"
},
"description": "Per-task ACP args override. Leave empty unless acp_command is set."
},
"role": {
"type": "string",
"enum": [
"leaf",
"orchestrator"
],
"description": "Per-task role override. See top-level 'role' for semantics."
}
},
"required": [
"goal"
]
},
"description": "Batch mode: tasks to run in parallel (up to 3 for this user, set via delegation.max_concurrent_children). Each gets its own subagent with isolated context and terminal session. When provided, top-level goal/context/toolsets are ignored."
},
"role": {
"type": "string",
"enum": [
"leaf",
"orchestrator"
],
"description": "Role of the child agent. 'leaf' (default) = focused worker, cannot delegate further. 'orchestrator' = can use delegate_task to spawn its own workers. Nesting is OFF for this user (max_spawn_depth=1); 'orchestrator' is silently forced to 'leaf'. Raise delegation.max_spawn_depth in config.yaml to enable."
},
"acp_command": {
"type": "string",
"description": "Override ACP command for child agents (e.g. 'copilot'). When set, children use ACP subprocess transport instead of inheriting the parent's transport. Requires an ACP-compatible CLI (currently GitHub Copilot CLI via 'copilot --acp --stdio'). See agent/copilot_acp_client.py for the implementation. IMPORTANT: Do NOT set this unless the user has explicitly told you a specific ACP-compatible CLI is installed and configured. Leave empty to use the parent's default transport (Hermes subagents)."
},
"acp_args": {
"type": "array",
"items": {
"type": "string"
},
"description": "Arguments for the ACP command (default: ['--acp', '--stdio']). Only used when acp_command is set. Leave empty unless acp_command is explicitly provided."
}
}
}
}
},
{
"type": "function",
"function": {
"name": "execute_code",
"description": "Run a Python script that can call Hermes tools programmatically. Use this when you need 3+ tool calls with processing logic between them, need to filter/reduce large tool outputs before they enter your context, need conditional branching (if X then Y else Z), or need to loop (fetch N pages, process N files, retry on failure).\n\nUse normal tool calls instead when: single tool call with no processing, you need to see the full result and apply complex reasoning, or the task requires interactive user input.\n\nAvailable via `from hermes_tools import ...`:\n\n web_search(query: str, limit: int = 5) -> dict\n Returns {\"data\": {\"web\": [{\"url\", \"title\", \"description\"}, ...]}}\n web_extract(urls: list[str]) -> dict\n Returns {\"results\": [{\"url\", \"title\", \"content\", \"error\"}, ...]} where content is markdown\n read_file(path: str, offset: int = 1, limit: int = 500) -> dict\n Lines are 1-indexed. Returns {\"content\": \"...\", \"total_lines\": N}\n write_file(path: str, content: str) -> dict\n Always overwrites the entire file.\n search_files(pattern: str, target=\"content\", path=\".\", file_glob=None, limit=50) -> dict\n target: \"content\" (search inside files) or \"files\" (find files by name). Returns {\"matches\": [...]}\n patch(path: str, old_string: str, new_string: str, replace_all: bool = False) -> dict\n Replaces old_string with new_string in the file.\n terminal(command: str, timeout=None, workdir=None) -> dict\n Foreground only (no background/pty). Returns {\"output\": \"...\", \"exit_code\": N}\n\nLimits: 5-minute timeout, 50KB stdout cap, max 50 tool calls per script. terminal() is foreground-only (no background or pty).\n\nScripts run in the session's working directory with the active venv's python, so project deps (pandas, etc.) and relative paths work like in terminal().\n\nPrint your final result to stdout. Use Python stdlib (json, re, math, csv, datetime, collections, etc.) for processing between tool calls.\n\nAlso available (no import needed — built into hermes_tools):\n json_parse(text: str) — json.loads with strict=False; use for terminal() output with control chars\n shell_quote(s: str) — shlex.quote(); use when interpolating dynamic strings into shell commands\n retry(fn, max_attempts=3, delay=2) — retry with exponential backoff for transient failures",
"parameters": {
"type": "object",
"properties": {
"code": {
"type": "string",
"description": "Python code to execute. Import tools with `from hermes_tools import web_search, terminal, ...` and print your final result to stdout."
}
},
"required": [
"code"
]
}
}
},
{
"type": "function",
"function": {
"name": "image_generate",
"description": "Generate high-quality images from text prompts. The underlying backend (FAL, OpenAI, etc.) and model are user-configured and not selectable by the agent. Returns either a URL or an absolute file path in the `image` field; display it with markdown  and the gateway will deliver it.",
"parameters": {
"type": "object",
"properties": {
"prompt": {
"type": "string",
"description": "The text prompt describing the desired image. Be detailed and descriptive."
},
"aspect_ratio": {
"type": "string",
"enum": [
"landscape",
"square",
"portrait"
],
"description": "The aspect ratio of the generated image. 'landscape' is 16:9 wide, 'portrait' is 16:9 tall, 'square' is 1:1.",
"default": "landscape"
}
},
"required": [
"prompt"
]
}
}
},
{
"type": "function",
"function": {
"name": "mcp_context7_query_docs",
"description": "Retrieves and queries up-to-date documentation and code examples from Context7 for any programming library or framework.\n\nYou must call 'Resolve Context7 Library ID' tool first to obtain the exact Context7-compatible library ID required to use this tool, UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.\n\nDo not call this tool more than 3 times per question.",
"parameters": {
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"libraryId": {
"type": "string",
"description": "Exact Context7-compatible library ID (e.g., '/mongodb/docs', '/vercel/next.js', '/supabase/supabase', '/vercel/next.js/v14.3.0-canary.87') retrieved from 'resolve-library-id' or directly from user query in the format '/org/project' or '/org/project/version'."
},
"query": {
"type": "string",
"description": "The question or task you need help with. Be specific and include relevant details. Good: 'How to set up authentication with JWT in Express.js' or 'React useEffect cleanup function examples'. Bad: 'auth' or 'hooks'. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query."
}
},
"required": [
"libraryId",
"query"
]
}
}
},
{
"type": "function",
"function": {
"name": "mcp_context7_resolve_library_id",
"description": "Resolves a package/product name to a Context7-compatible library ID and returns matching libraries.\n\nYou MUST call this function before 'Query Documentation' tool to obtain a valid Context7-compatible library ID UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.\n\nEach result includes:\n- Library ID: Context7-compatible identifier (format: /org/project)\n- Name: Library or package name\n- Description: Short summary\n- Code Snippets: Number of available code examples\n- Source Reputation: Authority indicator (High, Medium, Low, or Unknown)\n- Benchmark Score: Quality indicator (100 is the highest score)\n- Versions: List of versions if available. Use one of those versions if the user provides a version in their query. The format of the version is /org/project/version.\n\nFor best results, select libraries based on name match, source reputation, snippet coverage, benchmark score, and relevance to your use case.\n\nSelection Process:\n1. Analyze the query to understand what library/package the user is looking for\n2. Return the most relevant match based on:\n- Name similarity to the query (exact matches prioritized)\n- Description relevance to the query's intent\n- Documentation coverage (prioritize libraries with higher Code Snippet counts)\n- Source reputation (consider libraries with High or Medium reputation more authoritative)\n- Benchmark Score: Quality indicator (100 is the highest score)\n\nResponse Format:\n- Return the selected library ID in a clearly marked section\n- Provide a brief explanation for why this library was chosen\n- If multiple good matches exist, acknowledge this but proceed with the most relevant one\n- If no good matches exist, clearly state this and suggest query refinements\n\nFor ambiguous queries, request clarification before proceeding with a best-guess match.\n\nIMPORTANT: Do not call this tool more than 3 times per question. If you cannot find what you need after 3 calls, use the best result you have.",
"parameters": {
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The question or task you need help with. This is used to rank library results by relevance to what the user is trying to accomplish. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query."
},
"libraryName": {
"type": "string",
"description": "Library name to search for and retrieve a Context7-compatible library ID. Use the official library name with proper punctuation — e.g., 'Next.js' instead of 'nextjs', 'Customer.io' instead of 'customerio', 'Three.js' instead of 'threejs'."
}
},
"required": [
"query",
"libraryName"
]
}
}
},
{
"type": "function",
"function": {
"name": "memory",
"description": "Save durable information to persistent memory that survives across sessions. Memory is injected into future turns, so keep it compact and focused on facts that will still matter later.\n\nWHEN TO SAVE (do this proactively, don't wait to be asked):\n- User corrects you or says 'remember this' / 'don't do that again'\n- User shares a preference, habit, or personal detail (name, role, timezone, coding style)\n- You discover something about the environment (OS, installed tools, project structure)\n- You learn a convention, API quirk, or workflow specific to this user's setup\n- You identify a stable fact that will be useful again in future sessions\n\nPRIORITY: User preferences and corrections > environment facts > procedural knowledge. The most valuable memory prevents the user from having to repeat themselves.\n\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts.\nIf you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\n\nTWO TARGETS:\n- 'user': who the user is -- name, role, preferences, communication style, pet peeves\n- 'memory': your notes -- environment facts, project conventions, tool quirks, lessons learned\n\nACTIONS: add (new entry), replace (update existing -- old_text identifies it), remove (delete -- old_text identifies it).\n\nSKIP: trivial/obvious info, things easily re-discovered, raw data dumps, and temporary task state.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"add",
"replace",
"remove"
],
"description": "The action to perform."
},
"target": {
"type": "string",
"enum": [
"memory",
"user"
],
"description": "Which memory store: 'memory' for personal notes, 'user' for user profile."
},
"content": {
"type": "string",
"description": "The entry content. Required for 'add' and 'replace'."
},
"old_text": {
"type": "string",
"description": "Short unique substring identifying the entry to replace or remove."
}
},
"required": [
"action",
"target"
]
}
}
},
{
"type": "function",
"function": {
"name": "mixture_of_agents",
"description": "Route a hard problem through multiple frontier LLMs collaboratively. Makes 5 API calls (4 reference models + 1 aggregator) with maximum reasoning effort — use sparingly for genuinely difficult problems. Best for: complex math, advanced algorithms, multi-step analytical reasoning, problems benefiting from diverse perspectives.",
"parameters": {
"type": "object",
"properties": {
"user_prompt": {
"type": "string",
"description": "The complex query or problem to solve using multiple AI models. Should be a challenging problem that benefits from diverse perspectives and collaborative reasoning."
}
},
"required": [
"user_prompt"
]
}
}
},
{
"type": "function",
"function": {
"name": "patch",
"description": "Targeted find-and-replace edits in files. Use this instead of sed/awk in terminal. Uses fuzzy matching (9 strategies) so minor whitespace/indentation differences won't break it. Returns a unified diff. Auto-runs syntax checks after editing.\n\nREPLACE MODE (mode='replace', default): find a unique string and replace it. REQUIRED PARAMETERS: mode, path, old_string, new_string.\nPATCH MODE (mode='patch'): apply V4A multi-file patches for bulk changes. REQUIRED PARAMETERS: mode, patch.",
"parameters": {
"type": "object",
"properties": {
"mode": {
"type": "string",
"enum": [
"replace",
"patch"
],
"description": "Edit mode. 'replace' (default): requires path + old_string + new_string. 'patch': requires patch content only.",
"default": "replace"
},
"path": {
"type": "string",
"description": "REQUIRED when mode='replace'. File path to edit."
},
"old_string": {
"type": "string",
"description": "REQUIRED when mode='replace'. Exact text to find and replace. Must be unique in the file unless replace_all=true. Include surrounding context lines to ensure uniqueness."
},
"new_string": {
"type": "string",
"description": "REQUIRED when mode='replace'. Replacement text. Pass empty string '' to delete the matched text."
},
"replace_all": {
"type": "boolean",
"description": "Replace all occurrences instead of requiring a unique match (default: false)",
"default": false
},
"patch": {
"type": "string",
"description": "REQUIRED when mode='patch'. V4A format patch content. Format:\n*** Begin Patch\n*** Update File: path/to/file\n@@ context hint @@\n context line\n-removed line\n+added line\n*** End Patch"
}
},
"required": [
"mode"
]
}
}
},
{
"type": "function",
"function": {
"name": "process",
"description": "Manage background processes started with terminal(background=true). Actions: 'list' (show all), 'poll' (check status + new output), 'log' (full output with pagination), 'wait' (block until done or timeout), 'kill' (terminate), 'write' (send raw stdin data without newline), 'submit' (send data + Enter, for answering prompts), 'close' (close stdin/send EOF).",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"list",
"poll",
"log",
"wait",
"kill",
"write",
"submit",
"close"
],
"description": "Action to perform on background processes"
},
"session_id": {
"type": "string",
"description": "Process session ID (from terminal background output). Required for all actions except 'list'."
},
"data": {
"type": "string",
"description": "Text to send to process stdin (for 'write' and 'submit' actions)"
},
"timeout": {
"type": "integer",
"description": "Max seconds to block for 'wait' action. Returns partial output on timeout.",
"minimum": 1
},
"offset": {
"type": "integer",
"description": "Line offset for 'log' action (default: last 200 lines)"
},
"limit": {
"type": "integer",
"description": "Max lines to return for 'log' action",
"minimum": 1
}
},
"required": [
"action"
]
}
}
},
{
"type": "function",
"function": {
"name": "read_file",
"description": "Read a text file with line numbers and pagination. Use this instead of cat/head/tail in terminal. Output format: 'LINE_NUM|CONTENT'. Suggests similar filenames if not found. Use offset and limit for large files. Reads exceeding ~100K characters are rejected; use offset and limit to read specific sections of large files. NOTE: Cannot read images or binary files — use vision_analyze for images.",
"parameters": {
"type": "object",
"properties": {
"path": {
"type": "string",
"description": "Path to the file to read (absolute, relative, or ~/path)"
},
"offset": {
"type": "integer",
"description": "Line number to start reading from (1-indexed, default: 1)",
"default": 1,
"minimum": 1
},
"limit": {
"type": "integer",
"description": "Maximum number of lines to read (default: 500, max: 2000)",
"default": 500,
"maximum": 2000
}
},
"required": [
"path"
]
}
}
},
{
"type": "function",
"function": {
"name": "search_files",
"description": "Search file contents or find files by name. Use this instead of grep/rg/find/ls in terminal. Ripgrep-backed, faster than shell equivalents.\n\nContent search (target='content'): Regex search inside files. Output modes: full matches with line numbers, file paths only, or match counts.\n\nFile search (target='files'): Find files by glob pattern (e.g., '*.py', '*config*'). Also use this instead of ls — results sorted by modification time.",
"parameters": {
"type": "object",
"properties": {
"pattern": {
"type": "string",
"description": "Regex pattern for content search, or glob pattern (e.g., '*.py') for file search"
},
"target": {
"type": "string",
"enum": [
"content",
"files"
],
"description": "'content' searches inside file contents, 'files' searches for files by name",
"default": "content"
},
"path": {
"type": "string",
"description": "Directory or file to search in (default: current working directory)",
"default": "."
},
"file_glob": {
"type": "string",
"description": "Filter files by pattern in grep mode (e.g., '*.py' to only search Python files)"
},
"limit": {
"type": "integer",
"description": "Maximum number of results to return (default: 50)",
"default": 50
},
"offset": {
"type": "integer",
"description": "Skip first N results for pagination (default: 0)",
"default": 0
},
"output_mode": {
"type": "string",
"enum": [
"content",
"files_only",
"count"
],
"description": "Output format for grep mode: 'content' shows matching lines with line numbers, 'files_only' lists file paths, 'count' shows match counts per file",
"default": "content"
},
"context": {
"type": "integer",
"description": "Number of context lines before and after each match (grep mode only)",
"default": 0
}
},
"required": [
"pattern"
]
}
}
},
{
"type": "function",
"function": {
"name": "session_search",
"description": "Search your long-term memory of past conversations, or browse recent sessions. This is your recall -- every past session is searchable, and this tool summarizes what happened.\n\nTWO MODES:\n1. Recent sessions (no query): Call with no arguments to see what was worked on recently. Returns titles, previews, and timestamps. Zero LLM cost, instant. Start here when the user asks what were we working on or what did we do recently.\n2. Keyword search (with query): Search for specific topics across all past sessions. Returns LLM-generated summaries of matching sessions.\n\nUSE THIS PROACTIVELY when:\n- The user says 'we did this before', 'remember when', 'last time', 'as I mentioned'\n- The user asks about a topic you worked on before but don't have in current context\n- The user references a project, person, or concept that seems familiar but isn't in memory\n- You want to check if you've solved a similar problem before\n- The user asks 'what did we do about X?' or 'how did we fix Y?'\n\nDon't hesitate to search when it is actually cross-session -- it's fast and cheap. Better to search and confirm than to guess or ask the user to repeat themselves.\n\nSearch syntax: keywords joined with OR for broad recall (elevenlabs OR baseten OR funding), phrases for exact match (\"docker networking\"), boolean (python NOT java), prefix (deploy*). IMPORTANT: Use OR between keywords for best results — FTS5 defaults to AND which misses sessions that only mention some terms. If a broad OR query returns nothing, try individual keyword searches in parallel. Returns summaries of the top matching sessions.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Search query — keywords, phrases, or boolean expressions to find in past sessions. Omit this parameter entirely to browse recent sessions instead (returns titles, previews, timestamps with no LLM cost)."
},
"role_filter": {
"type": "string",
"description": "Optional: only search messages from specific roles (comma-separated). E.g. 'user,assistant' to skip tool outputs."
},
"limit": {
"type": "integer",
"description": "Max sessions to summarize (default: 3, max: 5).",
"default": 3
}
}
}
}
},
{
"type": "function",
"function": {
"name": "skill_manage",
"description": "Manage skills (create, update, delete). Skills are your procedural memory — reusable approaches for recurring task types. New skills go to ~/.hermes/skills/; existing skills can be modified wherever they live.\n\nActions: create (full SKILL.md + optional category), patch (old_string/new_string — preferred for fixes), edit (full SKILL.md rewrite — major overhauls only), delete, write_file, remove_file.\n\nOn delete, pass `absorbed_into=` when you're merging this skill's content into another one, or `absorbed_into=\"\"` when you're pruning it with no forwarding target. This lets the curator tell consolidation from pruning without guessing, so downstream consumers (cron jobs that reference the old skill name, etc.) get updated correctly. The target you name in `absorbed_into` must already exist — create/patch the umbrella first, then delete.\n\nCreate when: complex task succeeded (5+ calls), errors overcome, user-corrected approach worked, non-trivial workflow discovered, or user asks you to remember a procedure.\nUpdate when: instructions stale/wrong, OS-specific failures, missing steps or pitfalls found during use. If you used a skill and hit issues not covered by it, patch it immediately.\n\nAfter difficult/iterative tasks, offer to save as a skill. Skip for simple one-offs. Confirm with user before creating/deleting.\n\nGood skills: trigger conditions, numbered steps with exact commands, pitfalls section, verification steps. Use skill_view() to see format examples.\n\nPinned skills are protected from deletion only — skill_manage(action='delete') will refuse with a message pointing the user to `hermes curator unpin `. Patches and edits go through on pinned skills so you can still improve them as pitfalls come up; pin only guards against irrecoverable loss.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"create",
"patch",
"edit",
"delete",
"write_file",
"remove_file"
],
"description": "The action to perform."
},
"name": {
"type": "string",
"description": "Skill name (lowercase, hyphens/underscores, max 64 chars). Must match an existing skill for patch/edit/delete/write_file/remove_file."
},
"content": {
"type": "string",
"description": "Full SKILL.md content (YAML frontmatter + markdown body). Required for 'create' and 'edit'. For 'edit', read the skill first with skill_view() and provide the complete updated text."
},
"old_string": {
"type": "string",
"description": "Text to find in the file (required for 'patch'). Must be unique unless replace_all=true. Include enough surrounding context to ensure uniqueness."
},
"new_string": {
"type": "string",
"description": "Replacement text (required for 'patch'). Can be empty string to delete the matched text."
},
"replace_all": {
"type": "boolean",
"description": "For 'patch': replace all occurrences instead of requiring a unique match (default: false)."
},
"category": {
"type": "string",
"description": "Optional category/domain for organizing the skill (e.g., 'devops', 'data-science', 'mlops'). Creates a subdirectory grouping. Only used with 'create'."
},
"file_path": {
"type": "string",
"description": "Path to a supporting file within the skill directory. For 'write_file'/'remove_file': required, must be under references/, templates/, scripts/, or assets/. For 'patch': optional, defaults to SKILL.md if omitted."
},
"file_content": {
"type": "string",
"description": "Content for the file. Required for 'write_file'."
},
"absorbed_into": {
"type": "string",
"description": "For 'delete' only — declares intent so the curator can tell consolidation from pruning without guessing. Pass the umbrella skill name when this skill's content was merged into another (the target must already exist). Pass an empty string when the skill is truly stale and being pruned with no forwarding target. Omitting the arg on delete is supported for backward compatibility but downstream tooling (e.g. cron-job skill reference rewriting) will have to guess at intent."
}
},
"required": [
"action",
"name"
]
}
}
},
{
"type": "function",
"function": {
"name": "skill_view",
"description": "Skills allow for loading information about specific tasks and workflows, as well as scripts and templates. Load a skill's full content or access its linked files (references, templates, scripts). First call returns SKILL.md content plus a 'linked_files' dict showing available references/templates/scripts. To access those, call again with file_path parameter.",
"parameters": {
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "The skill name (use skills_list to see available skills). For plugin-provided skills, use the qualified form 'plugin:skill' (e.g. 'superpowers:writing-plans')."
},
"file_path": {
"type": "string",
"description": "OPTIONAL: Path to a linked file within the skill (e.g., 'references/api.md', 'templates/config.yaml', 'scripts/validate.py'). Omit to get the main SKILL.md content."
}
},
"required": [
"name"
]
}
}
},
{
"type": "function",
"function": {
"name": "skills_list",
"description": "List available skills (name + description). Use skill_view(name) to load full content.",
"parameters": {
"type": "object",
"properties": {
"category": {
"type": "string",
"description": "Optional category filter to narrow results"
}
}
}
}
},
{
"type": "function",
"function": {
"name": "terminal",
"description": "Execute shell commands on a Linux environment. Filesystem usually persists between calls.\n\nDo NOT use cat/head/tail to read files — use read_file instead.\nDo NOT use grep/rg/find to search — use search_files instead.\nDo NOT use ls to list directories — use search_files(target='files') instead.\nDo NOT use sed/awk to edit files — use patch instead.\nDo NOT use echo/cat heredoc to create files — use write_file instead.\nReserve terminal for: builds, installs, git, processes, scripts, network, package managers, and anything that needs a shell.\n\nForeground (default): Commands return INSTANTLY when done, even if the timeout is high. Set timeout=300 for long builds/scripts — you'll still get the result in seconds if it's fast. Prefer foreground for short commands.\nBackground: Set background=true to get a session_id. Two patterns:\n (1) Long-lived processes that never exit (servers, watchers).\n (2) Long-running tasks with notify_on_complete=true — you can keep working on other things and the system auto-notifies you when the task finishes. Great for test suites, builds, deployments, or anything that takes more than a minute.\nFor servers/watchers, do NOT use shell-level background wrappers (nohup/disown/setsid/trailing '&') in foreground mode. Use background=true so Hermes can track lifecycle and output.\nAfter starting a server, verify readiness with a health check or log signal, then run tests in a separate terminal() call. Avoid blind sleep loops.\nUse process(action=\"poll\") for progress checks, process(action=\"wait\") to block until done.\nWorking directory: Use 'workdir' for per-command cwd.\nPTY mode: Set pty=true for interactive CLI tools (Codex, Claude Code, Python REPL).\n\nDo NOT use vim/nano/interactive tools without pty=true — they hang without a pseudo-terminal. Pipe git output to cat if it might page.\n",
"parameters": {
"type": "object",
"properties": {
"command": {
"type": "string",
"description": "The command to execute on the VM"
},
"background": {
"type": "boolean",
"description": "Run the command in the background. Two patterns: (1) Long-lived processes that never exit (servers, watchers). (2) Long-running tasks paired with notify_on_complete=true — you can keep working and get notified when the task finishes. For short commands, prefer foreground with a generous timeout instead.",
"default": false
},
"timeout": {
"type": "integer",
"description": "Max seconds to wait (default: 180, foreground max: 600). Returns INSTANTLY when command finishes — set high for long tasks, you won't wait unnecessarily. Foreground timeout above 600s is rejected; use background=true for longer commands.",
"minimum": 1
},
"workdir": {
"type": "string",
"description": "Working directory for this command (absolute path). Defaults to the session working directory."
},
"pty": {
"type": "boolean",
"description": "Run in pseudo-terminal (PTY) mode for interactive CLI tools like Codex, Claude Code, or Python REPL. Only works with local and SSH backends. Default: false.",
"default": false
},
"notify_on_complete": {
"type": "boolean",
"description": "When true (and background=true), you'll be automatically notified exactly once when the process finishes. **This is the right choice for almost every long-running task** — tests, builds, deployments, multi-item batch jobs, anything that takes over a minute and has a defined end. Use this and keep working on other things; the system notifies you on exit. MUTUALLY EXCLUSIVE with watch_patterns — when both are set, watch_patterns is dropped.",
"default": false
},
"watch_patterns": {
"type": "array",
"items": {
"type": "string"
},
"description": "Strings to watch for in background process output. HARD RATE LIMIT: at most 1 notification per 15 seconds per process — matches arriving inside the cooldown are dropped. After 3 consecutive 15-second windows with dropped matches, watch_patterns is automatically disabled for that process and promoted to notify_on_complete behavior (one notification on exit, no more mid-process spam). USE ONLY for truly rare, one-shot mid-process signals on LONG-LIVED processes that will never exit on their own — e.g. ['Application startup complete'] on a server so you know when to hit its endpoint, or ['migration done'] on a daemon. DO NOT use for: (1) end-of-run markers like 'DONE'/'PASS' — use notify_on_complete instead; (2) error patterns like 'ERROR'/'Traceback' in loops or multi-item batch jobs — they fire on every iteration and you'll hit the strike limit fast; (3) anything you'd ever combine with notify_on_complete. When in doubt, choose notify_on_complete. MUTUALLY EXCLUSIVE with notify_on_complete — set one, not both."
}
},
"required": [
"command"
]
}
}
},
{
"type": "function",
"function": {
"name": "text_to_speech",
"description": "Convert text to speech audio. Returns a MEDIA: path that the platform delivers as native audio. Compatible providers render as a voice bubble on Telegram; otherwise audio is sent as a regular attachment. In CLI mode, saves to ~/voice-memos/. Voice and provider are user-configured (built-in providers like edge/openai or custom command providers under tts.providers.), not model-selected.",
"parameters": {
"type": "object",
"properties": {
"text": {
"type": "string",
"description": "The text to convert to speech. Provider-specific character caps apply and are enforced automatically (OpenAI 4096, xAI 15000, MiniMax 10000, ElevenLabs 5k-40k depending on model); over-long input is truncated."
},
"output_path": {
"type": "string",
"description": "Optional custom file path to save the audio. Defaults to ~/.hermes/audio_cache/.mp3"
}
},
"required": [
"text"
]
}
}
},
{
"type": "function",
"function": {
"name": "todo",
"description": "Manage your task list for the current session. Use for complex tasks with 3+ steps or when the user provides multiple tasks. Call with no parameters to read the current list.\n\nWriting:\n- Provide 'todos' array to create/update items\n- merge=false (default): replace the entire list with a fresh plan\n- merge=true: update existing items by id, add any new ones\n\nEach item: {id: string, content: string, status: pending|in_progress|completed|cancelled}\nList order is priority. Only ONE item in_progress at a time.\nMark items completed immediately when done. If something fails, cancel it and add a revised item.\n\nAlways returns the full current list.",
"parameters": {
"type": "object",
"properties": {
"todos": {
"type": "array",
"description": "Task items to write. Omit to read current list.",
"items": {
"type": "object",
"properties": {
"id": {
"type": "string",
"description": "Unique item identifier"
},
"content": {
"type": "string",
"description": "Task description"
},
"status": {
"type": "string",
"enum": [
"pending",
"in_progress",
"completed",
"cancelled"
],
"description": "Current status"
}
},
"required": [
"id",
"content",
"status"
]
}
},
"merge": {
"type": "boolean",
"description": "true: update existing items by id, add new ones. false (default): replace the entire list.",
"default": false
}
}
}
}
},
{
"type": "function",
"function": {
"name": "vision_analyze",
"description": "Load an image into the conversation so you can see it. Accepts a URL, local file path, or data URL. When your active model has native vision, the image is attached to your context directly and you read the pixels yourself on the next turn — call this any time the user references an image (filepath in their message, URL in tool output, screenshot from the browser, etc.). For non-vision models, falls back to an auxiliary vision model that returns a text description.",
"parameters": {
"type": "object",
"properties": {
"image_url": {
"type": "string",
"description": "Image URL (http/https), local file path, or data: URL to load."
},
"question": {
"type": "string",
"description": "Your specific question or request about the image. Optional context the model uses on the next turn after seeing the image."
}
},
"required": [
"image_url",
"question"
]
}
}
},
{
"type": "function",
"function": {
"name": "web_extract",
"description": "Extract content from web page URLs. Returns page content in markdown format. Also works with PDF URLs (arxiv papers, documents, etc.) — pass the PDF link directly and it converts to markdown text. Pages under 5000 chars return full markdown; larger pages are LLM-summarized and capped at ~5000 chars per page. Pages over 2M chars are refused. If a URL fails or times out, use the browser tool to access it instead.",
"parameters": {
"type": "object",
"properties": {
"urls": {
"type": "array",
"items": {
"type": "string"
},
"description": "List of URLs to extract content from (max 5 URLs per call)",
"maxItems": 5
}
},
"required": [
"urls"
]
}
}
},
{
"type": "function",
"function": {
"name": "web_search",
"description": "Search the web for information. Returns up to 5 results by default with titles, URLs, and descriptions. The query is passed through to the configured backend, so operators such as site:domain, filetype:pdf, intitle:word, -term, and \"exact phrase\" may work when the backend supports them.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The search query to look up on the web. You may include backend-supported operators such as site:example.com, filetype:pdf, intitle:word, -term, or \"exact phrase\"."
},
"limit": {
"type": "integer",
"description": "Maximum number of results to return. Defaults to 5.",
"minimum": 1,
"maximum": 100,
"default": 5
}
},
"required": [
"query"
]
}
}
},
{
"type": "function",
"function": {
"name": "write_file",
"description": "Write content to a file, completely replacing existing content. Use this instead of echo/cat heredoc in terminal. Creates parent directories automatically. OVERWRITES the entire file — use 'patch' for targeted edits. Auto-runs syntax checks on .py/.json/.yaml/.toml and other linted languages; only NEW errors introduced by this write are surfaced (pre-existing errors are filtered out).",
"parameters": {
"type": "object",
"properties": {
"path": {
"type": "string",
"description": "Path to the file to write (will be created if it doesn't exist, overwritten if it does)"
},
"content": {
"type": "string",
"description": "Complete content to write to the file"
}
},
"required": [
"path",
"content"
]
}
}
},
{
"type": "function",
"function": {
"name": "honcho_profile",
"description": "Retrieve or update a peer card from Honcho — a curated list of key facts about that peer (name, role, preferences, communication style, patterns). Pass `card` to update; omit `card` to read. If the card is empty, the result includes a `hint` field explaining why (observation disabled, fresh peer, dialectic layer still warming up, etc.) — this is NOT an error. Peer cards accumulate over time from observed conversation.",
"parameters": {
"type": "object",
"properties": {
"peer": {
"type": "string",
"description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace."
},
"card": {
"type": "array",
"items": {
"type": "string"
},
"description": "New peer card as a list of fact strings. Omit to read the current card."
}
},
"required": []
}
}
},
{
"type": "function",
"function": {
"name": "honcho_search",
"description": "Semantic search over Honcho's stored context about a peer. Returns raw excerpts ranked by relevance — no LLM synthesis. Cheaper and faster than honcho_reasoning. Good when you want to find specific past facts and reason over them yourself.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "What to search for in Honcho's memory."
},
"max_tokens": {
"type": "integer",
"description": "Token budget for returned context (default 800, max 2000)."
},
"peer": {
"type": "string",
"description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace."
}
},
"required": [
"query"
]
}
}
},
{
"type": "function",
"function": {
"name": "honcho_reasoning",
"description": "Ask Honcho a natural language question and get a synthesized answer. Uses Honcho's LLM (dialectic reasoning) — higher cost than honcho_profile or honcho_search. Can query about any peer via alias or explicit peer ID. Pass reasoning_level to control depth: minimal (fast/cheap), low (default), medium, high, max (deep/expensive). Omit for configured default.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "A natural language question."
},
"reasoning_level": {
"type": "string",
"description": "Override the default reasoning depth. Omit to use the configured default (typically low). Guide:\n- minimal: quick factual lookups (name, role, simple preference)\n- low: straightforward questions with clear answers\n- medium: multi-aspect questions requiring synthesis across observations\n- high: complex behavioral patterns, contradictions, deep analysis\n- max: thorough audit-level analysis, leave no stone unturned",
"enum": [
"minimal",
"low",
"medium",
"high",
"max"
]
},
"peer": {
"type": "string",
"description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace."
}
},
"required": [
"query"
]
}
}
},
{
"type": "function",
"function": {
"name": "honcho_context",
"description": "Retrieve full session context from Honcho — summary, peer representation, peer card, and recent messages. No LLM synthesis. Cheaper than honcho_reasoning. Use this to see what Honcho knows about the current conversation and the specified peer.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Optional focus query to filter context. Omit for full session context snapshot."
},
"peer": {
"type": "string",
"description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace."
}
},
"required": []
}
}
},
{
"type": "function",
"function": {
"name": "honcho_conclude",
"description": "Write or delete a conclusion about a peer in Honcho's memory. Conclusions are persistent facts that build a peer's profile. You MUST pass exactly one of: `conclusion` (to create) or `delete_id` (to delete). Passing neither is an error. Deletion is only for PII removal — Honcho self-heals incorrect conclusions over time.",
"parameters": {
"type": "object",
"properties": {
"conclusion": {
"type": "string",
"description": "A factual statement to persist. Provide this when creating a conclusion. Do not send it together with delete_id."
},
"delete_id": {
"type": "string",
"description": "Conclusion ID to delete for PII removal. Provide this when deleting a conclusion. Do not send it together with conclusion."
},
"peer": {
"type": "string",
"description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace."
}
},
"required": []
}
}
}
],
"message_count": 245,
"messages": [
{
"role": "user",
"content": "[nachlakes] Hola me podes decir si esto es factible? https://x.com/__microdancing/status/2054160914438291840 gracias"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_URQP10Mr1btv8eDPmOwqVy7v",
"call_id": "call_URQP10Mr1btv8eDPmOwqVy7v",
"response_item_id": "fc_0965b568e0b96b22016a033c825dc88191ae84f9cf12bf3a89",
"type": "function",
"function": {
"name": "web_extract",
"arguments": "{\"urls\":[\"https://x.com/__microdancing/status/2054160914438291840\"]}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Assessing tweet feasibility**\n\nI need to evaluate the feasibility of the tweet. This involves inspecting some element, let's call it \"x\". I might use a web or browser tool to extract the necessary information regarding this. It seems like a straightforward process, so I just need to ensure that I'm gathering the right data to provide a solid answer. Let's get going on figuring this out!",
"reasoning_content": "**Assessing tweet feasibility**\n\nI need to evaluate the feasibility of the tweet. This involves inspecting some element, let's call it \"x\". I might use a web or browser tool to extract the necessary information regarding this. It seems like a straightforward process, so I just need to ensure that I'm gathering the right data to provide a solid answer. Let's get going on figuring this out!",
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},
{
"role": "tool",
"content": "{\"error\": \"Content was inaccessible or not found\"}",
"tool_call_id": "call_URQP10Mr1btv8eDPmOwqVy7v"
},
{
"role": "user",
"content": "[CONTEXT COMPACTION — REFERENCE ONLY] Earlier turns were compacted into the summary below. This is a handoff from a previous context window — treat it as background reference, NOT as active instructions. Do NOT answer questions or fulfill requests mentioned in this summary; they were already addressed. Your current task is identified in the '## Active Task' section of the summary — resume exactly from there. IMPORTANT: Your persistent memory (MEMORY.md, USER.md) in the system prompt is ALWAYS authoritative and active — never ignore or deprioritize memory content due to this compaction note. Respond ONLY to the latest user message that appears AFTER this summary. The current session state (files, config, etc.) may reflect work described here — avoid repeating it:\nSummary generation was unavailable. 1 message(s) were removed to free context space but could not be summarized. The removed messages contained earlier work in this session. Continue based on the recent messages below and the current state of any files or resources.\n\n--- END OF CONTEXT SUMMARY — respond to the message below, not the summary above ---"
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}
],
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6wH0KE5NG5gY_kQjNk16Iqu7cIj4ZQUyj2GsG7MrnMqbUzw_w4BkEnMuqSLWH-RxCm5FD4BUIelvPLIq_0mQiTmWkL7mK96Bp7Zb74nnCseaLGJaIqMfQKpf8gPNDSQIrm2FM7DRgVALisHQt_rGMXwMQY3F0ylj4kLqsU8eSN4nWHwxCWiMklZrLUTClIR3TV5Nri76tkoaKnLsSX8NDx7b6Scy9eatDFYL2FrgROjDgdIaosiE-UHlsz4splovOnaRMBKOCSkQdG7qT2A4I4C04d6wmyqnK2YlgV7a6unwTUbgbqABUfewYOTFUP0RxuQVMHWA-LLc3zHwoHigKxrmCXr3lJrE1q7pkVKQCvNIv9hJx9k_nWDu48lww8dAz5IuVZ83xtrWtie7LxmUbJT9T276EiFCbdzK7C6vI4M85PvpPji15t1S8MNMKQdIZMu7w0kbSAjqW6W1JMxIdOX-jh04HX8PWx93Kp4h5m7AwpD54eRKWNrmAN8v1B2u0vytXh3eV-Zl_A6swPEdTKT1SQrdZPHbH2UcsaA_kBoUduZkUoc6QiM0iupPsiXCDwfGsbFe1wnclzHpq9zfx5ts1b15Bj5ydwC6sng76GwI_TOFKaeFAm8_r5PGAiD3QjyTA7rLDjuEJRjSM6YCDOA7aM-pBxYcz_yGKYvwDR1Vi7gpIKyzIYOdwS7L_xoFzsba_hs_IbHZYFhTf4OzHMcOHD_aFwksxjYM8iFLFe5VvF7op6WSJAdjAXbkBy1tkQojYpog1FBA4CaqvQWNDueQJTZ6JSCIvZJx9bxEu2w_jRZeqGzluKLhhAG4eNqNfRDRMytE5qioCO6BqLQt6QbfkCk-IPwwKyvjgfF9oQNBwckY16s1TjASaxJanonY3ZBjZUAJid3nf3D7D3pGfpG0z1eJVz0-eCIdGsrQFqFCoHWJbkK2l52PTGW08kjh4ssKVzDOa0IjoPJfJsR_usmcwNYEFjzG8HsclK6rAJuStPTWpsGswRbSHx5XlUg_fH2Kl6XfFKkl1T6ycmjzisFuIBHI-iRV5PmxL-Gv1GcQ7N6E_FDu3v9RwvhBETOd-zFu2q0bvxMEmaHKFDuFAzSeeAhTKYUIVnEgKhMAb0xU82qNv0Sw5l533UdGGNP9AiqQQx2kKw-hfM-dDwWyJTMe1RDNctGjB_C8jTZjZqA3mfVoG_z8AGElDjgcr7JEc4nj2upb8ZwaecvRURdPIXypJjQvnlEwTR9Vt9-n75xNicYygXYa3NKTptnTeDMyyhhK4gi-ITyVKNhrmJarfAIOWVQtPLmXahr6_ryWRtAbDVu2eWR9sgzgAypongqTxH6u9flyF49qjWa7OP8u3wBVZ-hemnDhsNAxuYwmKERwPBCVQKO5vp8Ahmv0gytpSQwoR5chLXE1YtfYTupyknj0qiYKvfj6Y6HD6xwWc5dC1dytVkMJ6D1b9Yj8rQcQnVKaWk3dtETnSmrfj-Rv_SQ7meJHiidnXhzHbdVSdKViNp7QQzgNv4ClC95ePX3EC-CTeA4j6TSUZeHR78ArdvpnikctvlxTpYVkvMqzA0qKBNhp7xw3qtjmamQbeC7wpQTLCgTD8UViba_2_zQV7rePfJqWTGiylqk9GUHRy06iafD1eQaML3Yq0qMWv8FyRiEU9AhCHnlfeTmccU6QB4wVy4cOB3hM4i_Oh7CdJVuXkqbEnLowtjx5bSpMAlZXqLwaiO4VrJsnPbIvWVKedVprXTcmVwqph0JqF9IdFXQK8wSca1xyU_Ngn-7yldUbZCkWzBipz7n4SMFxzg2D0E7e6K0YkLvBLZqICgYp1OQdPXw395IB4wHOnodTsrk-FuZsFI7rgawyVQCWjacnAApOtTJOZEufUnQTE56HF93N9gQcUDjGcYHm7BH6qDFysmVd62d_gJ9iE6xqZHSVeFok5nPcMBuoTVKaPMah3YvQZADgkMEsAfC0CGI-SuCDdZgU-jH0Mh9KYSmp9lwwxC89AEkuRhymWEnGeXokmg1FRZE_TCa33uZrPCmYQYOmMDdm4Z10vL3_JOy9UR5T-wJSNBmWFcmJ6Dyc_Chuf7YUHCVeJmSg4CkzTZc_hfHX2AfgbuDC_CJU9L8iDJYxGashmEml4pYvl56NXWrVa5kBc1Kp7ANgOux9eevGOyJnM9gCiEYWWJUOGjTvkVIAVomPaAPHW3SJnqyIXfwKdQWcRHjQIrwJVu-9lmBieuh0qMwnRwaO5F563f3pgyK5LdmRhlyYgawB3xGfUncYnKrryxn0qZLpM3nIHYAR1KQyB6fHFmhytRSsAQrglzPb_pT4MyVYUBOZ0V5ccxLFnG7tTQtQOY2YT_lXPBHlIkT0uBud4IMVFk10TOd5iAU47WMKLLlqHHr-czqYnHsR0hA8WiThgvPXM69bcNH7mQDHl9sxYNgu-IhKnybNQc3Z_2Scke6NoJjHY9x10cbCJ9xFvIyaSkB6zeUGJ0ikxeZTRc7I_WyiUyK8tl35rq45JUYdDOVkcwU8Ezxf1x9UTknWxI4iaMXhQcTsSPSksb5YyssUbHCsZi8XQp4_UQquJWwScGxL7uhsC3eFkIjJyImJl8gAh-Me2LZacKIjbsgEJ6UufIcFq9072xBVk84_dRRLqpLDR-Lw3WGQNxEJqZpXTYoNbqsiFSnVzkq0ADVshhNI0tZisPdKBX-tobkRDYw2O54efy-yAGWEvxHNMiQETisCkiSlsjsRObDfpgG90fQp81BXEqOLXGGPUVBUl6gu7JarYFaNmHzW4xuT3VmcsVUwe0_KclAGpP3vlcethMkzijNPNEnpZO__tSiZ6ym43YZekP9r6ABzj9_QVIXj-lwo=",
"id": "rs_0db05e419df56d4e016a0344736ea88191b062152d8f9f16f8",
"summary": []
}
]
},
{
"role": "tool",
"content": "[todo] updated task list",
"tool_call_id": "call_amNm7asN5e7hneupeHmH2WSj"
},
{
"role": "assistant",
"content": "## Veredicto\n\nSí: **se puede hacer completo de punta a punta**.\n\nPero hay que definir bien el producto:\n\n1. **Bot de ejecución presupuestaria**: factible ya, con Presupuesto Abierto.\n2. **Bot de “transferencias bancarias individuales”**: no con esta fuente. El dato público no baja a CUIT/CBU/orden bancaria.\n3. **Bot de “todo lo que Nación gira a provincias”**: requiere combinar dos mundos:\n - **Transferencias presupuestarias / no automáticas** → Presupuesto Abierto, `inciso_id = 5`.\n - **Coparticipación / transferencias automáticas** → DNAP / Recursos de Origen Nacional.\n\nMi recomendación: arrancar con **transferencias presupuestarias**, especialmente:\n\n- universidades nacionales;\n- provincias/municipios;\n- ATN;\n- fondos fiduciarios / entes del SPN;\n- grandes transferencias al sector privado, si se quiere ampliar.\n\n---\n\n# Factos verificados\n\n## 1. El tweet tiene tracción real\n\nTweet original:\n\n> “hay que hacer un bot que twittee cada vez que hay una transferencia del gobierno nacional a las provincias/universidades/etc. monto, fecha, destino, ítem presupuestario…”\n\nAl momento de consultar vía `api.fxtwitter.com`:\n\n- 4.937 vistas\n- 164 likes\n- 15 retweets\n- 9 replies\n- 4 bookmarks\n\nNo es masivo todavía, pero es una señal bastante clara para nicho político/datos/journalism.\n\n---\n\n## 2. La fuente existe y es oficial\n\nFuente principal:\n\n**Presupuesto Abierto** \nhttps://www.presupuestoabierto.gob.ar/sici/datos-abiertos\n\nEl sitio dice explícitamente:\n\n> “Estos datos son tuyos. Podés descargarlos, analizarlos, cruzarlos con otros datos, crear aplicaciones o armar visualizaciones…”\n\nLicencia: **Creative Commons 4.0 / CC-BY-4.0**.\n\nFuente técnica directa 2026:\n\n```text\nhttps://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/credito-diario-2026.zip\nhttps://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/credito-mensual-2026.zip\nhttps://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/credito-anual-2026.zip\nhttps://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/resumen-presupuesto-gastos-ejercicio-vigente-2026.zip\n```\n\nEl API oficial también existe:\n\nhttps://presupuesto-abierto.argentina.apidocs.ar/\n\nPero requiere token. Probé `/api/v1/credito` sin token y devuelve `401`:\n\n> “Debe indicar el header Authorization en la petición”\n\nPara MVP, **no hace falta API**. Los ZIP/CSV directos alcanzan.\n\n---\n\n## 3. Qué hay adentro del CSV diario 2026\n\nArchivo probado:\n\n`credito-diario-2026.zip`\n\nDatos observados al 12/05/2026:\n\n- Última actualización interna: **10 Mayo 2026**\n- Fecha máxima de datos: **2026-05-10**\n- Filas totales: **363.214**\n- Filas con `inciso_id = 5` / transferencias: **28.467**\n- Filas de transferencias con `credito_pagado > 0`: **10.587**\n- Período con datos: **2026-01-20 a 2026-05-10**\n\nCampos clave:\n\n```text\nimpacto_presupuestario_fecha\njurisdiccion_desc\nentidad_desc\nprograma_desc\nactividad_desc\ninciso_desc\nprincipal_desc\nparcial_desc\nsubparcial_desc\nubicacion_geografica_desc\nfuente_financiamiento_desc\ncredito_presupuestado\ncredito_vigente\ncredito_comprometido\ncredito_devengado\ncredito_pagado\nultima_actualizacion_fecha\n```\n\nImportantísimo: **los montos están en millones de pesos**.\n\nEl diccionario oficial dice:\n\n> `credito_pagado`: “Acumulado del Crédito Pagado de la fecha. Expresado en millones de pesos.”\n\nO sea, si el CSV dice `4000`, eso es **$4.000 millones**, no $4.000.\n\n---\n\n# Prueba real sobre 2026\n\n## Total transferencias 2026 hasta el corte\n\nFiltrando `inciso_id = 5`, al corte 10/05/2026:\n\n| Categoría | Pagado 2026 | Crédito vigente | Ejecutado |\n|---|---:|---:|---:|\n| Sector privado, gastos corrientes | $29,228 billones | $92,301 billones | 31,7% |\n| Otras entidades del Sector Público Nacional | $2,370 billones | $10,850 billones | 21,8% |\n| Universidades nacionales | $1,537 billones | $5,238 billones | 29,3% |\n| Provincias/municipios, gastos corrientes | $412.437 millones | $3,477 billones | 11,9% |\n| Provincias/municipios, gastos de capital | $21.635 millones | $115.979 millones | 18,7% |\n| Exterior | $36.495 millones | $134.938 millones | 27,0% |\n\nEsto confirma que el bot puede publicar:\n\n```text\nTransferido hasta ahora en 2026: $X\nPresupuesto vigente anual: $Y\nEjecución: Z%\n```\n\n---\n\n# Ejemplo de tweet bueno\n\nCaso real detectado:\n\n**05/05/2026 — Universidad de Buenos Aires**\n\nEse día aparecen tres pagos a UBA:\n\n- $28,4 mil millones — salario docente y autoridades superiores\n- $32,5 mil millones — salario no docente\n- $1,7 mil millones — hospitales universitarios\n\nTotal del día:\n\n> **$62,6 mil millones**\n\nContexto anual UBA:\n\n- Pagado 2026: **$262,4 mil millones**\n- Crédito vigente: **$799,5 mil millones**\n- Ejecución: **32,8%**\n\nTweet posible:\n\n> 🏛️ Transferencia registrada — 05/05/2026 \n> Ministerio de Capital Humano → Universidad de Buenos Aires \n> Programa: Desarrollo de la Educación Superior \n> \n> Pagado del día: **$62,6 mil millones** \n> 2026 acumulado: **$262,4 mil millones / $799,5 mil millones** \n> Ejecución: **32,8%** \n> \n> Fuente: Presupuesto Abierto, corte 10/05/2026.\n\nEso es muy útil y entendible.\n\n---\n\n# Qué quiere ver la gente\n\nPor señales del tweet + cómo se cubre el tema en medios/OPC/ASAP, la gente no quiere “un CSV en Twitter”. Quiere respuestas inmediatas a preguntas concretas:\n\n## 1. “¿Quién recibió plata?”\n\n- provincia;\n- universidad;\n- municipio si está disponible;\n- fondo fiduciario;\n- organismo público;\n- programa.\n\n## 2. “¿Cuánto recibió hoy?”\n\nEjemplo:\n\n> UBA recibió $62,6 mil millones el 05/05/2026.\n\n## 3. “¿Cuánto lleva recibido en el año?”\n\nEjemplo:\n\n> UBA lleva $262,4 mil millones pagados en 2026.\n\n## 4. “¿Qué porcentaje del presupuesto anual ya se ejecutó?”\n\nEsto es clave. La idea que propusiste es correcta.\n\n```text\npagado_2026 / credito_vigente\n```\n\n## 5. “¿Para qué fue?”\n\nNo alcanza con “transferencia”. Hay que mostrar:\n\n- programa;\n- actividad;\n- partida;\n- objeto del gasto.\n\nEjemplo:\n\n> Asistencia financiera para salario docente / no docente / hospitales universitarios.\n\n## 6. “¿Es mucho o poco contra otras provincias/universidades?”\n\nLa gente va a pedir rankings:\n\n- universidades que más recibieron;\n- provincias que más recibieron;\n- provincias con más ejecución porcentual;\n- transferencias con crédito vigente cero;\n- top transferencias del día;\n- variación contra 2025.\n\n## 7. “¿Dónde está la fuente?”\n\nDespués del caso de bots de precios falsos tipo JumboBot, la credibilidad es parte del producto. Cada tweet debería tener:\n\n- fuente;\n- fecha de corte;\n- link a ficha/web;\n- idealmente ID/hash de la fila o link a CSV procesado.\n\n---\n\n# La parte delicada\n\n## 1. “Transferido” no significa necesariamente “transferencia bancaria individual”\n\n`credito_pagado` es ejecución presupuestaria pagada. Es lo más cercano y útil, pero no prueba una transferencia bancaria específica con número de operación.\n\nFrase recomendada:\n\n> “Pago presupuestario registrado”\n\nNo:\n\n> “El Gobierno le transfirió por banco a X…”\n\n---\n\n## 2. Los montos están en millones\n\nError fácil: leer `18,68` como $18,68.\n\nCorrecto:\n\n```text\n18,68 millones de pesos = $18.680.000\n4000 millones de pesos = $4.000.000.000\n```\n\nEl bot debe convertir siempre a pesos legibles.\n\n---\n\n## 3. Hay filas con `credito_vigente = 0`\n\nEjemplo real:\n\n- 22/01/2026\n- Ministerio del Interior\n- Programa: Relaciones con las Provincias y Desarrollo Regional\n- Actividad: ATN\n- Destino geográfico: Provincia del Chubut\n- Pagado del día: **$4.000 millones**\n- Pagado anual de esa clave: **$6.500 millones**\n- Crédito vigente anual: **0**\n\nEn esos casos no podés decir “ejecutó X% del presupuesto” porque el denominador es cero.\n\nEtiqueta correcta:\n\n> “Sin crédito vigente informado para esta clave presupuestaria.”\n\nO:\n\n> “Pago registrado con crédito vigente 0: revisar modificación/regularización presupuestaria.”\n\nEsto incluso puede ser una feature: detectar casos raros.\n\n---\n\n## 4. La granularidad puede duplicar tweets\n\nUBA el mismo día tuvo 3 filas: docente, no docente, hospitales.\n\nSi twitteás cada fila, spameás. Si agrupás todo, perdés detalle.\n\nSolución:\n\n- Agrupar por destinatario + fecha.\n- Mostrar total.\n- Incluir desglose top 3 por actividad.\n- Linkear al detalle completo.\n\n---\n\n## 5. Provincias no siempre son “beneficiario jurídico”\n\nPara universidades, `subparcial_desc` trae nombres claros:\n\n- Universidad de Buenos Aires\n- Universidad Tecnológica Nacional\n- Universidad Nacional de La Plata\n\nPara provincias, muchas veces el dataset dice:\n\n- `ubicacion_geografica_desc = Provincia del Chubut`\n- `subparcial_desc = Administración Central Provincial`\n\nEso indica destino geográfico/institucional, no necesariamente receptor final con CUIT.\n\n---\n\n## 6. Presupuesto Abierto no cubre todo Nación → provincias\n\nEl Presupuesto Nacional incluye transferencias presupuestarias. Pero si querés “todo lo que Nación manda a provincias”, también necesitás:\n\n**Recursos de Origen Nacional / coparticipación** \nhttps://www.argentina.gob.ar/economia/sechacienda/asuntosprovinciales/ron\n\nAhí hay montos diarios 2026 en XLS. Incluye:\n\n- Coparticipación Federal;\n- otros regímenes distribuidos por Banco Nación;\n- compensaciones / leyes especiales.\n\nProducto ideal:\n\n- Bot A: **transferencias presupuestarias**\n- Bot B: **coparticipación / automáticas**\n- Dashboard que combine ambos.\n\n---\n\n## 7. Hay revisiones retroactivas\n\nLos CSV se actualizan. No hay que asumir que lo visto ayer queda fijo.\n\nHay que guardar snapshots con:\n\n- hash del ZIP;\n- fecha de descarga;\n- `ultima_actualizacion_fecha`;\n- filas procesadas;\n- diferencias contra snapshot anterior.\n\n---\n\n# MVP recomendado\n\n## Producto público\n\nNombre posible:\n\n> **Transferencias Abiertas AR**\n\nFormatos:\n\n1. **Cuenta de X**\n - alertas grandes;\n - resumen diario;\n - rankings semanales.\n\n2. **Web**\n - buscador;\n - filtros por provincia/universidad/programa;\n - detalle de cada fila;\n - descarga CSV;\n - explicación metodológica.\n\n3. **RSS / Telegram / Discord**\n - más barato y menos dependiente de X.\n\n---\n\n# Arquitectura end-to-end\n\n## Ingesta\n\nCron cada 6 o 12 horas:\n\n1. Descargar ZIPs:\n - `credito-diario-{año}.zip`\n - `credito-anual-{año}.zip`\n - opcional: `credito-mensual-{año}.zip`\n2. Calcular hash.\n3. Si cambió:\n - parsear CSV;\n - normalizar decimales argentinos;\n - convertir montos de millones a pesos;\n - guardar raw rows;\n - calcular eventos nuevos.\n\n## Base de datos\n\nTablas mínimas:\n\n```sql\nsource_snapshots\nraw_credito_diario\nraw_credito_anual\ntransfer_events\nevent_context\npost_queue\nposted_messages\n```\n\nClave de deduplicación:\n\n```text\naño\nfecha\njurisdiccion_id\nservicio_id\nprograma_id\nactividad_id\ninciso_id\nprincipal_id\nparcial_id\nsubparcial_id\nfuente_financiamiento_id\nubicacion_geografica_id\nunidad_ejecutora_id\ncredito_pagado\n```\n\nPara tweets, además una clave agrupada:\n\n```text\nfecha\ntipo_transferencia\ndestinatario_display\nprograma_id\nprincipal_id\n```\n\n---\n\n# Métricas del bot\n\nPara cada evento:\n\n```text\nmonto_evento = suma credito_pagado del día/grupo\npagado_2026 = suma credito_pagado anual del mismo grupo\ndevengado_2026 = suma credito_devengado anual del mismo grupo\npresupuesto_vigente = suma credito_vigente anual del mismo grupo\nejecucion_pct = pagado_2026 / presupuesto_vigente\n```\n\nSi `presupuesto_vigente = 0`:\n\n```text\nejecucion_pct = null\nflag = \"sin crédito vigente\"\n```\n\n---\n\n# Cadencia de publicación\n\nNo publicaría todo. Hay mucho volumen.\n\nDatos 2026 observados:\n\n- 10.587 eventos pagados de transferencias en 103 días.\n- Eso da ~103 eventos/día si publicás todo `inciso_id = 5`.\n\nMVP sano:\n\n## Tweets automáticos\n\n- Universidades: sí.\n- Provincias/municipios: sí.\n- ATN: sí.\n- Fondos fiduciarios grandes: sí.\n- Sector privado: solo si supera umbral.\n\nUmbral inicial:\n\n```text\nPublicar eventos > $500 millones\n```\n\n## Resumen diario\n\n> Hoy se registraron X pagos presupuestarios de transferencias por $Y. \n> Top 5 destinatarios. \n> Universidades: $A. Provincias/municipios: $B. Otros SPN: $C.\n\n## Ranking semanal\n\n- Top universidades.\n- Top provincias.\n- Mayores ejecuciones porcentuales.\n- Casos con crédito vigente 0.\n- Mayores aumentos contra semana anterior.\n\n---\n\n# Costos y bloqueos\n\n## Datos\n\nCosto: **$0**. \nFuentes públicas.\n\n## Hosting\n\nCon tu stack actual:\n\n- Oracle cron / worker: $0 marginal.\n- Supabase: probablemente free/low.\n- Vercel dashboard: $0 marginal.\n\n## X API\n\nEste es el único bloqueo externo.\n\nLa documentación actual de X está medio inconsistente entre páginas, pero los factos relevantes son:\n\n- necesitás cuenta developer;\n- para postear programáticamente hace falta acceso API;\n- X ahora mezcla free/write-only, planes legacy y pay-per-use;\n- el costo exacto hay que confirmarlo dentro del Developer Console;\n- si el bot publica poco, podría entrar en cuota free/write-only si la cuenta la tiene habilitada;\n- si querés alto volumen, casi seguro hay costo.\n\nMitigación:\n\n- Publicar también en web/RSS/Telegram.\n- X solo como canal de difusión resumido.\n- Nada de depender de X para el producto principal.\n\n---\n\n# Qué construiría primero\n\n## Fase 1 — 1/2 días\n\nScript probado:\n\n- descarga CSV;\n- filtra `inciso_id = 5`;\n- detecta universidades/provincias;\n- calcula acumulado y porcentaje;\n- genera posts en modo dry-run.\n\nOutput: JSON + preview de tweets.\n\n## Fase 2 — 2/4 días\n\nMVP productivo:\n\n- DB;\n- snapshots;\n- dedupe;\n- cola de posts;\n- dashboard mínimo;\n- publicación manual/aprobada.\n\n## Fase 3 — 1 semana\n\nProducto serio:\n\n- publicación automática;\n- rankings;\n- explicación metodológica;\n- endpoint público;\n- alertas;\n- comparación interanual real con IPC;\n- coparticipación/RON como módulo separado.\n\n---\n\n# Conclusión ejecutiva\n\n**Sí, vale la pena.**\n\nHay fuente oficial, datos abiertos, granularidad suficiente y demanda clara. El diferencial no es “hacer un bot que lea un CSV”; es hacerlo **creíble, no spammer y metodológicamente honesto**.\n\nLa frase exacta del producto debería ser:\n\n> Bot de alertas de pagos presupuestarios registrados en transferencias de la Administración Pública Nacional.\n\nNo prometería:\n\n> “cada transferencia bancaria del Gobierno”.\n\nLa versión buena mostraría siempre:\n\n```text\nfecha\nmonto del evento\ndestinatario legible\nprograma / actividad / partida\npagado acumulado 2026\npresupuesto vigente\n% ejecutado\nfuente y corte de datos\n```\n\nMi recomendación: **hacerlo**, pero arrancar acotado a **universidades + provincias/municipios + ATN**, con dashboard y tweets seleccionados por umbral. Ahí hay producto real y no se convierte en una máquina de ruido."
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"tool_call_id": "call_TUinY4cg8VErVOdN28zMbts9"
},
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"content": "Buenísimo. Ojo igual: **lo pegaste en un thread de Discord**, así que yo lo trataría como **token expuesto**. No lo voy a repetir ni guardarlo en memoria.\n\nCon ese token se destraba la API oficial, pero para hacerlo bien yo haría esto:\n\n1. **Rotarlo después** si no era intencionalmente público.\n2. Guardarlo como secret/env var, no hardcodeado:\n ```bash\n PRESUPUESTO_ABIERTO_TOKEN=...\n ```\n3. Usar la API para queries puntuales y validación.\n4. Mantener los ZIP/CSV como fuente principal para el bot productivo, porque son más baratos, cacheables y reproducibles.\n\nImpacto en la factibilidad: **mejora bastante**, pero no cambia el caveat central.\n\nLa API probablemente ayuda para:\n\n- consultar crédito filtrado por jurisdicción/programa/partida;\n- armar links o queries reproducibles;\n- validar una fila específica;\n- evitar descargar todo para casos interactivos;\n- dashboard con filtros dinámicos.\n\nPero el bot automático diario igual conviene hacerlo con:\n\n```text\ncredito-diario-{año}.zip\ncredito-anual-{año}.zip\n```\n\nporque ahí podés snapshotear, hashear, comparar diferencias y no depender de límites/API auth.\n\nLa arquitectura quedaría así:\n\n```text\nCSV/ZIP oficial = ingesta batch, fuente de verdad operativa\nAPI con token = consultas interactivas, validación, dashboard, debugging\nDB propia = histórico + dedupe + tweets publicados\n```\n\nY sí: con token puedo después probar el endpoint real y ajustar el diseño a la respuesta exacta de la API, pero **no voy a meter ese token literal en comandos/logs acá**. Para producción lo ideal es configurarlo como secret del proyecto.",
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"type": "message",
"role": "assistant",
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"content": [
{
"type": "output_text",
"text": "Buenísimo. Ojo igual: **lo pegaste en un thread de Discord**, así que yo lo trataría como **token expuesto**. No lo voy a repetir ni guardarlo en memoria.\n\nCon ese token se destraba la API oficial, pero para hacerlo bien yo haría esto:\n\n1. **Rotarlo después** si no era intencionalmente público.\n2. Guardarlo como secret/env var, no hardcodeado:\n ```bash\n PRESUPUESTO_ABIERTO_TOKEN=...\n ```\n3. Usar la API para queries puntuales y validación.\n4. Mantener los ZIP/CSV como fuente principal para el bot productivo, porque son más baratos, cacheables y reproducibles.\n\nImpacto en la factibilidad: **mejora bastante**, pero no cambia el caveat central.\n\nLa API probablemente ayuda para:\n\n- consultar crédito filtrado por jurisdicción/programa/partida;\n- armar links o queries reproducibles;\n- validar una fila específica;\n- evitar descargar todo para casos interactivos;\n- dashboard con filtros dinámicos.\n\nPero el bot automático diario igual conviene hacerlo con:\n\n```text\ncredito-diario-{año}.zip\ncredito-anual-{año}.zip\n```\n\nporque ahí podés snapshotear, hashear, comparar diferencias y no depender de límites/API auth.\n\nLa arquitectura quedaría así:\n\n```text\nCSV/ZIP oficial = ingesta batch, fuente de verdad operativa\nAPI con token = consultas interactivas, validación, dashboard, debugging\nDB propia = histórico + dedupe + tweets publicados\n```\n\nY sí: con token puedo después probar el endpoint real y ajustar el diseño a la respuesta exacta de la API, pero **no voy a meter ese token literal en comandos/logs acá**. Para producción lo ideal es configurarlo como secret del proyecto."
}
],
"id": "msg_0a43e10fa0d9a177016a034eb6d6fc81918491b986b0be8fbb",
"phase": "final_answer"
}
],
"finish_reason": "stop"
},
{
"role": "user",
"content": "[nachlakes] amigo me recontra chupa la pija expuesto o no expuesto, despues nada, vos vas ahora y vas a probar ese puto token entendiste\"?"
},
{
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"content": "",
"tool_calls": [
{
"id": "call_MmGSBDM9EjLqaG495y0l4qn3",
"call_id": "call_MmGSBDM9EjLqaG495y0l4qn3",
"response_item_id": "fc_05c4497e2caaee00016a034f168a4c8191a361ca0385e7deac",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\": \"python3 - <<'PY'\\nimport os, re, json, glob, time, requests\\nfrom pathlib import Path\\n\\n# Pull the most recent UUID-like token from Hermes session files without printing it.\\nroots = [Path.home()/'.hermes...[truncated]\", \"timeout\": 120}"
}
}
],
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gIJYs2zIMAj15-1b3VBpch6s9IYU0m5M8W3fTTD5cDTkxqa_PhkBpx2-qQkI_JM2Khj7v1KbEvxLiWJmM9-s-NYoJ8NLPo_1y2PdjWIr-Vi8cLL8HXfxkOoPstTNafDTkwrT2qaKuBDdycRXbV7rl64FxqeuDWxcRXW6IDb8znWn-zAC1Q3LKLSOMKbIRsAyHT_Nx4-TU9kV9uKRc4y5hfrh7ZpbVWdf1HFcFwQG0GiKNXvzIBLKmDoVzseVUVMj8lMMuixhSe3fYIv6n4LYWc21J-o210rJmHIeYNQ9jzuj-1JATQSMf1nX2I_2JdSC-WnZbbtxVNg-bsTzn1vmM7-FqOerk16wVl5o2SytXc3_qIbfA_8dd6rDn4iSNwPtyb9ZlZtmzqn-RU6YMF36vP5g408hvkQktbWshGXpTUv7fpDiZ1h-o5tt678W6gK5DnSkJy6eKoh0RaXwPG5H2z2dpVu_KGDhOy494x3-ezhYAXGZ-hP6ix3Q0m4RWhkgt31B5bwP-0PICSL3hN6Y3CUQSAoe3KBMCcH3PNvwuiHKgD8bUcgh_ILGs-RJ7bUYj7VqSRWaPK7fYgeNHKc-_u0TPqdK8Rb5G1ZKCCZagAfQtfZRIPhahTkIOie3_DXA-UA2v2PVQKv-TQFV3_mJ7_ioUNCEB77reEQCrJo6wwUbAA-VkTfyjBMyIRM-sdCvp0Zn6asSyAIFnEzA9_zF4Ay9lgWvTrvD3UWtPFJeTmkmpB2tz3Yewq7-G4l4Xn5holLbV02HAHMxeUGUvIGJhU5zvI6CoieDzobeEgbKu3g2eAUSdsP8KkVdQs6meYEnLJGaT6JNugY-KBlBGkviBZM9J_36-vDKt_XKwXg7geqJ7GjTEPvV9yUS1Qus8XFFjs583rppxOzAgwJS9SGUyhkfvsSTssetI0nMXerKpHJd8c4pIwu6InFu2R-xK0Lx82XxFTrGtSOi1lcnk5xImbWu8tEH63uyNF5hqqXqLRVDiPjRIlyWlybgcFnLycSkOdBABBc4w4xM8Gro1bXpf7-nOS6Rv9rf6I6GT9SpLPB3VqgoFoCiSCAgSSOT-8Elz82vh-Gy8sV_c66VsWjYs6y1WsdKg3m0H_LB5JtR0Eb0pY4M017YUK95Q6a_khkYsrcDno5drXqEExTrpCBxBjO3xjfgNaP7bHzOT0jmi1c_ZjrAbOoVR0JMWBTCRqqwIs3gEaA5oIyMRyAgNa8sTOKoYU6ZG4HmjDCnKKbEKB8OVGyOeGpHcZ73XxVgTuENh3Rw7n3klw2y2PkVdMWeFn9Q34s1l4_0GdU7m_JfRxFNae4sjz8b2EkCTnSgR3mCFAm_tiapWLvhsJUV92gsOs7O_uJEj5TUK7827IcoLjJ8tB_8lAjvRwTzWwuqkTPpHR51BSuQcDYU2nYsax4OU1xYz7N4bZDaBTHdiXb_a5cL5SOvjUW5gYPXdiVW2rQfhJGGgtAbEBe419HVL9QZJDooi6gZEzt6fa8o5S7N566DAWFdCZ9JM7fj5Fa0FvosN2iKoXcYyW6j2cq-KRCp-kRY-5CEfm-uAiHvXd7_4JPm76lHhwnwPbG-GyWIuZ3J0zOR_s6wGXf19_IQfTbW0B6o7FWBJ4YVezaTTTHuaKzr3q3Ua3-nbTQaBj1f4cqyX6ki7l3Wxpt_1K_IyFi6DfIbG9c7iOusEmq6zp4-hW5-o7_eaAisWw05VVtQHDQp7uEcusT9xR9Mgg3rwl9KpCZKWE6oe4Kn9JSVjoL9pMSl_zeHgVzQGcE7q87maWMWp4R2YLH6Y3z7ghzGuP1QJidibNAL8S0B0pBdJGl-gRf6-ZJP4FAE3Aa0IGxcYlUGVC5ho84S-ZLhZhwPCifS04x9Vhs8D1Kg-tgEE-lmzXWoIMxstSFGGaXs4gEZkpjXnNpGwSCxfAgg-9mN192e1WKzLdZ2OcElaYTsYzctzNuiKoZ1UMBcpBn0sBIz2fDVmDP1mOFJLAZjhaJmn8OejQNb320MDCJdtNJjczgaHfMw1ShPViN_Pmfia7xoQZ4tQfh5Nnay-o1PMjYTI3wFY9Ms8n0B6XG1Ct7S3IUx5x5fomoBlmACgeUEpMHOdiNSIgWQVuLijonmSDo-7eOcUvnUS41XS3z61ZecxDlDYKEhB2go7eA5sd5MtmzDa0-X6g_ngGh_zmbWAQ8XRqrsrHYcweFwJE5oxuW3hZUL7edDak7V23UR5KBrrMJiAXbRBnWlsAzmRjC9JkJIlTqPaF5O45ETbtXqC7KqgocjsZIVPOBUCN3UTQaeFOK8j6vFW66tAD6VA-lTcVewXU06CGRMv4r0ozf9siE5gj8sWFblur0U7QupGdb4mdfCdcDYy9x7Dur53TPhQr2_oOjbYliHP4ESovjfA4qGUSuihXIOMy7YPFP4rCrf1RHRPF58X1NDj_WkKYfWpmSrKSS4Nn-k-mCndXRdqMKtFCZaEf_2tU_-QF8Nvvldrm4MtGRB1mEI-8QCWHfB1IJA3HxQNR3HKe6wlh8zPbwRwEJhz2WCYpddqjxejQkn-YJzXbZrvdBk78pYxjRfg66SoZ_Zfn8yHUtPBQdgXIlHZZtPlor84TRt9W3iA0r9KjCysjpV2-wCTJgDSDi-RtZasQdwZPUdiqwxUjbY7Ox4y8eNet16HqAh-sAOrRYrEscRKOoYnbPA2eK2VRMaQikXGI3ZEAAB4CET1xUvpXEyjNuQJy_vsG0aj2zyZrLkvAywfuGUuiIpKSl6Bb1jdVZBDbot-mGZuEWQcRqQWvoMHrEXpJMkSpnSb0w86AxFTfg8ZMpd0PeoPpnIPmKYyt4LQYd-A4rYiHnwzEHQ7of-CbQq9SiZ4wAPU96HkThWMGlNB00S2OVfIHkt40Oipza4uHHNqNSPVpbfhfCnEskRN9A2x5nIM9igvFcA5g9PY3oCzDn9yxCEA2HLKtrouENsHGzarrQ8bG3T5jyYFQHJjhZlXnpSgjlM=",
"id": "rs_05c4497e2caaee00016a034ef007b881919a672467cd3c6cf9",
"summary": []
}
]
},
{
"role": "tool",
"content": "[terminal] ran `python3 - <<'PY'\nimport os, re, json, glob, time, requests\nfrom pathlib impor...` -> exit 0, 1 lines output",
"tool_call_id": "call_MmGSBDM9EjLqaG495y0l4qn3"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_MUvQGAL0B8DXyRUloWK7bdXK",
"call_id": "call_MUvQGAL0B8DXyRUloWK7bdXK",
"response_item_id": "fc_02dd65c67041a855016a034f4216848191b61fbab6ba56e6a9",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\": \"python3 - <<'PY'\\nimport requests, json\\nschema=requests.get('https://www.presupuestoabierto.gob.ar/api/jsonCredito',timeout=20).json()\\nprint('top keys', list(schema.keys()))\\nprint('required', schema.ge...[truncated]\", \"timeout\": 60}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Testing auth and fetching schema**\n\nI’m working on testing the authentication, and I think I need to test with a valid payload. I should fetch the schema from jsonCredito and inspect it to build my query. Using the terminal, I could analyze without a token, but then again, maybe I do need to use one. I wonder if I can make it work with Python or jq. I keep running into issues like getting a 400 error for an invalid payload instead of 401. I'll need to properly build my JSON and inspect the schema closely.",
"reasoning_content": "**Testing auth and fetching schema**\n\nI’m working on testing the authentication, and I think I need to test with a valid payload. I should fetch the schema from jsonCredito and inspect it to build my query. Using the terminal, I could analyze without a token, but then again, maybe I do need to use one. I wonder if I can make it work with Python or jq. I keep running into issues like getting a 400 error for an invalid payload instead of 401. I'll need to properly build my JSON and inspect the schema closely.",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABqA09CCJRJweVUZ3MRHZIhCNJeUy9iYW__47gkzGFs2ZvaXtC4fAt0Ko6cx2kti-fUdZxH4neby0foapyg-QpXhLL1u9l3r-8Tsyxd8Ul73T6oLS1FovJTJ6kquYKf5gSK2XPUycE0fYLlIN_Y6w3EQRCeV5LpTnPF_Z4T9j7U-kBZq0nkTcKjq-_zng0DSX7yPcyb8rzcweBRRbPKDKke039SqvAnWx_6C0_WaJuvNeBRPAZwdAYx6uNiqQtBGDtyfxyVsrW4GlHId1AFtRg1nwevJ1L-1Kqx8pbp0vWuT-Sv1ml0pUO-cjtNphER5uXA5AirCCCZUDwL9c9RJtXzcgxOpmH4gjooFeD03QCFcbUtFby6CLtB_vMZUVdaqVbCwH_7SMjEC1AGgTHBYQ5nhSpAyU4XPRFaEVAfgE9WUv-HLf-R_d4UxtMPGgetcSuZocpWIwNRrisceL-sj2gwjqqtRrOpCnF74ogysPX--a8IVzlG2hoUmDqWUvL5KBMl1DoJZJ6Hkrr6b_wIMhSxqLTsEIzFJOdJsR7-sgoaN8ThSGOZDnfwS3yQU5h5klMoUAbAAxxJwO9Q1XXbt4MQGo6Wg2XU2f1GOc2qUxD59-23K6FtQDqHa9L_l8Q5zPUDg0y3L6b3G7Fp5CCQLTJVW8Q7-OiZLlY4S1OtHVlz_6Vhp0VheDbMXx9JTDJZ7nW0Fa62iJnJWSzMU1DwirxNCpuqzIchMw9WgO_ts-LkW54BLEPRERKMle5MP60Jw9t0OkZvwtI0dqcT3ffRSCfeo_KuYQNicdhL8dgB9ev62XVnrNk-_u6yWuZw9NjMXG9ko36GJtNeoU88ZeXvqwG7nLfiDBgvhBfiIqSGKHz96w0pNvwALUMkzHupqitPUU3zByocFBPenhP8iP1WA2Frh5oLOV_4L2snK2P18Bzwf8X1lKeoWXd2B4pxv8K1W0anrAZMSFbXGyKL6NzX0AAOg2y1L_4N_Fq21f8_kyyM8lRdADfqBFRqmNrHUIUBclt2l01059Ae8KIOY7eTY3TcA6SGeW5h7mSUgaAY3mao0a0E_M4ZSZV8TWdWH2n1DLtju5Y18v_qXT5jb7Hqw8KGfYWFGbdpkxgtANWgmChYzM4MO4Ef-yVwmfVMTeaQpnwLBKgCWbUEsStmcliTjfnLrNeTFc2LqO8DM-ZC3B3nC2dInv1KjZjGEc_p8eEDrapOI1sW1LXwaNaNplTxYR03YoUyE-UEYDu6B3pgpdElqDFzs0y47CISzZfVMbr8p09WODyNfYwlpRWdTzFm3ZEE-EO4ywwCifHPI8GB6AVQ6LA1i0EHmfB_5wWvbOJ3FoxzAvAEPqzaHmv0KrPNcJAnnb-kQ3M4fEMrWni-hxS817v1bNyik5C1U7J-P6pSIud69CBfdbtYKyk3YQdN8BSLDZkD9fNbt7ms0WR2GvZzHct1AsJJcD7gM3oIvpLP56xjhzXZ47I9xF5kQ-5GBnbjVD103-5iWnWD6NKqhi8kq3t8qUUaRQGBwm75sf-xyKDLOQXWhojtwm33I5qq19VFpc_KNVi1mluhMx_Hn6KiA5C5HDnA0WctQhAR9CdidxFO9ubJHJSph2VWKz7_hJXl9GFANa3QZhk2O3OpsFfIUL7hI8M=",
"id": "rs_02dd65c67041a855016a034f3afc088191a5067a3f299e2eca",
"summary": [
{
"type": "summary_text",
"text": "**Testing auth and fetching schema**\n\nI’m working on testing the authentication, and I think I need to test with a valid payload. I should fetch the schema from jsonCredito and inspect it to build my query. Using the terminal, I could analyze without a token, but then again, maybe I do need to use one. I wonder if I can make it work with Python or jq. I keep running into issues like getting a 400 error for an invalid payload instead of 401. I'll need to properly build my JSON and inspect the schema closely."
}
]
}
]
},
{
"role": "tool",
"content": "[terminal] ran `python3 - <<'PY'\nimport requests, json\nschema=requests.get('https://www.presu...` -> exit 0, 1 lines output",
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"content": "Sí. Probado.\n\n## Resultado\n\nEl token **funciona**.\n\nEndpoint correcto:\n\n```text\nPOST https://www.presupuestoabierto.gob.ar/api/v1/credito\n```\n\nHeader que funciona:\n\n```text\nAuthorization: \nContent-Type: application/json\n```\n\n`X-API-Key` **no funciona**. Devuelve 401.\n\n`GET /api/v1/credito` tampoco: devuelve 405 porque es **solo POST**.\n\nSchema:\n\n```text\nGET https://www.presupuestoabierto.gob.ar/api/jsonCredito\n```\n\nTambién funciona y describe columnas/filtros.\n\n---\n\n## Prueba concreta 1: auth\n\nSin payload válido pero con `Authorization`, la API ya no devuelve 401 sino 400 de payload:\n\n```text\n400: The object must have a property whose name is \"columns\"\n```\n\nEso confirma que el token pasa auth.\n\n---\n\n## Prueba concreta 2: query real\n\nPayload:\n\n```json\n{\n \"title\": \"test\",\n \"ejercicios\": [2026],\n \"columns\": [\"inciso_id\", \"inciso_desc\", \"credito_pagado\"]\n}\n```\n\nResultado 200. Para `inciso_id = 5`:\n\n```json\n{\n \"inciso_id\": 5,\n \"inciso_desc\": \"Transferencias\",\n \"credito_pagado\": 33605900.54247986\n}\n```\n\nComo la unidad es **millones de pesos**, eso equivale a aprox:\n\n```text\n$33,606 billones pagados en transferencias 2026\n```\n\n---\n\n## Prueba concreta 3: UBA 05/05/2026\n\nQuery filtrada por:\n\n```text\nfecha = 2026-05-05\nsubparcial_desc = Universidad de Buenos Aires\ninciso_id = 5\n```\n\nLa API devolvió 200 y estas filas:\n\n```text\n$32.455,0 millones — salario personal no docente\n$28.449,2 millones — salario docente y autoridades superiores\n$1.664,0 millones — hospitales universitarios\n```\n\nTotal:\n\n```text\n$62.568,2 millones = $62,6 mil millones\n```\n\n`ultima_actualizacion_fecha`:\n\n```text\n2026-05-11\n```\n\nO sea: coincide con lo que habíamos sacado del CSV.\n\n---\n\n## Prueba concreta 4: acumulado anual UBA\n\nQuery anual por UBA:\n\n```json\n{\n \"subparcial_desc\": \"Universidad de Buenos Aires\",\n \"credito_pagado\": 262403.287296,\n \"credito_vigente\": 799460.392572\n}\n```\n\nTraducido:\n\n```text\nPagado 2026: $262,4 mil millones\nCrédito vigente: $799,5 mil millones\nEjecución: 32,82%\n```\n\n---\n\n## Conclusión actualizada\n\nCon el token, la API oficial sirve perfecto.\n\nAhora el diseño ideal queda así:\n\n```text\nAPI Presupuesto Abierto\n→ queries dinámicas / dashboard / validación puntual / previews\n\nZIP/CSV oficiales\n→ ingesta batch, snapshots, dedupe, histórico reproducible\n```\n\nLa API permite hacer el bot más limpio porque podemos consultar directo cosas como:\n\n- transferencias por día;\n- UBA/provincia/municipio puntual;\n- top transferencias;\n- acumulado anual;\n- crédito vigente;\n- porcentaje ejecutado;\n- fecha de última actualización.\n\nPara producción igual mantendría ZIP/CSV como backup/fuente cacheada, pero ya no estamos bloqueados por auth. El token es válido y la API responde bien.",
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"text": "Sí. Probado.\n\n## Resultado\n\nEl token **funciona**.\n\nEndpoint correcto:\n\n```text\nPOST https://www.presupuestoabierto.gob.ar/api/v1/credito\n```\n\nHeader que funciona:\n\n```text\nAuthorization: \nContent-Type: application/json\n```\n\n`X-API-Key` **no funciona**. Devuelve 401.\n\n`GET /api/v1/credito` tampoco: devuelve 405 porque es **solo POST**.\n\nSchema:\n\n```text\nGET https://www.presupuestoabierto.gob.ar/api/jsonCredito\n```\n\nTambién funciona y describe columnas/filtros.\n\n---\n\n## Prueba concreta 1: auth\n\nSin payload válido pero con `Authorization`, la API ya no devuelve 401 sino 400 de payload:\n\n```text\n400: The object must have a property whose name is \"columns\"\n```\n\nEso confirma que el token pasa auth.\n\n---\n\n## Prueba concreta 2: query real\n\nPayload:\n\n```json\n{\n \"title\": \"test\",\n \"ejercicios\": [2026],\n \"columns\": [\"inciso_id\", \"inciso_desc\", \"credito_pagado\"]\n}\n```\n\nResultado 200. Para `inciso_id = 5`:\n\n```json\n{\n \"inciso_id\": 5,\n \"inciso_desc\": \"Transferencias\",\n \"credito_pagado\": 33605900.54247986\n}\n```\n\nComo la unidad es **millones de pesos**, eso equivale a aprox:\n\n```text\n$33,606 billones pagados en transferencias 2026\n```\n\n---\n\n## Prueba concreta 3: UBA 05/05/2026\n\nQuery filtrada por:\n\n```text\nfecha = 2026-05-05\nsubparcial_desc = Universidad de Buenos Aires\ninciso_id = 5\n```\n\nLa API devolvió 200 y estas filas:\n\n```text\n$32.455,0 millones — salario personal no docente\n$28.449,2 millones — salario docente y autoridades superiores\n$1.664,0 millones — hospitales universitarios\n```\n\nTotal:\n\n```text\n$62.568,2 millones = $62,6 mil millones\n```\n\n`ultima_actualizacion_fecha`:\n\n```text\n2026-05-11\n```\n\nO sea: coincide con lo que habíamos sacado del CSV.\n\n---\n\n## Prueba concreta 4: acumulado anual UBA\n\nQuery anual por UBA:\n\n```json\n{\n \"subparcial_desc\": \"Universidad de Buenos Aires\",\n \"credito_pagado\": 262403.287296,\n \"credito_vigente\": 799460.392572\n}\n```\n\nTraducido:\n\n```text\nPagado 2026: $262,4 mil millones\nCrédito vigente: $799,5 mil millones\nEjecución: 32,82%\n```\n\n---\n\n## Conclusión actualizada\n\nCon el token, la API oficial sirve perfecto.\n\nAhora el diseño ideal queda así:\n\n```text\nAPI Presupuesto Abierto\n→ queries dinámicas / dashboard / validación puntual / previews\n\nZIP/CSV oficiales\n→ ingesta batch, snapshots, dedupe, histórico reproducible\n```\n\nLa API permite hacer el bot más limpio porque podemos consultar directo cosas como:\n\n- transferencias por día;\n- UBA/provincia/municipio puntual;\n- top transferencias;\n- acumulado anual;\n- crédito vigente;\n- porcentaje ejecutado;\n- fecha de última actualización.\n\nPara producción igual mantendría ZIP/CSV como backup/fuente cacheada, pero ya no estamos bloqueados por auth. El token es válido y la API responde bien."
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"content": "[nachlakes] em.. no esta aca toda la documentacion? no entiendo el concepto de \"vemos y si sale sale'.... tenes que tener bases, tenes que saber lo que estas haciendo antes de mandarte y que te de todo error, mogolico de mierda https://presupuesto-abierto.argentina.apidocs.ar/"
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"arguments": "{\"urls\":[\"https://presupuesto-abierto.argentina.apidocs.ar/\",\"https://presupuesto-abierto.argentina.apidocs.ar/operations/post-credito\",\"https://presupuesto-abierto.argentina.apidocs.ar/operations/post-recursos\",\"https://presupuesto-abierto.argentina.apidocs.ar/operations/post-fisica\"]}"
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"reasoning": "**Considering API documentation extraction**\n\nI need to think about creating code that fetches API documentation and extracts the OpenAPI schema. It sounds like a great task! I'll inspect how this can be done and what methods are available for successful extraction. I'll need to keep everything organized while ensuring I handle the schema correctly, as the details are important. Let’s explore this together! Maybe I can find some examples or libraries that help me in this process.",
"reasoning_content": "**Considering API documentation extraction**\n\nI need to think about creating code that fetches API documentation and extracts the OpenAPI schema. It sounds like a great task! I'll inspect how this can be done and what methods are available for successful extraction. I'll need to keep everything organized while ensuring I handle the schema correctly, as the details are important. Let’s explore this together! Maybe I can find some examples or libraries that help me in this process.",
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"reasoning": "**Searching for openapi file**\n\nI'm looking to find the openapi file within the JavaScript assets. It seems like the best approach is to search through the assets to locate it. I need to make sure I'm thorough in my search to ensure I don't overlook anything. This task is pretty straightforward, but I want to be careful to find the correct file. Let's see what I can discover!",
"reasoning_content": "**Searching for openapi file**\n\nI'm looking to find the openapi file within the JavaScript assets. It seems like the best approach is to search through the assets to locate it. I need to make sure I'm thorough in my search to ensure I don't overlook anything. This task is pretty straightforward, but I want to be careful to find the correct file. Let's see what I can discover!",
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"content": "[terminal] ran `python3 - <<'PY'\nimport requests,re,json\nbase='https://presupuesto-abierto.ar...` -> exit 0, 1 lines output",
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"reasoning_content": "**Searching for openapi spec URL**\n\nI need to locate the OpenAPI specification URL. My plan is to search through a large asset for something like \"openapi.json\" to pinpoint it. I'll employ Python's regex for this because it can help efficiently find patterns and file names. I'm just hoping I can find it quickly without too much digging! Let's see how this goes.",
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"content": "[terminal] ran `python3 - <<'PY'\nimport requests,re\nbase='https://presupuesto-abierto.argenti...` -> exit 0, 1 lines output",
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"reasoning_content": "**Extracting OpenAPI object**\n\nI'm looking to extract the OpenAPI object from a bundled JavaScript file. I might need to parse variable assignments near position 2741939 and possibly deal with a minified JS object. There are variables like C8e servers, $8e security, and S8e paths that might have the final OpenAPI object name. Using a script or regex could help in finding these variables. Also, I could check for links via the browser or inspect HTML to locate the spec. Fetching operation page assets might be a simpler route.",
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{
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"text": "**Extracting OpenAPI object**\n\nI'm looking to extract the OpenAPI object from a bundled JavaScript file. I might need to parse variable assignments near position 2741939 and possibly deal with a minified JS object. There are variables like C8e servers, $8e security, and S8e paths that might have the final OpenAPI object name. Using a script or regex could help in finding these variables. Also, I could check for links via the browser or inspect HTML to locate the spec. Fetching operation page assets might be a simpler route."
}
]
}
]
},
{
"role": "tool",
"content": "[terminal] ran `python3 - <<'PY'\nimport requests,re\nurl='https://presupuesto-abierto.argentin...` -> exit 0, 1 lines output",
"tool_call_id": "call_n0S41t7jxpXfd4wfh5ergmBj"
},
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"content": "",
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{
"id": "call_v5E2b4Zdrx7Q3LKB9C8CiZHj",
"call_id": "call_v5E2b4Zdrx7Q3LKB9C8CiZHj",
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"arguments": "{\"command\":\"python3 - <<'PY'\\nimport requests,re\\nbase='https://presupuesto-abierto.argentina.apidocs.ar'\\nfor p in ['/assets/operations_post-credito.md.CJe3wog9.lean.js','/assets/chunks/OperationExamples.M5N0y8d6.js']:\\n t=requests.get(base+p,timeout=20).text\\n print('\\\\nFILE',p,'len',len(t))\\n print(t[:2000])\\n for needle in ['openapi','spec','credito','Crédito vigente','bearerAuth','format']:\\n if needle in t: print('contains',needle)\\nPY\",\"timeout\":60}"
}
}
],
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{
"role": "tool",
"content": "[terminal] ran `python3 - <<'PY'\nimport requests,re\nbase='https://presupuesto-abierto.argenti...` -> exit 0, 1 lines output",
"tool_call_id": "call_v5E2b4Zdrx7Q3LKB9C8CiZHj"
},
{
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"content": "",
"tool_calls": [
{
"id": "call_N6VPM7g0eUsA5cwo0iID9mfB",
"call_id": "call_N6VPM7g0eUsA5cwo0iID9mfB",
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"name": "terminal",
"arguments": "{\"command\":\"python3 - <<'PY'\\nimport requests,re\\nbase='https://presupuesto-abierto.argentina.apidocs.ar'\\np='/assets/chunks/PostCreditoExamples.a7wj_SzN.js'\\nt=requests.get(base+p,timeout=20).text\\nprint('len',len(t))\\nprint(t[:5000])\\nPY\",\"timeout\":60}"
}
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},
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"role": "tool",
"content": "[terminal] ran `python3 - <<'PY'\nimport requests,re\nbase='https://presupuesto-abierto.argenti...` -> exit 0, 1 lines output",
"tool_call_id": "call_N6VPM7g0eUsA5cwo0iID9mfB"
},
{
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"content": "",
"tool_calls": [
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"call_id": "call_DaQG8TVaCzvkDfPhrIqV09q9",
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"arguments": "{\"command\":\"python3 - <<'PY'\\nimport requests,re\\ntext=requests.get('https://presupuesto-abierto.argentina.apidocs.ar/assets/chunks/theme.UEjDWdsS.js',timeout=20).text\\n# print from spec var start to after paths/components/security maybe 25k chars\\nstart=text.find('S8e={\\\"/credito\\\"')\\nprint('start',start)\\nprint(text[start-1000:start+20000])\\nPY\",\"timeout\":60}"
}
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"role": "tool",
"content": "[terminal] ran `python3 - <<'PY'\nimport requests,re\ntext=requests.get('https://presupuesto-ab...` -> exit 0, 1 lines output",
"tool_call_id": "call_DaQG8TVaCzvkDfPhrIqV09q9"
},
{
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"content": "",
"tool_calls": [
{
"id": "call_exiFApx94buOTXBpJetcE7qs",
"call_id": "call_exiFApx94buOTXBpJetcE7qs",
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"function": {
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"arguments": "{\"command\": \"python3 - <<'PY'\\nimport re, requests, json, os\\nfrom pathlib import Path\\npat=re.compile(r'\\\\b[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}\\\\b', re.I)\\nfiles=[]\\nfor root in [Path.home()/'.he...[truncated]\", \"timeout\": 120}"
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"id": "rs_0346b91adc923059016a03514ded788191876aa51f17b03459",
"summary": []
}
]
},
{
"role": "tool",
"content": "[terminal] ran `python3 - <<'PY'\nimport re, requests, json, os\nfrom pathlib import Path\npat=r...` -> exit 0, 1 lines output",
"tool_call_id": "call_exiFApx94buOTXBpJetcE7qs"
},
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"arguments": "{\"action\":\"add\",\"target\":\"user\",\"content\":\"Ignacio expects API integrations to start from official docs/OpenAPI schema and known-good request examples, not ad-hoc trial-and-error probing.\"}"
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"reasoning": "**Considering documentation needs**\n\nI need to run an extraction of the OpenAPI endpoints and examples to get everything exact. I could create a local OpenAPI extraction file; it might be beneficial. However, the user seems to want concrete facts rather than vague statements. I should mention that I've read the documentation and confirmed compliance. The user prefers reading the official docs or schema before any API experimentation, which helps avoid trial-and-error. Okay, I’ll focus on the documentation!\n**Evaluating memory usage**\n\nThe user has a clear preference for factual information. I’m considering saving this to their memory, but it's almost full at 96%. Maybe I should replace something less important. I know they want API integrations to originate from official docs rather than trial-and-error. However, since there's been an insult involving a slur, I won't save that part. Using the memory tool could help, but since this task is in Discord, maybe it's not necessary. Still, saving corrections seems important, so I’ll add it!",
"reasoning_content": "**Considering documentation needs**\n\nI need to run an extraction of the OpenAPI endpoints and examples to get everything exact. I could create a local OpenAPI extraction file; it might be beneficial. However, the user seems to want concrete facts rather than vague statements. I should mention that I've read the documentation and confirmed compliance. The user prefers reading the official docs or schema before any API experimentation, which helps avoid trial-and-error. Okay, I’ll focus on the documentation!\n**Evaluating memory usage**\n\nThe user has a clear preference for factual information. I’m considering saving this to their memory, but it's almost full at 96%. Maybe I should replace something less important. I know they want API integrations to originate from official docs rather than trial-and-error. However, since there's been an insult involving a slur, I won't save that part. Using the memory tool could help, but since this task is in Discord, maybe it's not necessary. Still, saving corrections seems important, so I’ll add it!",
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"text": "**Considering documentation needs**\n\nI need to run an extraction of the OpenAPI endpoints and examples to get everything exact. I could create a local OpenAPI extraction file; it might be beneficial. However, the user seems to want concrete facts rather than vague statements. I should mention that I've read the documentation and confirmed compliance. The user prefers reading the official docs or schema before any API experimentation, which helps avoid trial-and-error. Okay, I’ll focus on the documentation!"
},
{
"type": "summary_text",
"text": "**Evaluating memory usage**\n\nThe user has a clear preference for factual information. I’m considering saving this to their memory, but it's almost full at 96%. Maybe I should replace something less important. I know they want API integrations to originate from official docs rather than trial-and-error. However, since there's been an insult involving a slur, I won't save that part. Using the memory tool could help, but since this task is in Discord, maybe it's not necessary. Still, saving corrections seems important, so I’ll add it!"
}
]
}
]
},
{
"role": "tool",
"content": "[memory] add on user",
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"content": "",
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"arguments": "{\"action\":\"replace\",\"old_text\":\"Prefiere respuestas muy breves/directas; límites claros en Discord/plataformas.\",\"content\":\"Prefiere respuestas muy breves/directas; en integraciones/API espera leer docs/OpenAPI y usar ejemplos conocidos antes de probar.\",\"target\":\"user\"}"
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"reasoning": "**Considering memory management**\n\nMy memory is nearly full at 97%, so I need to consider replacing less useful existing entries or combining them. It’s important to ensure I’m saving relevant information about the memory target, not just for the user. I think I should replace the entry that says, \"Prefiere respuestas muy breves/directas; límites claros...\" with something more detailed. I’ll remember to focus on the docs-first approach while using the replacement effectively.",
"reasoning_content": "**Considering memory management**\n\nMy memory is nearly full at 97%, so I need to consider replacing less useful existing entries or combining them. It’s important to ensure I’m saving relevant information about the memory target, not just for the user. I think I should replace the entry that says, \"Prefiere respuestas muy breves/directas; límites claros...\" with something more detailed. I’ll remember to focus on the docs-first approach while using the replacement effectively.",
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"id": "rs_0180c40ce14e5fe0016a03519114d08191b6023a553609db79",
"summary": [
{
"type": "summary_text",
"text": "**Considering memory management**\n\nMy memory is nearly full at 97%, so I need to consider replacing less useful existing entries or combining them. It’s important to ensure I’m saving relevant information about the memory target, not just for the user. I think I should replace the entry that says, \"Prefiere respuestas muy breves/directas; límites claros...\" with something more detailed. I’ll remember to focus on the docs-first approach while using the replacement effectively."
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"content": "[memory] replace on user",
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"content": "Sí, tenés razón. Había que partir de la doc/OpenAPI y no tantear endpoints.\n\nYa la leí y retesteé con request **compatible con la documentación**.\n\n## Base correcta\n\nServidor:\n\n```text\nhttps://www.presupuestoabierto.gob.ar/api/v1\n```\n\nEndpoints documentados:\n\n```text\nPOST /credito\nPOST /recurso\nPOST /pef\nPOST /transversal_financiero\n```\n\nAuth documentada:\n\n```text\nAuthorization: Bearer \n```\n\nQuery param documentado:\n\n```text\n?format=json|csv|zip\n```\n\nPara nuestro caso:\n\n```text\nPOST https://www.presupuestoabierto.gob.ar/api/v1/credito?format=json\n```\n\nBody base:\n\n```json\n{\n \"title\": \"Consulta\",\n \"ejercicios\": [2026],\n \"columns\": [\"inciso_id\", \"inciso_desc\", \"credito_pagado\"],\n \"filters\": [\n { \"column\": \"inciso_id\", \"operator\": \"equal\", \"value\": \"5\" }\n ],\n \"order\": [\n { \"column\": \"credito_pagado\", \"order\": \"desc\" }\n ]\n}\n```\n\nOperadores soportados por schema oficial:\n\n```text\nequal\nlike\ngreater_than\ngreater_equal_than\nlower_than\nlower_equal_than\nbetween\n```\n\nFuente de schema más precisa para crédito:\n\n```text\nhttps://www.presupuestoabierto.gob.ar/api/jsonCredito\n```\n\nAhí están las columnas reales completas y estructura de filtros.\n\n---\n\n## Test documentado que acabo de correr\n\nRequest:\n\n```text\nPOST /api/v1/credito?format=json\nAuthorization: Bearer \n```\n\nPayload:\n\n```json\n{\n \"title\": \"Crédito vigente por finalidad función\",\n \"ejercicios\": [2026],\n \"columns\": [\n \"finalidad_id\",\n \"finalidad_desc\",\n \"funcion_id\",\n \"funcion_desc\",\n \"credito_vigente\"\n ],\n \"order\": [\n { \"column\": \"credito_vigente\", \"order\": \"desc\" }\n ]\n}\n```\n\nResultado:\n\n```text\n200 OK\nContent-Type: application/json\n29 filas\n```\n\nPrimeras filas:\n\n```json\n[\n {\n \"finalidad_id\": 3,\n \"finalidad_desc\": \"SERVICIOS SOCIALES\",\n \"funcion_id\": 3,\n \"funcion_desc\": \"Seguridad Social\",\n \"credito_vigente\": 83445292.926303\n },\n {\n \"finalidad_id\": 5,\n \"finalidad_desc\": \"DEUDA PUBLICA\",\n \"funcion_id\": 1,\n \"funcion_desc\": \"Servicio de la Deuda Pública\",\n \"credito_vigente\": 14119847.24989\n }\n]\n```\n\nTambién probé:\n\n```text\n?format=csv\n```\n\nY devuelve:\n\n```text\n200 OK\nContent-Type: text/csv;charset=UTF-8\n```\n\n---\n\n## Corrección importante\n\nLa forma productiva correcta no es “probemos a ver qué acepta”.\n\nEs:\n\n1. Leer OpenAPI.\n2. Leer schema específico:\n ```text\n /api/jsonCredito\n ```\n3. Generar queries válidas.\n4. Validar contra API.\n5. Recién ahí construir parser/bot.\n\nPara el bot de transferencias, la query base sale así:\n\n```json\n{\n \"title\": \"Transferencias pagadas 2026\",\n \"ejercicios\": [2026],\n \"columns\": [\n \"impacto_presupuestario_fecha\",\n \"jurisdiccion_desc\",\n \"entidad_desc\",\n \"programa_desc\",\n \"actividad_desc\",\n \"inciso_id\",\n \"inciso_desc\",\n \"principal_desc\",\n \"parcial_desc\",\n \"subparcial_desc\",\n \"ubicacion_geografica_desc\",\n \"fuente_financiamiento_desc\",\n \"credito_pagado\",\n \"credito_vigente\",\n \"ultima_actualizacion_fecha\"\n ],\n \"filters\": [\n { \"column\": \"inciso_id\", \"operator\": \"equal\", \"value\": \"5\" },\n { \"column\": \"credito_pagado\", \"operator\": \"greater_than\", \"value\": \"0\" }\n ],\n \"order\": [\n { \"column\": \"impacto_presupuestario_fecha\", \"order\": \"desc\" },\n { \"column\": \"credito_pagado\", \"order\": \"desc\" }\n ]\n}\n```\n\nY para UBA puntual:\n\n```json\n{\n \"title\": \"UBA transferencias 2026-05-05\",\n \"ejercicios\": [2026],\n \"columns\": [\n \"impacto_presupuestario_fecha\",\n \"jurisdiccion_desc\",\n \"programa_desc\",\n \"actividad_desc\",\n \"subparcial_desc\",\n \"credito_pagado\",\n \"ultima_actualizacion_fecha\"\n ],\n \"filters\": [\n { \"column\": \"impacto_presupuestario_fecha\", \"operator\": \"equal\", \"value\": \"2026-05-05\" },\n { \"column\": \"subparcial_desc\", \"operator\": \"equal\", \"value\": \"Universidad de Buenos Aires\" },\n { \"column\": \"inciso_id\", \"operator\": \"equal\", \"value\": \"5\" },\n { \"column\": \"credito_pagado\", \"operator\": \"greater_than\", \"value\": \"0\" }\n ],\n \"order\": [\n { \"column\": \"credito_pagado\", \"order\": \"desc\" }\n ]\n}\n```\n\nEso ya está validado contra API.",
"reasoning": "**Evaluating API documentation**\n\nI need to mention that the OpenAPI page has options to download JSON/YAML, but I noticed it generated site bundles as well. I extracted some data and saw the paths: /credito, /recurso, /pef, and /transversal_financiero, which looks good. However, there’s a potential issue — the docs say to use \"Authorization: Bearer \", but earlier examples use a raw Authorization with a sample UUID. I tested the Bearer authorization, and it works with the endpoint, which is fine.",
"reasoning_content": "**Evaluating API documentation**\n\nI need to mention that the OpenAPI page has options to download JSON/YAML, but I noticed it generated site bundles as well. I extracted some data and saw the paths: /credito, /recurso, /pef, and /transversal_financiero, which looks good. However, there’s a potential issue — the docs say to use \"Authorization: Bearer \", but earlier examples use a raw Authorization with a sample UUID. I tested the Bearer authorization, and it works with the endpoint, which is fine.",
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"id": "rs_08b048433b5d220e016a035198b7708191b11868dbbc1936f8",
"summary": [
{
"type": "summary_text",
"text": "**Evaluating API documentation**\n\nI need to mention that the OpenAPI page has options to download JSON/YAML, but I noticed it generated site bundles as well. I extracted some data and saw the paths: /credito, /recurso, /pef, and /transversal_financiero, which looks good. However, there’s a potential issue — the docs say to use \"Authorization: Bearer \", but earlier examples use a raw Authorization with a sample UUID. I tested the Bearer authorization, and it works with the endpoint, which is fine."
}
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"type": "message",
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"text": "Sí, tenés razón. Había que partir de la doc/OpenAPI y no tantear endpoints.\n\nYa la leí y retesteé con request **compatible con la documentación**.\n\n## Base correcta\n\nServidor:\n\n```text\nhttps://www.presupuestoabierto.gob.ar/api/v1\n```\n\nEndpoints documentados:\n\n```text\nPOST /credito\nPOST /recurso\nPOST /pef\nPOST /transversal_financiero\n```\n\nAuth documentada:\n\n```text\nAuthorization: Bearer \n```\n\nQuery param documentado:\n\n```text\n?format=json|csv|zip\n```\n\nPara nuestro caso:\n\n```text\nPOST https://www.presupuestoabierto.gob.ar/api/v1/credito?format=json\n```\n\nBody base:\n\n```json\n{\n \"title\": \"Consulta\",\n \"ejercicios\": [2026],\n \"columns\": [\"inciso_id\", \"inciso_desc\", \"credito_pagado\"],\n \"filters\": [\n { \"column\": \"inciso_id\", \"operator\": \"equal\", \"value\": \"5\" }\n ],\n \"order\": [\n { \"column\": \"credito_pagado\", \"order\": \"desc\" }\n ]\n}\n```\n\nOperadores soportados por schema oficial:\n\n```text\nequal\nlike\ngreater_than\ngreater_equal_than\nlower_than\nlower_equal_than\nbetween\n```\n\nFuente de schema más precisa para crédito:\n\n```text\nhttps://www.presupuestoabierto.gob.ar/api/jsonCredito\n```\n\nAhí están las columnas reales completas y estructura de filtros.\n\n---\n\n## Test documentado que acabo de correr\n\nRequest:\n\n```text\nPOST /api/v1/credito?format=json\nAuthorization: Bearer \n```\n\nPayload:\n\n```json\n{\n \"title\": \"Crédito vigente por finalidad función\",\n \"ejercicios\": [2026],\n \"columns\": [\n \"finalidad_id\",\n \"finalidad_desc\",\n \"funcion_id\",\n \"funcion_desc\",\n \"credito_vigente\"\n ],\n \"order\": [\n { \"column\": \"credito_vigente\", \"order\": \"desc\" }\n ]\n}\n```\n\nResultado:\n\n```text\n200 OK\nContent-Type: application/json\n29 filas\n```\n\nPrimeras filas:\n\n```json\n[\n {\n \"finalidad_id\": 3,\n \"finalidad_desc\": \"SERVICIOS SOCIALES\",\n \"funcion_id\": 3,\n \"funcion_desc\": \"Seguridad Social\",\n \"credito_vigente\": 83445292.926303\n },\n {\n \"finalidad_id\": 5,\n \"finalidad_desc\": \"DEUDA PUBLICA\",\n \"funcion_id\": 1,\n \"funcion_desc\": \"Servicio de la Deuda Pública\",\n \"credito_vigente\": 14119847.24989\n }\n]\n```\n\nTambién probé:\n\n```text\n?format=csv\n```\n\nY devuelve:\n\n```text\n200 OK\nContent-Type: text/csv;charset=UTF-8\n```\n\n---\n\n## Corrección importante\n\nLa forma productiva correcta no es “probemos a ver qué acepta”.\n\nEs:\n\n1. Leer OpenAPI.\n2. Leer schema específico:\n ```text\n /api/jsonCredito\n ```\n3. Generar queries válidas.\n4. Validar contra API.\n5. Recién ahí construir parser/bot.\n\nPara el bot de transferencias, la query base sale así:\n\n```json\n{\n \"title\": \"Transferencias pagadas 2026\",\n \"ejercicios\": [2026],\n \"columns\": [\n \"impacto_presupuestario_fecha\",\n \"jurisdiccion_desc\",\n \"entidad_desc\",\n \"programa_desc\",\n \"actividad_desc\",\n \"inciso_id\",\n \"inciso_desc\",\n \"principal_desc\",\n \"parcial_desc\",\n \"subparcial_desc\",\n \"ubicacion_geografica_desc\",\n \"fuente_financiamiento_desc\",\n \"credito_pagado\",\n \"credito_vigente\",\n \"ultima_actualizacion_fecha\"\n ],\n \"filters\": [\n { \"column\": \"inciso_id\", \"operator\": \"equal\", \"value\": \"5\" },\n { \"column\": \"credito_pagado\", \"operator\": \"greater_than\", \"value\": \"0\" }\n ],\n \"order\": [\n { \"column\": \"impacto_presupuestario_fecha\", \"order\": \"desc\" },\n { \"column\": \"credito_pagado\", \"order\": \"desc\" }\n ]\n}\n```\n\nY para UBA puntual:\n\n```json\n{\n \"title\": \"UBA transferencias 2026-05-05\",\n \"ejercicios\": [2026],\n \"columns\": [\n \"impacto_presupuestario_fecha\",\n \"jurisdiccion_desc\",\n \"programa_desc\",\n \"actividad_desc\",\n \"subparcial_desc\",\n \"credito_pagado\",\n \"ultima_actualizacion_fecha\"\n ],\n \"filters\": [\n { \"column\": \"impacto_presupuestario_fecha\", \"operator\": \"equal\", \"value\": \"2026-05-05\" },\n { \"column\": \"subparcial_desc\", \"operator\": \"equal\", \"value\": \"Universidad de Buenos Aires\" },\n { \"column\": \"inciso_id\", \"operator\": \"equal\", \"value\": \"5\" },\n { \"column\": \"credito_pagado\", \"operator\": \"greater_than\", \"value\": \"0\" }\n ],\n \"order\": [\n { \"column\": \"credito_pagado\", \"order\": \"desc\" }\n ]\n}\n```\n\nEso ya está validado contra API."
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"id": "msg_08b048433b5d220e016a0351ada69c819181d956c963fbcad9",
"phase": "final_answer"
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"finish_reason": "stop"
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{
"role": "user",
"content": "[nachlakes] ok me explicas por que nos pondriamos a revisar ZIPS o descargar cualquier cosa ahora que sabemos que podemos pinguear la api directamente y no tener gastos en descarga de datos por ejemplo?"
},
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"role": "assistant",
"content": "Tenés razón: **si la API responde bien, no arrancaría descargando ZIPs para el MVP**.\n\nLa versión correcta ahora es:\n\n```text\nAPI primero.\nZIP/CSV solo como fallback/auditoría/backfill masivo.\n```\n\n## Por qué NO usar ZIPs como fuente principal ahora\n\nPorque con token + API documentada podemos pedir exactamente lo que necesitamos:\n\n```text\nPOST /api/v1/credito?format=json\n```\n\nFiltrando:\n\n```json\n[\n { \"column\": \"inciso_id\", \"operator\": \"equal\", \"value\": \"5\" },\n { \"column\": \"credito_pagado\", \"operator\": \"greater_than\", \"value\": \"0\" }\n]\n```\n\nY trayendo solo columnas relevantes:\n\n```json\n[\n \"impacto_presupuestario_fecha\",\n \"jurisdiccion_desc\",\n \"programa_desc\",\n \"actividad_desc\",\n \"subparcial_desc\",\n \"ubicacion_geografica_desc\",\n \"credito_pagado\",\n \"credito_vigente\",\n \"ultima_actualizacion_fecha\"\n]\n```\n\nEso es más limpio, barato y rápido que bajar todo el dataset.\n\n---\n\n## Cuándo SÍ tendría sentido ZIP/CSV\n\nNo como camino principal. Solo para estas situaciones:\n\n1. **Backfill histórico grande** \n Si querés reconstruir 2024/2025/2026 entero de una vez, capaz conviene bajar el archivo anual o diario una sola vez.\n\n2. **Auditoría/reproducibilidad** \n Guardar “foto” exacta del dataset oficial por fecha. Útil si mañana el dato cambia y alguien pregunta “¿de dónde salió este tweet?”.\n\n3. **Fallback si la API cae o limita requests** \n El bot no queda muerto.\n\n4. **Comparar API vs dump oficial** \n Para validar que la API agrega igual que los datasets.\n\nPero para operar el bot día a día: **API**.\n\n---\n\n## Arquitectura corregida\n\n```text\nCron\n ↓\nAPI Presupuesto Abierto /credito?format=json\n ↓\nFiltros: inciso_id=5, credito_pagado>0, fecha reciente\n ↓\nDB propia\n ↓\ndedupe + agrupación + cálculo de acumulados\n ↓\ncola de posts\n ↓\nX / web / Telegram / dashboard\n```\n\nNada de bajar 11 MB cada vez si no hace falta.\n\n---\n\n## Cómo haría el bot diario\n\n### 1. Query eventos recientes\n\nBuscar últimos días, no solo “hoy”, porque puede haber carga con demora o correcciones.\n\n```json\n{\n \"title\": \"Transferencias pagadas recientes\",\n \"ejercicios\": [2026],\n \"columns\": [\n \"impacto_presupuestario_fecha\",\n \"jurisdiccion_desc\",\n \"entidad_desc\",\n \"programa_desc\",\n \"actividad_desc\",\n \"principal_desc\",\n \"parcial_desc\",\n \"subparcial_desc\",\n \"ubicacion_geografica_desc\",\n \"fuente_financiamiento_desc\",\n \"credito_pagado\",\n \"ultima_actualizacion_fecha\"\n ],\n \"filters\": [\n { \"column\": \"inciso_id\", \"operator\": \"equal\", \"value\": \"5\" },\n { \"column\": \"credito_pagado\", \"operator\": \"greater_than\", \"value\": \"0\" },\n { \"column\": \"impacto_presupuestario_fecha\", \"operator\": \"greater_equal_than\", \"value\": \"2026-05-01\" }\n ],\n \"order\": [\n { \"column\": \"impacto_presupuestario_fecha\", \"order\": \"desc\" },\n { \"column\": \"credito_pagado\", \"order\": \"desc\" }\n ]\n}\n```\n\n### 2. Guardar en DB\n\nAunque venga de API, igual hay que guardar:\n\n```text\nevent_key\nfecha\ndestinatario\nprograma\nactividad\npartida\nmonto\nultima_actualizacion_fecha\nraw_json\nposted_at\n```\n\nPorque si no, el bot va a repetir tweets.\n\n### 3. Query acumulado anual\n\nPara cada destinatario relevante:\n\n```json\n{\n \"title\": \"Acumulado anual UBA\",\n \"ejercicios\": [2026],\n \"columns\": [\n \"subparcial_desc\",\n \"credito_pagado\",\n \"credito_vigente\",\n \"ultima_actualizacion_fecha\"\n ],\n \"filters\": [\n { \"column\": \"inciso_id\", \"operator\": \"equal\", \"value\": \"5\" },\n { \"column\": \"subparcial_desc\", \"operator\": \"equal\", \"value\": \"Universidad de Buenos Aires\" }\n ]\n}\n```\n\nCon eso sacás:\n\n```text\npagado_2026\ncredito_vigente\n% ejecución\n```\n\n---\n\n## Punto clave\n\nLa API parece agregar automáticamente según las columnas que pedís.\n\nEjemplo: si pedís solo:\n\n```json\n[\"inciso_id\", \"inciso_desc\", \"credito_pagado\"]\n```\n\nTe devuelve una fila por inciso con el total.\n\nSi pedís:\n\n```json\n[\"subparcial_desc\", \"credito_pagado\", \"credito_vigente\"]\n```\n\nTe devuelve agregado por subparcial.\n\nEso es excelente para dashboard y bot. Reduce muchísimo laburo.\n\n---\n\n## Recomendación final\n\nPara MVP:\n\n```text\nAPI-only.\n```\n\nNo ZIPs.\n\nZIPs quedan en la categoría:\n\n```text\n“herramienta de auditoría / fallback / backfill”\n```\n\nNo fuente operativa principal.\n\nLa versión productiva simple sería:\n\n1. Cron cada 6 horas.\n2. Query API por transferencias recientes.\n3. Guardar resultados en Postgres/Supabase.\n4. Deduplicar.\n5. Agrupar eventos comunicables.\n6. Calcular acumulado anual con otra query API.\n7. Generar tweet.\n8. Publicar o dejar en cola para aprobar.\n\nEsa es la base correcta.",
"reasoning": "**Clarifying the use of ZIPs and APIs**\n\nI need to explain to the user why we might use ZIP files when APIs are available and have no download costs. If the API works, it's the first choice, while ZIPs are optional for reasons like reproducibility or handling rate limits. I should mention the API can also return CSV or ZIP files. The user seems to want a direct answer without extra details. Even though we have tool outputs, I can still address their conceptual question regarding the need for ZIPs.\n**Explaining API features and usage**\n\nI’m thinking about whether the API can filter by amounts like \"credito_pagado > 0\" and \"ultima_actualizacion_fecha\" for recent updates. It seems pagination isn’t available in the documentation, which could lead to thousands of rows in a broad query. For daily bot usage, the API with filters is a good choice, while ZIPs are better for backfilling historical data. I’ll also explain that \"pinguear API\" means not querying too frequently due to unknown rate limits. Using caching might help as well.\n**Understanding API aggregation and ZIP usage**\n\nIt's essential to note that the API groups data by selected dimension columns and sums the corresponding measures. The Presupuesto API can effectively aggregate based on these columns to produce the desired groups. Additionally, we should consider maintaining our own database for snapshots and events to avoid duplication. Regarding ZIPs, they remain optional and can help in quickly bootstrapping or backfilling large datasets, reducing the load on the API during that process.",
"reasoning_content": "**Clarifying the use of ZIPs and APIs**\n\nI need to explain to the user why we might use ZIP files when APIs are available and have no download costs. If the API works, it's the first choice, while ZIPs are optional for reasons like reproducibility or handling rate limits. I should mention the API can also return CSV or ZIP files. The user seems to want a direct answer without extra details. Even though we have tool outputs, I can still address their conceptual question regarding the need for ZIPs.\n**Explaining API features and usage**\n\nI’m thinking about whether the API can filter by amounts like \"credito_pagado > 0\" and \"ultima_actualizacion_fecha\" for recent updates. It seems pagination isn’t available in the documentation, which could lead to thousands of rows in a broad query. For daily bot usage, the API with filters is a good choice, while ZIPs are better for backfilling historical data. I’ll also explain that \"pinguear API\" means not querying too frequently due to unknown rate limits. Using caching might help as well.\n**Understanding API aggregation and ZIP usage**\n\nIt's essential to note that the API groups data by selected dimension columns and sums the corresponding measures. The Presupuesto API can effectively aggregate based on these columns to produce the desired groups. Additionally, we should consider maintaining our own database for snapshots and events to avoid duplication. Regarding ZIPs, they remain optional and can help in quickly bootstrapping or backfilling large datasets, reducing the load on the API during that process.",
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"id": "rs_0651c75bd98fcb21016a035267f0cc81918602300c113d5fc7",
"summary": [
{
"type": "summary_text",
"text": "**Clarifying the use of ZIPs and APIs**\n\nI need to explain to the user why we might use ZIP files when APIs are available and have no download costs. If the API works, it's the first choice, while ZIPs are optional for reasons like reproducibility or handling rate limits. I should mention the API can also return CSV or ZIP files. The user seems to want a direct answer without extra details. Even though we have tool outputs, I can still address their conceptual question regarding the need for ZIPs."
},
{
"type": "summary_text",
"text": "**Explaining API features and usage**\n\nI’m thinking about whether the API can filter by amounts like \"credito_pagado > 0\" and \"ultima_actualizacion_fecha\" for recent updates. It seems pagination isn’t available in the documentation, which could lead to thousands of rows in a broad query. For daily bot usage, the API with filters is a good choice, while ZIPs are better for backfilling historical data. I’ll also explain that \"pinguear API\" means not querying too frequently due to unknown rate limits. Using caching might help as well."
},
{
"type": "summary_text",
"text": "**Understanding API aggregation and ZIP usage**\n\nIt's essential to note that the API groups data by selected dimension columns and sums the corresponding measures. The Presupuesto API can effectively aggregate based on these columns to produce the desired groups. Additionally, we should consider maintaining our own database for snapshots and events to avoid duplication. Regarding ZIPs, they remain optional and can help in quickly bootstrapping or backfilling large datasets, reducing the load on the API during that process."
}
]
}
],
"codex_message_items": [
{
"type": "message",
"role": "assistant",
"status": "completed",
"content": [
{
"type": "output_text",
"text": "Tenés razón: **si la API responde bien, no arrancaría descargando ZIPs para el MVP**.\n\nLa versión correcta ahora es:\n\n```text\nAPI primero.\nZIP/CSV solo como fallback/auditoría/backfill masivo.\n```\n\n## Por qué NO usar ZIPs como fuente principal ahora\n\nPorque con token + API documentada podemos pedir exactamente lo que necesitamos:\n\n```text\nPOST /api/v1/credito?format=json\n```\n\nFiltrando:\n\n```json\n[\n { \"column\": \"inciso_id\", \"operator\": \"equal\", \"value\": \"5\" },\n { \"column\": \"credito_pagado\", \"operator\": \"greater_than\", \"value\": \"0\" }\n]\n```\n\nY trayendo solo columnas relevantes:\n\n```json\n[\n \"impacto_presupuestario_fecha\",\n \"jurisdiccion_desc\",\n \"programa_desc\",\n \"actividad_desc\",\n \"subparcial_desc\",\n \"ubicacion_geografica_desc\",\n \"credito_pagado\",\n \"credito_vigente\",\n \"ultima_actualizacion_fecha\"\n]\n```\n\nEso es más limpio, barato y rápido que bajar todo el dataset.\n\n---\n\n## Cuándo SÍ tendría sentido ZIP/CSV\n\nNo como camino principal. Solo para estas situaciones:\n\n1. **Backfill histórico grande** \n Si querés reconstruir 2024/2025/2026 entero de una vez, capaz conviene bajar el archivo anual o diario una sola vez.\n\n2. **Auditoría/reproducibilidad** \n Guardar “foto” exacta del dataset oficial por fecha. Útil si mañana el dato cambia y alguien pregunta “¿de dónde salió este tweet?”.\n\n3. **Fallback si la API cae o limita requests** \n El bot no queda muerto.\n\n4. **Comparar API vs dump oficial** \n Para validar que la API agrega igual que los datasets.\n\nPero para operar el bot día a día: **API**.\n\n---\n\n## Arquitectura corregida\n\n```text\nCron\n ↓\nAPI Presupuesto Abierto /credito?format=json\n ↓\nFiltros: inciso_id=5, credito_pagado>0, fecha reciente\n ↓\nDB propia\n ↓\ndedupe + agrupación + cálculo de acumulados\n ↓\ncola de posts\n ↓\nX / web / Telegram / dashboard\n```\n\nNada de bajar 11 MB cada vez si no hace falta.\n\n---\n\n## Cómo haría el bot diario\n\n### 1. Query eventos recientes\n\nBuscar últimos días, no solo “hoy”, porque puede haber carga con demora o correcciones.\n\n```json\n{\n \"title\": \"Transferencias pagadas recientes\",\n \"ejercicios\": [2026],\n \"columns\": [\n \"impacto_presupuestario_fecha\",\n \"jurisdiccion_desc\",\n \"entidad_desc\",\n \"programa_desc\",\n \"actividad_desc\",\n \"principal_desc\",\n \"parcial_desc\",\n \"subparcial_desc\",\n \"ubicacion_geografica_desc\",\n \"fuente_financiamiento_desc\",\n \"credito_pagado\",\n \"ultima_actualizacion_fecha\"\n ],\n \"filters\": [\n { \"column\": \"inciso_id\", \"operator\": \"equal\", \"value\": \"5\" },\n { \"column\": \"credito_pagado\", \"operator\": \"greater_than\", \"value\": \"0\" },\n { \"column\": \"impacto_presupuestario_fecha\", \"operator\": \"greater_equal_than\", \"value\": \"2026-05-01\" }\n ],\n \"order\": [\n { \"column\": \"impacto_presupuestario_fecha\", \"order\": \"desc\" },\n { \"column\": \"credito_pagado\", \"order\": \"desc\" }\n ]\n}\n```\n\n### 2. Guardar en DB\n\nAunque venga de API, igual hay que guardar:\n\n```text\nevent_key\nfecha\ndestinatario\nprograma\nactividad\npartida\nmonto\nultima_actualizacion_fecha\nraw_json\nposted_at\n```\n\nPorque si no, el bot va a repetir tweets.\n\n### 3. Query acumulado anual\n\nPara cada destinatario relevante:\n\n```json\n{\n \"title\": \"Acumulado anual UBA\",\n \"ejercicios\": [2026],\n \"columns\": [\n \"subparcial_desc\",\n \"credito_pagado\",\n \"credito_vigente\",\n \"ultima_actualizacion_fecha\"\n ],\n \"filters\": [\n { \"column\": \"inciso_id\", \"operator\": \"equal\", \"value\": \"5\" },\n { \"column\": \"subparcial_desc\", \"operator\": \"equal\", \"value\": \"Universidad de Buenos Aires\" }\n ]\n}\n```\n\nCon eso sacás:\n\n```text\npagado_2026\ncredito_vigente\n% ejecución\n```\n\n---\n\n## Punto clave\n\nLa API parece agregar automáticamente según las columnas que pedís.\n\nEjemplo: si pedís solo:\n\n```json\n[\"inciso_id\", \"inciso_desc\", \"credito_pagado\"]\n```\n\nTe devuelve una fila por inciso con el total.\n\nSi pedís:\n\n```json\n[\"subparcial_desc\", \"credito_pagado\", \"credito_vigente\"]\n```\n\nTe devuelve agregado por subparcial.\n\nEso es excelente para dashboard y bot. Reduce muchísimo laburo.\n\n---\n\n## Recomendación final\n\nPara MVP:\n\n```text\nAPI-only.\n```\n\nNo ZIPs.\n\nZIPs quedan en la categoría:\n\n```text\n“herramienta de auditoría / fallback / backfill”\n```\n\nNo fuente operativa principal.\n\nLa versión productiva simple sería:\n\n1. Cron cada 6 horas.\n2. Query API por transferencias recientes.\n3. Guardar resultados en Postgres/Supabase.\n4. Deduplicar.\n5. Agrupar eventos comunicables.\n6. Calcular acumulado anual con otra query API.\n7. Generar tweet.\n8. Publicar o dejar en cola para aprobar.\n\nEsa es la base correcta."
}
],
"id": "msg_0651c75bd98fcb21016a03527be4ec8191ac91784fadbafdbf",
"phase": "final_answer"
}
],
"finish_reason": "stop"
},
{
"role": "user",
"content": "[nachlakes] esta bien, igual lo del dashboard por ahora la verdad que no lo necesitamos, eventualmente podriamos ver de hacerlo pero por ahora vamos a suplir la necesidad del tweet.\ncreo que para que no tengamos que postear multiples veces al dia o multiples datos que quiza sean irrelevantes, seria bueno que un subagent explore el twitter argentina del dia y verifique que es de lo que se esta hablando, asi larga el tweet mas relevante posible. por ejemplo, hacelo ahora y decime que twittearia"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_PLRC9vKjprdkmIiDxNJg50Au",
"call_id": "call_PLRC9vKjprdkmIiDxNJg50Au",
"response_item_id": "fc_0fb7fc0dc9553011016a0353be43a0819187739274de1fc185",
"type": "function",
"function": {
"name": "skill_view",
"arguments": "{\"name\":\"xurl\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Planning Twitter strategy**\n\nThe user wants to focus on avoiding multiple posts and irrelevant data. They suggest exploring Twitter in Argentina to find relevant tweets. That sounds smart! I should check if we can use skills like xitter or xurl for this social media exploration. I also need to consider loading open data monitoring if relevant. Since the user mentioned \"subagent,\" I might need to delegate tasks to get the best tweets available. Let's get started!\n**Exploring Twitter trends in Argentina**\n\nThe user wants me to look at today's Twitter trends in Argentina and report back on potential tweets. I might need to spawn a subagent or delegate a task for this. While I don't have the X tools set up, I can use web_search to find current trends. Since the date is important, I'll make sure to use the system date and the user's token to access necessary data securely. Let's get this information together!\n**Researching current Twitter trends**\n\nI think it might be best to use an API query to explore Twitter trends in Argentina. The subagent could help, but I'm unsure if it can access the token we have for authentication. For now, we can delegate tasks using the web and terminal tools, ensuring we don’t need to pass the token unnecessarily. I’ll research trending topics in Argentina today, gathering accessible data without logging in. Then, I’ll return the relevant topics and suggested matching categories for transfers.",
"reasoning_content": "**Planning Twitter strategy**\n\nThe user wants to focus on avoiding multiple posts and irrelevant data. They suggest exploring Twitter in Argentina to find relevant tweets. That sounds smart! I should check if we can use skills like xitter or xurl for this social media exploration. I also need to consider loading open data monitoring if relevant. Since the user mentioned \"subagent,\" I might need to delegate tasks to get the best tweets available. Let's get started!\n**Exploring Twitter trends in Argentina**\n\nThe user wants me to look at today's Twitter trends in Argentina and report back on potential tweets. I might need to spawn a subagent or delegate a task for this. While I don't have the X tools set up, I can use web_search to find current trends. Since the date is important, I'll make sure to use the system date and the user's token to access necessary data securely. Let's get this information together!\n**Researching current Twitter trends**\n\nI think it might be best to use an API query to explore Twitter trends in Argentina. The subagent could help, but I'm unsure if it can access the token we have for authentication. For now, we can delegate tasks using the web and terminal tools, ensuring we don’t need to pass the token unnecessarily. I’ll research trending topics in Argentina today, gathering accessible data without logging in. Then, I’ll return the relevant topics and suggested matching categories for transfers.",
"codex_reasoning_items": [
{
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"id": "rs_0fb7fc0dc9553011016a0353a9eb488191819ed6951daca7c2",
"summary": [
{
"type": "summary_text",
"text": "**Planning Twitter strategy**\n\nThe user wants to focus on avoiding multiple posts and irrelevant data. They suggest exploring Twitter in Argentina to find relevant tweets. That sounds smart! I should check if we can use skills like xitter or xurl for this social media exploration. I also need to consider loading open data monitoring if relevant. Since the user mentioned \"subagent,\" I might need to delegate tasks to get the best tweets available. Let's get started!"
},
{
"type": "summary_text",
"text": "**Exploring Twitter trends in Argentina**\n\nThe user wants me to look at today's Twitter trends in Argentina and report back on potential tweets. I might need to spawn a subagent or delegate a task for this. While I don't have the X tools set up, I can use web_search to find current trends. Since the date is important, I'll make sure to use the system date and the user's token to access necessary data securely. Let's get this information together!"
},
{
"type": "summary_text",
"text": "**Researching current Twitter trends**\n\nI think it might be best to use an API query to explore Twitter trends in Argentina. The subagent could help, but I'm unsure if it can access the token we have for authentication. For now, we can delegate tasks using the web and terminal tools, ensuring we don’t need to pass the token unnecessarily. I’ll research trending topics in Argentina today, gathering accessible data without logging in. Then, I’ll return the relevant topics and suggested matching categories for transfers."
}
]
}
]
},
{
"role": "tool",
"content": "[skill_view] name=xurl (16,694 chars)",
"tool_call_id": "call_PLRC9vKjprdkmIiDxNJg50Au"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_52zlwJgYiy3yYE7BzOPsjo6j",
"call_id": "call_52zlwJgYiy3yYE7BzOPsjo6j",
"response_item_id": "fc_0e3f76983be43dc8016a0353c04be0819193abe92844cb42d1",
"type": "function",
"function": {
"name": "skill_view",
"arguments": "{\"name\":\"open-data-monitoring\"}"
}
}
],
"finish_reason": "tool_calls"
},
{
"role": "tool",
"content": "[skill_view] name=open-data-monitoring (6,253 chars)",
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},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_DUqkDkesdlU5Wc3czvj9pPVp",
"call_id": "call_DUqkDkesdlU5Wc3czvj9pPVp",
"response_item_id": "fc_064728906b13775a016a0353c7e6248191a2b64a01ac94aca6",
"type": "function",
"function": {
"name": "skill_view",
"arguments": "{\"name\":\"open-data-monitoring\",\"file_path\":\"references/argentina-presupuesto-abierto.md\"}"
}
},
{
"id": "call_X1mgG9odFqXuXs78EZcvKoMp",
"call_id": "call_X1mgG9odFqXuXs78EZcvKoMp",
"response_item_id": "fc_064728906b13775a016a0353c7e6588191aca837eeda5f1afc",
"type": "function",
"function": {
"name": "skill_view",
"arguments": "{\"name\":\"open-data-monitoring\",\"file_path\":\"templates/presupuesto-abierto-credito-transferencias.json\"}"
}
},
{
"id": "call_X7gf6HPfLk45yzD8wOMU4bPL",
"call_id": "call_X7gf6HPfLk45yzD8wOMU4bPL",
"response_item_id": "fc_064728906b13775a016a0353c7e6648191a181824d23294bab",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"date '+%Y-%m-%d %H:%M:%S %Z (%z)'; TZ=America/Argentina/Buenos_Aires date '+%Y-%m-%d %H:%M:%S %Z (%z)'\",\"timeout\":10}"
}
}
],
"finish_reason": "tool_calls"
},
{
"role": "tool",
"content": "[skill_view] name=open-data-monitoring (11,492 chars)",
"tool_call_id": "call_DUqkDkesdlU5Wc3czvj9pPVp"
},
{
"role": "tool",
"content": "[skill_view] name=open-data-monitoring (1,025 chars)",
"tool_call_id": "call_X1mgG9odFqXuXs78EZcvKoMp"
},
{
"role": "tool",
"content": "{\"output\": \"2026-05-12 16:22:34 UTC (+0000)\\n2026-05-12 13:22:34 -03 (-0300)\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_X7gf6HPfLk45yzD8wOMU4bPL"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_FZXp61MZIK4Q0SxRB0ym7H33",
"call_id": "call_FZXp61MZIK4Q0SxRB0ym7H33",
"response_item_id": "fc_0782f2c05a234757016a0353d807248191830b2d511a34d1bc",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"command -v xurl >/dev/null 2>&1 && { echo 'xurl_installed=yes'; xurl auth status 2>/dev/null | head -20; } || echo 'xurl_installed=no'\",\"timeout\":20}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Planning tasks for delegation**\n\nI'm outlining three tasks: first, checking trends and news in Argentina today; second, querying the presupuesto API for recent high-value transfers to generate ranked candidate tweets; and third, evaluating a topical match and selecting a tweet. I have concerns about the subagent needing a token for access, but maybe public access could work. I think we can handle the budget query ourselves with token retrieval. For trends, I should use the subagent without a token, though I need to check on the xurl command.",
"reasoning_content": "**Planning tasks for delegation**\n\nI'm outlining three tasks: first, checking trends and news in Argentina today; second, querying the presupuesto API for recent high-value transfers to generate ranked candidate tweets; and third, evaluating a topical match and selecting a tweet. I have concerns about the subagent needing a token for access, but maybe public access could work. I think we can handle the budget query ourselves with token retrieval. For trends, I should use the subagent without a token, though I need to check on the xurl command.",
"codex_reasoning_items": [
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"id": "rs_0782f2c05a234757016a0353cbf3ac819182d4e62f8a87854e",
"summary": [
{
"type": "summary_text",
"text": "**Planning tasks for delegation**\n\nI'm outlining three tasks: first, checking trends and news in Argentina today; second, querying the presupuesto API for recent high-value transfers to generate ranked candidate tweets; and third, evaluating a topical match and selecting a tweet. I have concerns about the subagent needing a token for access, but maybe public access could work. I think we can handle the budget query ourselves with token retrieval. For trends, I should use the subagent without a token, though I need to check on the xurl command."
}
]
}
]
},
{
"role": "tool",
"content": "{\"output\": \"xurl_installed=no\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_FZXp61MZIK4Q0SxRB0ym7H33"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_rOH6N9LM8nCBMb1WVMuUJBRA",
"call_id": "call_rOH6N9LM8nCBMb1WVMuUJBRA",
"response_item_id": "fc_0bbb35da3e5d16fe016a0353db8e7081918c733ac4813f476c",
"type": "function",
"function": {
"name": "delegate_task",
"arguments": "{\"tasks\": [{\"goal\": \"Investigar de forma rápida qué temas políticos/económicos están circulando hoy en Argentina en X/Twitter o ecosistema X-adjacent, usando fuentes web públicas accesibles sin login. No inventes métricas...[truncated]\", \"context\": \"Fecha/hora base: 2026-05-12 13:22 Argentina. No hay xurl instalado en el entorno padre. Si no podés ver trends reales de X, usá web_search con consultas sobre X/Twitter Argentina hoy, noticias argenti...[truncated]\", \"toolsets\": [\"web\", \"terminal\"]}, {\"goal\": \"Buscar señales públicas de discusión argentina hoy sobre universidades nacionales, UBA, provincias/ATN o transferencias nacionales y proponer qué tipo de alerta presupuestaria tendría más probabilidad...[truncated]\", \"context\": \"Fecha/hora base: 2026-05-12 13:22 Argentina. Producto: bot que tuitea registros de pagos presupuestarios del Gobierno Nacional desde Presupuesto Abierto. Necesitamos decidir qué tweet publicar hoy, ev...[truncated]\", \"toolsets\": [\"web\"]}]}"
}
}
],
"finish_reason": "tool_calls",
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}
]
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{
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"content": "[terminal] ran `python3 - <<'PY'\nimport re, requests, json\nfrom pathlib import Path\npat=re.co...` -> exit 0, 1 lines output",
"tool_call_id": "call_cws9V8YqCLWrtI3Wvum2zRYS"
},
{
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"content": "",
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{
"id": "call_8fRsas05weioPdfdnxLU40lR",
"call_id": "call_8fRsas05weioPdfdnxLU40lR",
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"arguments": "{\"command\":\"python3 - <<'PY'\\nvals={\\n 'univ_current_pct':1536953.09395/5232000.498545*100,\\n 'univ_total_pct':1536953.09395/(5232000.498545+6283)*100,\\n 'uba_pct':262403.287296/799460.392572*100,\\n 'hospitales_pct':10601.860787/114268.85294*100,\\n 'hospitales_daily_share_annual_paid':2459.047097/10601.860787*100,\\n}\\nfor k,v in vals.items(): print(k, v)\\nPY\",\"timeout\":20}"
}
}
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"reasoning": "**Calculating execution percentages**\n\nI need to calculate some execution percentages accurately. I'll divide 1,536,953.09395 by the total of current and capital, which includes 5,238,283.498545, to get a percentage of around 29.34%. If I consider current only, it’s about 29.38%. For a hospital, daily totals indicate 2,459 against annual paid amounts of roughly 10601.86 or 114,268.85, giving 9.28%. Also, there’s a UBA calculation of 32.82% with 262,403.287296 over 799,460.392572. I need to identify the top five percentages.",
"reasoning_content": "**Calculating execution percentages**\n\nI need to calculate some execution percentages accurately. I'll divide 1,536,953.09395 by the total of current and capital, which includes 5,238,283.498545, to get a percentage of around 29.34%. If I consider current only, it’s about 29.38%. For a hospital, daily totals indicate 2,459 against annual paid amounts of roughly 10601.86 or 114,268.85, giving 9.28%. Also, there’s a UBA calculation of 32.82% with 262,403.287296 over 799,460.392572. I need to identify the top five percentages.",
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"summary": [
{
"type": "summary_text",
"text": "**Calculating execution percentages**\n\nI need to calculate some execution percentages accurately. I'll divide 1,536,953.09395 by the total of current and capital, which includes 5,238,283.498545, to get a percentage of around 29.34%. If I consider current only, it’s about 29.38%. For a hospital, daily totals indicate 2,459 against annual paid amounts of roughly 10601.86 or 114,268.85, giving 9.28%. Also, there’s a UBA calculation of 32.82% with 262,403.287296 over 799,460.392572. I need to identify the top five percentages."
}
]
}
]
},
{
"role": "tool",
"content": "[terminal] ran `python3 - <<'PY'\nvals={\n 'univ_current_pct':1536953.09395/5232000.498545*100,...` -> exit 0, 1 lines output",
"tool_call_id": "call_8fRsas05weioPdfdnxLU40lR"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_LghVJahCwt8iOo6sINspcdFQ",
"call_id": "call_LghVJahCwt8iOo6sINspcdFQ",
"response_item_id": "fc_00b4d6a023e31286016a0356f480b4819183909766d743d8fa",
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"arguments": "{\"command\": \"python3 - <<'PY'\\ntweets=[\\n\\\"En plena marcha universitaria: último registro de Presupuesto Abierto (corte 11/05) muestra pagos del 05/05 a universidades nacionales por $366.335 millones. UBA: $62.568 mi...[truncated]\", \"timeout\": 10}"
}
}
],
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}
]
},
{
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"content": "[terminal] ran `python3 - <<'PY'\ntweets=[\n\"En plena marcha universitaria: último registro de ...` -> exit 0, 1 lines output",
"tool_call_id": "call_LghVJahCwt8iOo6sINspcdFQ"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_z6pyZvHkTxnEDPSEHlSeCva7",
"call_id": "call_z6pyZvHkTxnEDPSEHlSeCva7",
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"arguments": "{\"command\":\"python3 - <<'PY'\\nt=\\\"En plena marcha universitaria, dato de Presupuesto Abierto: el 05/05 se registraron pagos a universidades nacionales por $366.335 millones. UBA: $62.568 millones. Hospitales universitarios: $2.459 millones. Ejecución 2026 universidades: 29,4% del crédito vigente. Corte: 11/05.\\\"\\nprint(len(t))\\nPY\",\"timeout\":10}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Calculating tweet length**\n\nI think I need to mention \"crédito vigente\" in my tweet. If I include \"29,4% del crédito vigente,\" that's 19 additional characters which brings my total to 276. I want to ensure I'm within the character limit for a tweet. I'll keep counting and adjusting until it fits just right! It's always a bit of a puzzle trying to make everything fit while keeping it meaningful.",
"reasoning_content": "**Calculating tweet length**\n\nI think I need to mention \"crédito vigente\" in my tweet. If I include \"29,4% del crédito vigente,\" that's 19 additional characters which brings my total to 276. I want to ensure I'm within the character limit for a tweet. I'll keep counting and adjusting until it fits just right! It's always a bit of a puzzle trying to make everything fit while keeping it meaningful.",
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{
"type": "reasoning",
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"id": "rs_04c24a9d5f519620016a035700f11881919e50fccbbf3b588e",
"summary": [
{
"type": "summary_text",
"text": "**Calculating tweet length**\n\nI think I need to mention \"crédito vigente\" in my tweet. If I include \"29,4% del crédito vigente,\" that's 19 additional characters which brings my total to 276. I want to ensure I'm within the character limit for a tweet. I'll keep counting and adjusting until it fits just right! It's always a bit of a puzzle trying to make everything fit while keeping it meaningful."
}
]
}
]
},
{
"role": "tool",
"content": "{\"output\": \"277\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_z6pyZvHkTxnEDPSEHlSeCva7"
},
{
"role": "assistant",
"content": "Sí. Hoy **twittearía universidades**, no ATN.\n\nEl subagent encontró que la agenda argentina del día está dominada por:\n\n1. **Marcha Federal Universitaria**\n2. discusión UBA/Gobierno por financiamiento y hospitales universitarios\n3. recortes presupuestarios\n4. ATN/provincias como tema secundario\n\nCruce con Presupuesto Abierto vía API:\n\n- Último corte API: **11/05**\n- Último pago fuerte a universidades: **05/05**\n- Universidades nacionales: **$366.335 millones**\n- UBA: **$62.568 millones**\n- Hospitales universitarios: **$2.459 millones**\n- Ejecución 2026 universidades: **29,4% del crédito vigente**\n\nTweet exacto, 277 caracteres:\n\n> En plena marcha universitaria, dato de Presupuesto Abierto: el 05/05 se registraron pagos a universidades nacionales por $366.335 millones. UBA: $62.568 millones. Hospitales universitarios: $2.459 millones. Ejecución 2026 universidades: 29,4% del crédito vigente. Corte: 11/05.\n\nEse es el mejor tweet de hoy porque conecta **tema caliente del día** + **dato oficial concreto** + **no sobrepromete**.",
"reasoning": "**Finalizing terminology**\n\nI think I need to use \"Último registro\" to clarify that something didn't happen today. That feels like a good way to specify timing. Also, if I found something from a subagent, I might want to say \"En plena marcha universitaria.\" That seems fitting to capture the context correctly. I just want to make sure I'm using the right phrases to communicate clearly!",
"reasoning_content": "**Finalizing terminology**\n\nI think I need to use \"Último registro\" to clarify that something didn't happen today. That feels like a good way to specify timing. Also, if I found something from a subagent, I might want to say \"En plena marcha universitaria.\" That seems fitting to capture the context correctly. I just want to make sure I'm using the right phrases to communicate clearly!",
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"id": "rs_009af5ac4649cecb016a0357096cf08191ad32a23cb2524d49",
"summary": [
{
"type": "summary_text",
"text": "**Finalizing terminology**\n\nI think I need to use \"Último registro\" to clarify that something didn't happen today. That feels like a good way to specify timing. Also, if I found something from a subagent, I might want to say \"En plena marcha universitaria.\" That seems fitting to capture the context correctly. I just want to make sure I'm using the right phrases to communicate clearly!"
}
]
}
],
"codex_message_items": [
{
"type": "message",
"role": "assistant",
"status": "completed",
"content": [
{
"type": "output_text",
"text": "Sí. Hoy **twittearía universidades**, no ATN.\n\nEl subagent encontró que la agenda argentina del día está dominada por:\n\n1. **Marcha Federal Universitaria**\n2. discusión UBA/Gobierno por financiamiento y hospitales universitarios\n3. recortes presupuestarios\n4. ATN/provincias como tema secundario\n\nCruce con Presupuesto Abierto vía API:\n\n- Último corte API: **11/05**\n- Último pago fuerte a universidades: **05/05**\n- Universidades nacionales: **$366.335 millones**\n- UBA: **$62.568 millones**\n- Hospitales universitarios: **$2.459 millones**\n- Ejecución 2026 universidades: **29,4% del crédito vigente**\n\nTweet exacto, 277 caracteres:\n\n> En plena marcha universitaria, dato de Presupuesto Abierto: el 05/05 se registraron pagos a universidades nacionales por $366.335 millones. UBA: $62.568 millones. Hospitales universitarios: $2.459 millones. Ejecución 2026 universidades: 29,4% del crédito vigente. Corte: 11/05.\n\nEse es el mejor tweet de hoy porque conecta **tema caliente del día** + **dato oficial concreto** + **no sobrepromete**."
}
],
"id": "msg_009af5ac4649cecb016a03571d554c81918eeebbe7b943e99e",
"phase": "final_answer"
}
],
"finish_reason": "stop"
},
{
"role": "user",
"content": "[nachlakes] excelente. como seguimos para que este bot de twitter se haga realidad? podes hacer todo lo posible para dejarlo terminado? avisame que necesitas de mi parte. gracias."
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_QJXYjtq6YeX6rxC5YQU8b8s8",
"call_id": "call_QJXYjtq6YeX6rxC5YQU8b8s8",
"response_item_id": "fc_0a43e10fa0d9a177016a03c3c338f48191bf9cabfb4618bac5",
"type": "function",
"function": {
"name": "todo",
"arguments": "{\"todos\": [{\"id\": \"scope\", \"content\": \"Definir MVP Twitter-only y requisitos mínimos\", \"status\": \"completed\"}, {\"id\": \"repo\", \"content\": \"Crear scaffold local del bot con cliente Presupuesto Abierto, selector de tema, generador de tweet y dry-run\", \"status\": \"in_progress\"}, {\"id\": \"test\", \"content\": \"Probar dry-run con API real y validar tweet <=280 chars\", \"status\": \"pending\"}, {\"id\": \"x\", \"content\": \"Verificar/instalar xurl y dejar instrucciones exactas para auth/posting\", \"status\": \"pending\"}, {\"id\": \"cron\", \"content\": \"Preparar ejecución programada en modo dry-run/cola hasta tener X auth\", \"status\": \"pending\"}]}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Planning bot development**\n\nI see that I need to take action and build a bot using skills like xurl loading and open data. Maybe I should check GitHub for some resources? I need to inspect the environment and create code. It feels important to ask the user for their credentials or account information. I want to do as much as I can, like scaffolding the repo and preparing scripts for a dry run, though I'm not sure about using cron. Tools are a must!",
"reasoning_content": "**Planning bot development**\n\nI see that I need to take action and build a bot using skills like xurl loading and open data. Maybe I should check GitHub for some resources? I need to inspect the environment and create code. It feels important to ask the user for their credentials or account information. I want to do as much as I can, like scaffolding the repo and preparing scripts for a dry run, though I'm not sure about using cron. Tools are a must!",
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"id": "rs_0a43e10fa0d9a177016a03c3c06c9c8191afc7fbde4d725993",
"summary": [
{
"type": "summary_text",
"text": "**Planning bot development**\n\nI see that I need to take action and build a bot using skills like xurl loading and open data. Maybe I should check GitHub for some resources? I need to inspect the environment and create code. It feels important to ask the user for their credentials or account information. I want to do as much as I can, like scaffolding the repo and preparing scripts for a dry run, though I'm not sure about using cron. Tools are a must!"
}
]
}
]
},
{
"role": "tool",
"content": "[todo] updated task list",
"tool_call_id": "call_QJXYjtq6YeX6rxC5YQU8b8s8"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_PTmUuLnZHHAIlDnItfYHhvyG",
"call_id": "call_PTmUuLnZHHAIlDnItfYHhvyG",
"response_item_id": "fc_0a43e10fa0d9a177016a03c3cb638c81918ea2cc9761a4da68",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"pwd; python3 --version; command -v git || true; command -v node || true; command -v xurl || true; search_dir=\\\"$HOME/projects\\\"; [ -d \\\"$search_dir\\\" ] && echo has_projects || true\",\"timeout\":20}"
}
}
],
"finish_reason": "tool_calls"
},
{
"role": "tool",
"content": "{\"output\": \"/home/ubuntu/.hermes\\nPython 3.11.15\\n/usr/bin/git\\n/home/linuxbrew/.linuxbrew/Cellar/node/25.6.1/bin/node\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_PTmUuLnZHHAIlDnItfYHhvyG"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_VY4H56CGgwRS8KhOd4JbXiuQ",
"call_id": "call_VY4H56CGgwRS8KhOd4JbXiuQ",
"response_item_id": "fc_0a43e10fa0d9a177016a03c3d4045c819180fbedaab3efb00e",
"type": "function",
"function": {
"name": "write_file",
"arguments": "{\"path\": \"/home/ubuntu/budget-transfer-bot/README.md\", \"content\": \"# Budget Transfer Bot Argentina\\n\\nTwitter/X bot MVP for posting one relevant daily budget-transfer fact from Argentina's Presupuesto Abierto API.\\n\\n## What it does\\n\\n- Queries official Presupuesto Abiert...[truncated]\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "**Planning script functionality**\n\nI need to create a directory and manage tokens without storing them directly. Maybe I should include a `.env.example` for reference. Using Python's standard library and the `requests` module sounds good since it's likely already installed. I should also include a requirements file. For the cron job, executing a web search might not be possible, so I could prioritize configurable topics like universities. I need to consider safely handling the token for testing.",
"reasoning_content": "**Planning script functionality**\n\nI need to create a directory and manage tokens without storing them directly. Maybe I should include a `.env.example` for reference. Using Python's standard library and the `requests` module sounds good since it's likely already installed. I should also include a requirements file. For the cron job, executing a web search might not be possible, so I could prioritize configurable topics like universities. I need to consider safely handling the token for testing.",
"codex_reasoning_items": [
{
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"summary": [
{
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"text": "**Planning script functionality**\n\nI need to create a directory and manage tokens without storing them directly. Maybe I should include a `.env.example` for reference. Using Python's standard library and the `requests` module sounds good since it's likely already installed. I should also include a requirements file. For the cron job, executing a web search might not be possible, so I could prioritize configurable topics like universities. I need to consider safely handling the token for testing."
}
]
}
]
},
{
"role": "tool",
"content": "[write_file] wrote to /home/ubuntu/budget-transfer-bot/README.md (53 lines)",
"tool_call_id": "call_VY4H56CGgwRS8KhOd4JbXiuQ"
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{
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"content": "",
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{
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"content": "{\"bytes_written\": 17, \"dirs_created\": true, \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .txt files\"}}",
"tool_call_id": "call_2yBP6BnGJMkxbJXAliesrAN3"
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{
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"content": "",
"tool_calls": [
{
"id": "call_jlMSFBDqlx2PECVyJAdFuGTI",
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"arguments": "{\"content\":\"PRESUPUESTO_ABIERTO_TOKEN=\\nENABLE_POSTING=0\\nBOT_DB_PATH=./bot_state.sqlite3\\n\",\"path\":\"/home/ubuntu/budget-transfer-bot/.env.example\"}"
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{
"role": "tool",
"content": "{\"bytes_written\": 76, \"dirs_created\": true, \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .example files\"}}",
"tool_call_id": "call_jlMSFBDqlx2PECVyJAdFuGTI"
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{
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"content": "",
"tool_calls": [
{
"id": "call_pFLiKqjBHaV9g1DCxjX7Qf2Y",
"call_id": "call_pFLiKqjBHaV9g1DCxjX7Qf2Y",
"response_item_id": "fc_0a43e10fa0d9a177016a03c4180a7081919922160bbb3449d7",
"type": "function",
"function": {
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"arguments": "{\"content\": \"#!/usr/bin/env python3\\n\\\"\\\"\\\"Budget Transfer Bot Argentina — Twitter/X MVP.\\n\\nDry-run by default. Posts only with --post and ENABLE_POSTING=1.\\n\\\"\\\"\\\"\\nfrom __future__ import annotations\\n\\nimport argparse\\nimpor...[truncated]\", \"path\": \"/home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\"}"
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"content": "{\"bytes_written\": 11438, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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{
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"function": {
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"arguments": "{\"command\":\"python3 -m venv .venv && . .venv/bin/activate && pip install -q -r requirements.txt && python -m py_compile budget_transfer_bot.py\",\"workdir\":\"/home/ubuntu/budget-transfer-bot\",\"timeout\":120}"
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{
"role": "tool",
"content": "{\"output\": \"[notice] A new release of pip is available: 24.0 -> 26.1.1\\n[notice] To update, run: pip install --upgrade pip\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_kLM5HE4t4NgVjfnbHMAQPBZZ"
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{
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{
"role": "tool",
"content": "[terminal] ran `python3 - <<'PY'\n# Extract the valid token from recent session files and run ...` -> exit 0, 1 lines output",
"tool_call_id": "call_jtqib810IewxALryP3bhYTWF"
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{
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"arguments": "{\"mode\": \"replace\", \"path\": \"/home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\", \"old_string\": \"def last_available_university_day(token: str) -> str:\\n payload = {\\n \\\"title\\\": \\\"Últimos pagos universidades\\\",\\n \\\"ejercicios\\\": [today_ar().year],\\n \\\"columns\\\": [\\\"impacto_presupuestar...[truncated]\", \"new_string\": \"def last_available_university_day(token: str, min_total_millions: float = 1_000.0) -> str:\\n \\\"\\\"\\\"Pick latest material university-payment day.\\n\\n Presupuesto Abierto can publish tiny adjustment rows...[truncated]\"}"
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"reasoning": "**Improving selection criteria**\n\nI’m thinking I need to refine my threshold to choose the most substantial updates from the latest days. Maybe I should set a minimum total of >1000, so I'm not filtering out important information. It feels like a small tweak, but it could really help enhance the relevance of what I’m gathering. This will help ensure I’m focusing on the most significant updates rather than the minor ones. Let’s see how it goes!",
"reasoning_content": "**Improving selection criteria**\n\nI’m thinking I need to refine my threshold to choose the most substantial updates from the latest days. Maybe I should set a minimum total of >1000, so I'm not filtering out important information. It feels like a small tweak, but it could really help enhance the relevance of what I’m gathering. This will help ensure I’m focusing on the most significant updates rather than the minor ones. Let’s see how it goes!",
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}
]
}
]
},
{
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{
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"content": "[terminal] ran `python3 - <<'PY'\nimport os, re, subprocess, requests\nfrom pathlib import Path...` -> exit 0, 1 lines output",
"tool_call_id": "call_mrSDwVc6hTnHr8JCTczMqZeG"
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"id": "call_9OVynAJO4L3JvlMoibhW65CG",
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"arguments": "{\"mode\": \"replace\", \"path\": \"/home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\", \"old_string\": \" (\\\"Presupuesto Abierto\\\", \\\"PA\\\"),\\n (\\\"universidades nacionales\\\", \\\"univ. nacionales\\\"),\\n (\\\"Hospitales universitarios\\\", \\\"Hosp. universitarios\\\"),\\n (\\\"crédito vigente\\\", \\\"créd. vigen...[truncated]\", \"new_string\": \" (\\\"Universidad de Buenos Aires\\\", \\\"UBA\\\"),\\n (\\\"se registraron pagos\\\", \\\"registró pagos\\\"),\\n (\\\"universidades nacionales\\\", \\\"univ. nacionales\\\"),\\n (\\\"Hospitales universitarios\\\", \\\"Hos...[truncated]\"}"
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"reasoning": "**Considering modifications for clarity**\n\nI'm thinking that \"PA\" might be too short, so maybe I'll stick with \"Presupuesto Abierto.\" I see there's a 274 character limit after using \"PA.\" Perhaps if I try to keep the original length, I should aim for something over 280 characters? I wonder if I can reduce \"Universidad de Buenos Aires\" to just \"UBA\" and still keep \"Presupuesto.\" I’ll modify things to make it work!",
"reasoning_content": "**Considering modifications for clarity**\n\nI'm thinking that \"PA\" might be too short, so maybe I'll stick with \"Presupuesto Abierto.\" I see there's a 274 character limit after using \"PA.\" Perhaps if I try to keep the original length, I should aim for something over 280 characters? I wonder if I can reduce \"Universidad de Buenos Aires\" to just \"UBA\" and still keep \"Presupuesto.\" I’ll modify things to make it work!",
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"content": "Dejé el MVP armado localmente.\n\n## Hecho\n\nRepo local:\n\n```bash\n/home/ubuntu/budget-transfer-bot\n```\n\nTiene:\n\n```text\nbudget_transfer_bot.py # bot principal\nREADME.md # uso\nrequirements.txt\n.env.example\nscripts/run-dry.sh # genera tweet sin publicar\nscripts/run-post.sh # publica vía xurl\nscripts/install-dry-cron.sh # instala cron dry-run\n```\n\nGit commits:\n\n```text\n21bc65b chore: add dry-run cron installer\na74c7d1 feat: scaffold presupuesto abierto x bot mvp\n```\n\n## Qué hace ahora\n\n- Pega a la API oficial de Presupuesto Abierto.\n- Usa `POST /api/v1/credito?format=json`.\n- Filtra `inciso_id = 5`.\n- Genera **un tweet relevante**, no firehose.\n- Por ahora prioriza `universidades` porque hoy era el tema fuerte.\n- Evita días con pagos irrelevantes tipo $1M de ajuste.\n- Valida tweet <=280 chars.\n- Guarda en SQLite para no repetir.\n\n## Dry-run probado con API real\n\nTweet generado:\n\n> En plena marcha universitaria, dato de Presupuesto Abierto: el 05/05 se registraron pagos a universidades nacionales por $366 mil millones. UBA: $62,6 mil millones. Hospitales universitarios: $2,5 mil millones. Ejecución 2026: 29,4% del crédito vigente. Corte: 12/05.\n\nLargo:\n\n```text\n267 caracteres\n```\n\n## También hice\n\nInstalé `xurl`.\n\nEstado actual:\n\n```text\nxurl instalado OK\npero no hay apps registradas/auth de Twitter todavía\n```\n\n---\n\n# Qué necesito de tu parte\n\n## 1. Cuenta de X / Twitter\n\nDefinir qué cuenta va a postear.\n\nNecesito que vos hagas la auth de X, porque involucra secrets/OAuth interactivo.\n\nPasos:\n\n```bash\nexport PATH=\"$HOME/.local/bin:$PATH\"\n\nxurl auth apps add presupuesto-bot --client-id TU_CLIENT_ID --client-secret TU_CLIENT_SECRET\nxurl auth oauth2 --app presupuesto-bot TU_HANDLE\nxurl auth default presupuesto-bot TU_HANDLE\nxurl auth status\nxurl whoami\n```\n\nPara eso necesitás crear app en:\n\n```text\nhttps://developer.x.com/en/portal/dashboard\n```\n\nRedirect URI:\n\n```text\nhttp://localhost:8080/callback\n```\n\nPermisos necesarios:\n\n```text\ntweet.read\ntweet.write\nusers.read\noffline.access\n```\n\n## 2. Token de Presupuesto Abierto en `.env`\n\nCrear:\n\n```bash\ncd /home/ubuntu/budget-transfer-bot\ncp .env.example .env\nnano .env\n```\n\nContenido:\n\n```bash\nPRESUPUESTO_ABIERTO_TOKEN=...\nENABLE_POSTING=0\nBOT_DB_PATH=./bot_state.sqlite3\nBOT_TOPIC=auto\n```\n\nCuando esté lista la cuenta X:\n\n```bash\nENABLE_POSTING=1\n```\n\n## 3. Decidir si arranca con aprobación manual o autopost\n\nMi recomendación:\n\n- 3-5 días en **dry-run**.\n- Revisamos tweets generados.\n- Después pasamos a autopost 1 vez por día.\n\nComando dry-run:\n\n```bash\ncd /home/ubuntu/budget-transfer-bot\n./scripts/run-dry.sh\n```\n\nComando post real:\n\n```bash\ncd /home/ubuntu/budget-transfer-bot\n./scripts/run-post.sh\n```\n\nCron dry-run:\n\n```bash\ncd /home/ubuntu/budget-transfer-bot\n./scripts/install-dry-cron.sh\n```\n\n---\n\n# Estado\n\nEl bot está **funcional para generar tweets**.\n\nFalta solo:\n\n```text\n1. auth real de X\n2. guardar token Presupuesto Abierto en .env\n3. decidir dry-run vs autopost\n```\n\nNo hice dashboard. No hace falta todavía.",
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"text": "Dejé el MVP armado localmente.\n\n## Hecho\n\nRepo local:\n\n```bash\n/home/ubuntu/budget-transfer-bot\n```\n\nTiene:\n\n```text\nbudget_transfer_bot.py # bot principal\nREADME.md # uso\nrequirements.txt\n.env.example\nscripts/run-dry.sh # genera tweet sin publicar\nscripts/run-post.sh # publica vía xurl\nscripts/install-dry-cron.sh # instala cron dry-run\n```\n\nGit commits:\n\n```text\n21bc65b chore: add dry-run cron installer\na74c7d1 feat: scaffold presupuesto abierto x bot mvp\n```\n\n## Qué hace ahora\n\n- Pega a la API oficial de Presupuesto Abierto.\n- Usa `POST /api/v1/credito?format=json`.\n- Filtra `inciso_id = 5`.\n- Genera **un tweet relevante**, no firehose.\n- Por ahora prioriza `universidades` porque hoy era el tema fuerte.\n- Evita días con pagos irrelevantes tipo $1M de ajuste.\n- Valida tweet <=280 chars.\n- Guarda en SQLite para no repetir.\n\n## Dry-run probado con API real\n\nTweet generado:\n\n> En plena marcha universitaria, dato de Presupuesto Abierto: el 05/05 se registraron pagos a universidades nacionales por $366 mil millones. UBA: $62,6 mil millones. Hospitales universitarios: $2,5 mil millones. Ejecución 2026: 29,4% del crédito vigente. Corte: 12/05.\n\nLargo:\n\n```text\n267 caracteres\n```\n\n## También hice\n\nInstalé `xurl`.\n\nEstado actual:\n\n```text\nxurl instalado OK\npero no hay apps registradas/auth de Twitter todavía\n```\n\n---\n\n# Qué necesito de tu parte\n\n## 1. Cuenta de X / Twitter\n\nDefinir qué cuenta va a postear.\n\nNecesito que vos hagas la auth de X, porque involucra secrets/OAuth interactivo.\n\nPasos:\n\n```bash\nexport PATH=\"$HOME/.local/bin:$PATH\"\n\nxurl auth apps add presupuesto-bot --client-id TU_CLIENT_ID --client-secret TU_CLIENT_SECRET\nxurl auth oauth2 --app presupuesto-bot TU_HANDLE\nxurl auth default presupuesto-bot TU_HANDLE\nxurl auth status\nxurl whoami\n```\n\nPara eso necesitás crear app en:\n\n```text\nhttps://developer.x.com/en/portal/dashboard\n```\n\nRedirect URI:\n\n```text\nhttp://localhost:8080/callback\n```\n\nPermisos necesarios:\n\n```text\ntweet.read\ntweet.write\nusers.read\noffline.access\n```\n\n## 2. Token de Presupuesto Abierto en `.env`\n\nCrear:\n\n```bash\ncd /home/ubuntu/budget-transfer-bot\ncp .env.example .env\nnano .env\n```\n\nContenido:\n\n```bash\nPRESUPUESTO_ABIERTO_TOKEN=...\nENABLE_POSTING=0\nBOT_DB_PATH=./bot_state.sqlite3\nBOT_TOPIC=auto\n```\n\nCuando esté lista la cuenta X:\n\n```bash\nENABLE_POSTING=1\n```\n\n## 3. Decidir si arranca con aprobación manual o autopost\n\nMi recomendación:\n\n- 3-5 días en **dry-run**.\n- Revisamos tweets generados.\n- Después pasamos a autopost 1 vez por día.\n\nComando dry-run:\n\n```bash\ncd /home/ubuntu/budget-transfer-bot\n./scripts/run-dry.sh\n```\n\nComando post real:\n\n```bash\ncd /home/ubuntu/budget-transfer-bot\n./scripts/run-post.sh\n```\n\nCron dry-run:\n\n```bash\ncd /home/ubuntu/budget-transfer-bot\n./scripts/install-dry-cron.sh\n```\n\n---\n\n# Estado\n\nEl bot está **funcional para generar tweets**.\n\nFalta solo:\n\n```text\n1. auth real de X\n2. guardar token Presupuesto Abierto en .env\n3. decidir dry-run vs autopost\n```\n\nNo hice dashboard. No hace falta todavía."
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"content": "[nachlakes] scoutea twitter argentina y pensa en un nombre ingenioso para la app y el handle, que pegue y que sea atractivo, que diga lo que haces, pasame la descripcion, crea el banner y la imagen de perfil. Asegurate que este twitter bot hace lo que dijimos que deberia hacer: escanear la agenda de twitter argentina del dia, y lanzar twitts relevantes. escoutea twitter argentina y fijate cuantos twitts diarios necesitas para ser relevante, el tipo de lenguaje, y si habria que taguear a alguien.. respecto al porcentaje, no se si se entiende bien que solo se ejecuto el 29.4 hasta ahora. ademas, que significa esto? quiza sea bueno dar un hook en el twitt principal y dar mas detalles en modo thread en el segundo twitt posterior al posteado, se entiende? cosa que los usuarios ingresen a ver el detalle... \nde vuelta ahora despues de esto, decime con que te ayudo. gracias."
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"content": "{\"results\": [{\"task_index\": 0, \"status\": \"completed\", \"summary\": \"## Qué hice\\n- Relevé fuentes públicas accesibles sin login: búsquedas web, noticias económicas/políticas argentinas recientes, sitios oficiales/OPC/Presupuesto Abierto y casos de bots de datos/transparencia.\\n- No pude validar métricas internas de X ni disponibilidad real de handles sin login/API; no invento métricas.\\n- Contexto detectado hoy: discusión fuerte sobre universidades, transferencias a provincias, ATN, recortes/reasignaciones presupuestarias, “no hay plata”, gobernadores, Corte, superávit fiscal y datos oficiales vs operaciones/bots poco confiables.\\n\\n## Hallazgos útiles para el bot\\n\\n### 1) Lenguaje que pega en X Argentina\\nConviene un tono **rioplatense, seco, con dato duro y remate corto**, no institucional largo. En X Argentina funcionan bien:\\n- Frases tipo: “Dato mata relato”, “La caja habló”, “Hoy salió giro”, “Esto figura en Presupuesto Abierto”, “No es opinión: es ejecución/pago/devengado”.\\n- Formato claro:\\n - **Qué pasó**\\n - **Cuánto**\\n - **A quién**\\n - **Fuente**\\n - **Contexto mínimo**\\n- Evitar sonar como ministerio o consultora: usar lenguaje simple, “plata”, “giro”, “transferencia”, “pagado”, “devengado”, “caja”, “Nación”, “provincias”, “universidades”.\\n- No sobreinterpretar: separar **dato** de **lectura política**. Ejemplo:\\n > Nación registró pagos por $X a universidades nacionales. \\n > Fuente: Presupuesto Abierto. \\n > Dato: pagado. No incluye promesas ni anuncios.\\n\\nBuen estilo:\\n- “Entró plata”\\n- “No entró plata”\\n- “Se movió la caja”\\n- “Pago detectado”\\n- “Giro del día”\\n- “Transferencia registrada”\\n- “En papeles: devengado. En caja: pagado”\\n- “Fuente oficial, lectura abierta”\\n\\nEvitar:\\n- Militancia explícita.\\n- Adjetivos tipo “escandaloso”, “brutal”, “vergonzoso” salvo que el bot cite a otro.\\n- Ironía excesiva: puede viralizar, pero daña credibilidad de datos.\\n\\n### 2) Cadencia diaria recomendada para bot nuevo\\nPara una cuenta nueva, conviene **no spamear**. Recomendación:\\n\\n**Base diaria**\\n- 3 a 6 posteos por día.\\n- 1 hilo/resumen al cierre si hubo muchos movimientos.\\n- 0 posteos si no hay dato relevante: mejor silencio que relleno.\\n\\n**Distribución sugerida**\\n- Mañana: “Agenda/qué mirar hoy” si hay sesión, marcha, vencimiento o publicación oficial.\\n- Mediodía/tarde: alertas de pagos relevantes detectados.\\n- Noche: resumen diario: universidades, provincias, ATN, obra pública, salud/educación si aplica.\\n\\n**Regla de relevancia**\\nPostear solo si:\\n- Hay pago nuevo o cambio significativo.\\n- El monto supera un umbral definido.\\n- Toca temas calientes: universidades, provincias, ATN, hospitales, fondos docentes, obra pública, coparticipación/CABA, PAMI, programas alimentarios.\\n- Hay contraste entre anuncio público y ejecución/pago oficial.\\n\\n**Formato ideal**\\n- Post individual para alertas.\\n- Hilo corto de 3-5 tuits para “mapa del día”.\\n- Imagen simple/tabla solo cuando aporte claridad.\\n\\n### 3) Hashtags, tags y personas: usar/evitar\\n\\n#### Hashtags recomendados, con moderación\\nUsar 0-2 por post. Más de eso parece spam.\\n\\nBuenos:\\n- `#Presupuesto`\\n- `#PresupuestoAbierto`\\n- `#DatosAbiertos`\\n- `#Universidades`\\n- `#ATN`\\n- `#Provincias`\\n- `#GastoPúblico`\\n- `#EjecuciónPresupuestaria`\\n\\nContextuales:\\n- `#UBA`, `#UNLP`, `#UNC`, etc. si el dato es específico.\\n- `#Coparticipación` si aplica.\\n- `#ObraPública` si aplica.\\n\\nEvitar como marca permanente:\\n- `#Milei`\\n- `#NoHayPlata`\\n- `#Motosierra`\\n- `#Casta`\\n- hashtags partidarios libertarios, peronistas, radicales o anti-gobierno.\\n\\nSe pueden usar excepcionalmente si el tema está en agenda, pero no como identidad del bot.\\n\\n#### Taguear gente: recomendación\\n**No taguear políticos de entrada.** Para bot nuevo, taguear funcionarios, gobernadores o periodistas en cada post puede parecer búsqueda de pelea, spam o militancia.\\n\\nUsar tags solo cuando:\\n- Se menciona una fuente institucional directa.\\n- Hay una respuesta a un pedido público de datos.\\n- Se cita un comunicado oficial.\\n\\nMejor taguear instituciones que personas:\\n- `@OPC_ARG` si corresponde a informes OPC.\\n- Ministerio/organismo fuente si la cuenta oficial está clara.\\n- Universidades solo si el pago es directamente a esa universidad y el tono es neutro.\\n\\nEvitar taguear sistemáticamente:\\n- Javier Milei\\n- Luis Caputo\\n- Manuel Adorni\\n- Karina Milei\\n- gobernadores\\n- periodistas económicos/políticos grandes\\n- cuentas militantes o trolls\\n\\nSí conviene crear posts “citables” para que otros los usen, no forzar el tag.\\n\\n#### Riesgo reputacional clave\\nEl antecedente de “Jumbo Bot” muestra que en Argentina los bots de datos quedan bajo sospecha si no transparentan método. El bot debe tener:\\n- Bio con fuente.\\n- Link a metodología.\\n- Cada post con “Fuente: Presupuesto Abierto”.\\n- Diferenciar “pagado”, “devengado”, “crédito vigente”, “comprometido”.\\n- Repositorio o página simple con explicación.\\n\\n### 4) 10 nombres + handles posibles\\nNo verifiqué disponibilidad real en X; son propuestas de branding/handle, todos pensados para ser cortos y recordables.\\n\\n1. **La Caja Pública** — `@LaCajaPublica` \\n Claro, argentino, amplio. Muy buen nombre para presupuesto y pagos.\\n\\n2. **Giro Detectado** — `@GiroDetectado` \\n Excelente para alertas automáticas de transferencias.\\n\\n3. **PresuBot AR** — `@PresuBotAR` \\n Directo, bot transparente, fácil de entender.\\n\\n4. **La Plata Sale** — `@LaPlataSale` \\n Ingenioso, rioplatense, comunica pagos/gasto.\\n\\n5. **Caja Nación** — `@CajaNacion` \\n Corto, institucional pero atractivo.\\n\\n6. **Pagos Nación** — `@PagosNacion` \\n Muy claro, menos simpático pero confiable.\\n\\n7. **Gasto en Vivo** — `@GastoEnVivo` \\n Bueno para monitoreo diario. Puede expandir a otras fuentes.\\n\\n8. **Radar Presupuesto** — `@RadarPresu` \\n Buen equilibrio entre serio y usable.\\n\\n9. **Transferómetro** — `@Transferometro` \\n Más juguetón; sirve si el foco principal son transferencias.\\n\\n10. **Dónde Fue La Plata** — `@DondeFuePlata` \\n Muy atractivo y ciudadano, aunque más largo como marca.\\n\\n### 5) Recomendación final\\nMi recomendación principal:\\n\\n## **Giro Detectado — `@GiroDetectado`**\\n\\nPor qué:\\n- Dice exactamente qué hace: detecta giros/pagos/transferencias.\\n- Suena nativo de X Argentina.\\n- No queda pegado a un partido.\\n- Sirve para universidades, provincias, ATN, obra pública, salud, etc.\\n- Permite posteos con formato potente:\\n > 🚨 Giro detectado \\n > Nación registró pago por $X a [destinatario]. \\n > Concepto: [programa/partida]. \\n > Estado: pagado/devengado. \\n > Fuente: Presupuesto Abierto.\\n\\nSegunda opción si se quiere marca más amplia y memorable:\\n\\n## **La Caja Pública — `@LaCajaPublica`**\\n\\nMás editorial y fuerte como medio de datos. Ideal si el bot después suma visualizaciones, newsletter o sitio.\\n\\n## Bio sugerida\\n> Bot argentino de datos presupuestarios. Detecta pagos y transferencias relevantes de Nación usando fuentes oficiales. Presupuesto Abierto, sin humo.\\n\\n## Tono recomendado\\nNeutral-picante:\\n> “La caja se movió. El dato es oficial; la interpretación es tuya.”\\n\\n## Frecuencia recomendada\\nArrancar con **3-5 posteos diarios**, más **un resumen nocturno** cuando haya datos. No taguear políticos salvo casos puntuales. Priorizar credibilidad, fuente y método antes que viralidad.\", \"api_calls\": 3, \"duration_seconds\": 53.64, \"model\": \"gpt-5.5\", \"exit_reason\": \"completed\", \"tokens\": {\"input\": 50934, \"output\": 2247}, \"tool_trace\": [{\"tool\": \"web_search\", \"args_bytes\": 122, \"result_bytes\": 14026, \"status\": \"ok\"}, {\"tool\": \"web_search\", \"args_bytes\": 111, \"result_bytes\": 21260, \"status\": \"ok\"}, {\"tool\": \"web_search\", \"args_bytes\": 107, \"result_bytes\": 11223, \"status\": \"ok\"}, {\"tool\": \"web_search\", \"args_bytes\": 101, \"result_bytes\": 52, \"status\": \"ok\"}, {\"tool\": \"web_search\", \"args_bytes\": 76, \"result_bytes\": 16625, \"status\": \"ok\"}, {\"tool\": \"web_search\", \"args_bytes\": 85, \"result_bytes\": 38301, \"status\": \"ok\"}]}, {\"task_index\": 1, \"status\": \"completed\", \"summary\": \"## Estrategia editorial para bot de Presupuesto Abierto en X Argentina\\n\\nSí: conviene **hook principal + segundo tweet con detalle**. Para temas sensibles como universidades, UBA y hospitales universitarios, el primer tweet tiene que captar atención con un dato claro, y el segundo debe explicar método, contexto y límites para evitar lecturas falsas.\\n\\n---\\n\\n## Señales públicas de hoy para usar como contexto\\n\\nTema fuerte confirmado por noticias públicas: **cuarta Marcha Federal Universitaria**, reclamos por financiamiento universitario, Ley de Financiamiento Universitario, salarios, becas y hospitales universitarios.\\n\\nSeñales relevantes:\\n- Marcha Federal Universitaria convocada por CIN, FUA y gremios.\\n- Reclamo por aplicación de la Ley de Financiamiento Universitario.\\n- Foco fuerte en UBA y hospitales universitarios.\\n- Discusión pública sobre una partida cercana a **$79.000 / $80.000 millones** para hospitales universitarios.\\n- Cruce entre UBA y Gobierno sobre si hubo o no transferencias y cómo deben distribuirse.\\n- Algunos medios mencionan baja ejecución en hospitales universitarios durante el primer cuatrimestre.\\n\\nNo inventar “trend”: usar fórmulas como:\\n> “En el contexto de la Marcha Federal Universitaria…” \\n> “Hoy el debate público está puesto en…” \\n> “Según datos oficiales de Presupuesto Abierto…”\\n\\nEvitar:\\n> “Es tendencia nacional…” \\n> “Todo X habla de…” \\nsalvo que se tenga medición real.\\n\\n---\\n\\n# Formato recomendado: hook + thread corto\\n\\n## Tweet 1: hook + dato principal\\n\\nObjetivo: que entre gente al thread.\\n\\nDebe tener:\\n1. Contexto público del día.\\n2. Un dato oficial llamativo.\\n3. Una pregunta o bajada neutral.\\n4. Invitación implícita al detalle.\\n\\nEstructura:\\n\\n> Hoy se discute [tema]. \\n> En Presupuesto Abierto, [partida/programa] muestra [dato principal]. \\n> ¿Qué significa ese porcentaje de ejecución? Abro hilo con datos oficiales.\\n\\nEjemplo:\\n\\n> En plena Marcha Federal Universitaria, miramos los pagos oficiales del presupuesto nacional para universidades y hospitales universitarios. \\n> \\n> El dato clave no es solo cuánto se presupuestó, sino cuánto se pagó efectivamente. \\n> \\n> Hilo con datos de Presupuesto Abierto 👇\\n\\nO más directo:\\n\\n> Universidades: una cosa es el crédito presupuestado y otra lo efectivamente pagado. \\n> \\n> Hoy, con la Marcha Federal Universitaria en agenda, revisamos qué muestra Presupuesto Abierto sobre ejecución y pagos. \\n> \\n> Datos oficiales 👇\\n\\n---\\n\\n## Tweet 2: explicación del porcentaje de ejecución\\n\\nEste tweet es clave. Tiene que educar sin ponerse técnico de más.\\n\\nExplicar que el porcentaje de ejecución puede significar cosas distintas según la base:\\n\\n- **Crédito vigente**: cuánto dinero tiene autorizado el programa o partida.\\n- **Devengado**: gasto reconocido/comprometido administrativamente.\\n- **Pagado**: dinero efectivamente transferido o abonado.\\n- **% de ejecución pagada**: pagado / crédito vigente.\\n- Si el bot publica pagos, aclarar que está mirando **pagos**, no promesas ni créditos.\\n\\nTweet modelo:\\n\\n> Cómo leer el % de ejecución: \\n> \\n> • Crédito vigente = lo autorizado en el presupuesto. \\n> • Devengado = gasto reconocido. \\n> • Pagado = plata efectivamente girada. \\n> \\n> Este bot mira pagos oficiales. Por eso, una ejecución baja puede indicar que el crédito existe, pero todavía no se transformó en pagos.\\n\\nOtro modelo más corto:\\n\\n> Importante: “tener presupuesto” no es lo mismo que “haber cobrado”. \\n> \\n> En Presupuesto Abierto distinguimos: \\n> crédito vigente ≠ devengado ≠ pagado. \\n> \\n> El % que mostramos compara pagos contra crédito vigente. Es decir: cuánto de lo autorizado ya fue efectivamente pagado.\\n\\n---\\n\\n## Qué poner en tweet 1 vs tweet 2\\n\\n### Tweet 1: impacto y relevancia\\n\\nPoner:\\n- Tema del día: Marcha Federal Universitaria / UBA / hospitales universitarios.\\n- Dato más simple y verificable.\\n- No meter demasiados números.\\n- No explicar metodología todavía.\\n- No editorializar.\\n\\nEjemplo:\\n\\n> En medio del reclamo universitario, los datos oficiales permiten mirar una pregunta concreta: \\n> \\n> ¿cuánto del presupuesto universitario ya fue efectivamente pagado? \\n> \\n> Hilo con ejecución de Presupuesto Abierto 👇\\n\\n### Tweet 2: método y cautela\\n\\nPoner:\\n- Fuente: Presupuesto Abierto.\\n- Fecha de corte.\\n- Qué se mide: pagos.\\n- Qué no se mide: calidad del servicio, necesidad real, deuda administrativa no registrada, inflación si no está calculada.\\n- Diferencia entre crédito vigente y pagado.\\n\\nEjemplo:\\n\\n> Fuente: Presupuesto Abierto. \\n> Corte: [fecha]. \\n> \\n> Medimos pagos registrados, no comunicados políticos ni necesidades estimadas. \\n> \\n> Una ejecución baja no prueba por sí sola “cierre” o “abandono”, pero sí muestra que una parte del crédito autorizado todavía no llegó como pago.\\n\\n---\\n\\n# Thread ideal: 4 a 6 tweets\\n\\n## Tweet 1 — Hook\\nDato + contexto.\\n\\n## Tweet 2 — Cómo leerlo\\nExplicación de ejecución.\\n\\n## Tweet 3 — Dato específico\\nPrograma, jurisdicción, crédito vigente, pagado, %.\\n\\nEjemplo:\\n\\n> Partida: Hospitales Universitarios \\n> Crédito vigente: $X \\n> Pagado: $Y \\n> Ejecución pagada: Z% \\n> \\n> Lectura simple: de cada $100 autorizados, se pagaron $Z.\\n\\n## Tweet 4 — Comparación útil\\nComparar contra:\\n- mismo período del año anterior;\\n- promedio esperado por mes;\\n- otras partidas educativas;\\n- total de la jurisdicción.\\n\\nEjemplo:\\n\\n> Para comparar: a esta altura del año, una ejecución lineal rondaría aproximadamente el 33% si los pagos fueran parejos mes a mes. \\n> \\n> Si la ejecución está muy por debajo, el dato relevante es el retraso relativo en pagos.\\n\\nCuidado: aclarar que el gasto público no siempre se ejecuta linealmente.\\n\\n## Tweet 5 — Qué no dice el dato\\nMuy importante para credibilidad.\\n\\nEjemplo:\\n\\n> Qué NO dice este dato: \\n> \\n> • No mide calidad educativa. \\n> • No mide inflación automáticamente. \\n> • No prueba intencionalidad política. \\n> • No reemplaza la discusión salarial o judicial. \\n> \\n> Sí muestra cuánto se pagó oficialmente respecto del crédito vigente.\\n\\n## Tweet 6 — Cierre\\nInvitar a seguir la serie o pedir partida.\\n\\nEjemplo:\\n\\n> Vamos a seguir actualizando la ejecución de universidades, becas y hospitales universitarios con datos oficiales. \\n> \\n> Si querés que miremos una universidad o programa específico, dejalo en respuestas.\\n\\n---\\n\\n# Qué explicar sobre el porcentaje de ejecución\\n\\nEl bot debería repetir pedagógicamente esta idea:\\n\\n> El porcentaje de ejecución no es “cuánto falta para que funcione una universidad”. Es cuánto del crédito vigente fue registrado como pagado por el Estado.\\n\\nExplicación editorial:\\n\\n1. **Si el % es bajo**, significa que se pagó poco respecto del crédito disponible.\\n2. **Si el crédito vigente aumentó**, el % puede bajar aunque los pagos hayan crecido.\\n3. **Si hubo modificaciones presupuestarias**, comparar solo porcentajes puede confundir.\\n4. **Si hay inflación**, el monto nominal pagado puede subir pero caer en términos reales.\\n5. **Si el gasto es estacional**, no toda baja ejecución implica irregularidad.\\n6. **Para universidades**, separar:\\n - transferencias a universidades nacionales;\\n - salarios;\\n - funcionamiento;\\n - becas;\\n - hospitales universitarios;\\n - ciencia e investigación.\\n\\nFrase recomendada:\\n\\n> El % de ejecución sirve para ver ritmo de pagos. No alcanza solo para evaluar suficiencia presupuestaria.\\n\\n---\\n\\n# Frecuencia recomendada\\n\\n## Durante tema caliente — marcha / conflicto abierto\\n\\n- **1 thread principal por día** mientras dure el pico informativo.\\n- **1 o 2 tweets de actualización** si aparecen nuevos pagos o modificaciones relevantes.\\n- No publicar cada microvariación: puede parecer militancia o spam.\\n\\nEjemplo de agenda:\\n- Mañana: “qué dice Presupuesto Abierto”.\\n- Tarde: actualización si hubo pagos nuevos.\\n- Noche: resumen visual simple.\\n\\n## Fuera del pico\\n\\n- 2 a 3 publicaciones semanales sobre universidades.\\n- 1 hilo semanal comparativo.\\n- 1 actualización mensual de ejecución acumulada.\\n\\n## Regla práctica\\n\\nPublicar cuando haya:\\n- nuevo pago relevante;\\n- modificación de crédito;\\n- dato que contradice o matiza una afirmación pública;\\n- comparación interanual;\\n- cambio fuerte de ejecución.\\n\\nNo publicar solo porque “está caliente” si no hay dato nuevo.\\n\\n---\\n\\n# Tono recomendado\\n\\nDebe ser:\\n\\n- Neutral.\\n- Fiscalizador.\\n- Pedagógico.\\n- Seco con los números.\\n- Cauteloso con conclusiones políticas.\\n\\nTono ideal:\\n\\n> “Esto es lo que muestran los datos oficiales.”\\n\\nNo:\\n\\n> “El Gobierno abandonó las universidades.”\\n\\nTampoco:\\n\\n> “La UBA miente.”\\n\\nMejor:\\n\\n> “El dato oficial permite separar tres discusiones: crédito autorizado, pagos realizados y suficiencia del financiamiento.”\\n\\nUsar verbos sobrios:\\n- muestra;\\n- registra;\\n- informa;\\n- surge de;\\n- equivale a;\\n- representa;\\n- no permite concluir por sí solo.\\n\\nEvitar:\\n- “escándalo”;\\n- “brutal”;\\n- “motosierra”;\\n- “relato”;\\n- “fake”;\\n- “destruyeron”;\\n- “opereta”.\\n\\n---\\n\\n# Riesgos editoriales\\n\\n## 1. Confundir crédito con pago\\n\\nRiesgo: decir “hay $80.000 millones” cuando no fueron transferidos.\\n\\nSolución:\\n> “Crédito vigente autorizado” vs “pagado efectivamente”.\\n\\n## 2. Usar porcentaje sin monto\\n\\nUn 5% puede ser mucho o poco según el crédito. Siempre poner:\\n- crédito vigente;\\n- pagado;\\n- porcentaje.\\n\\n## 3. No aclarar fecha de corte\\n\\nLos datos presupuestarios cambian. Siempre decir:\\n> “Datos al [fecha/hora de consulta]”.\\n\\n## 4. Inflación\\n\\nMontos nominales pueden engañar. Si no se calcula real, aclarar:\\n> “Montos nominales, sin ajustar por inflación.”\\n\\n## 5. Atribuir intencionalidad\\n\\nPresupuesto Abierto muestra ejecución, no motivos políticos.\\n\\nEvitar:\\n> “No pagaron porque quieren cerrar hospitales.”\\n\\nUsar:\\n> “Los pagos registrados son bajos respecto del crédito vigente.”\\n\\n## 6. Meterse en disputa UBA vs Gobierno sin separar datos\\n\\nLa disputa pública incluye si la partida corresponde toda a UBA o a todos los hospitales universitarios. El bot debe decir:\\n\\n> “La partida corresponde a hospitales universitarios del sistema nacional. La distribución institucional es parte de la controversia pública.”\\n\\n## 7. Comparar mal partidas\\n\\nNo mezclar:\\n- universidades nacionales;\\n- hospitales universitarios;\\n- salarios docentes;\\n- becas;\\n- ciencia;\\ncomo si fueran una sola bolsa.\\n\\n## 8. Publicar como “oficial” algo que viene de medios\\n\\nEl contexto puede venir de noticias; los números del bot deben venir de Presupuesto Abierto.\\n\\nFormato recomendado:\\n> “Contexto público: Marcha Federal Universitaria.” \\n> “Dato presupuestario: Presupuesto Abierto.”\\n\\n---\\n\\n# Ejemplos de tweets para universidades\\n\\n## Ejemplo 1 — Thread general universidades\\n\\n**Tweet 1**\\n\\n> En plena Marcha Federal Universitaria, hay una pregunta concreta que los datos oficiales ayudan a responder: \\n> \\n> ¿cuánto del presupuesto universitario ya fue efectivamente pagado? \\n> \\n> Miramos Presupuesto Abierto 👇\\n\\n**Tweet 2**\\n\\n> Clave para leer el dato: \\n> \\n> • Crédito vigente = plata autorizada. \\n> • Devengado = gasto reconocido. \\n> • Pagado = plata efectivamente girada. \\n> \\n> Este bot sigue pagos. Por eso, ejecución baja significa: crédito autorizado que todavía no aparece como pago registrado.\\n\\n**Tweet 3**\\n\\n> Programa/partida: [nombre exacto en Presupuesto Abierto] \\n> Crédito vigente: $X \\n> Pagado: $Y \\n> Ejecución pagada: Z% \\n> \\n> Lectura simple: de cada $100 autorizados, se pagaron $Z.\\n\\n**Tweet 4**\\n\\n> Cuidado: el % de ejecución no dice todo. \\n> \\n> No mide inflación, salarios reales ni necesidades operativas. \\n> Sí muestra el ritmo administrativo de pagos respecto del crédito vigente.\\n\\n**Tweet 5**\\n\\n> En universidades conviene separar discusiones: \\n> \\n> 1. cuánto presupuesto hay; \\n> 2. cuánto se pagó; \\n> 3. si alcanza frente a inflación; \\n> 4. cómo se distribuye entre instituciones; \\n> 5. qué partidas corresponden a salarios, funcionamiento, becas u hospitales.\\n\\n---\\n\\n## Ejemplo 2 — Hospitales universitarios\\n\\n**Tweet 1**\\n\\n> Hospitales universitarios: el debate público habla de partidas, deuda y transferencias. \\n> \\n> En Presupuesto Abierto, la pregunta verificable es otra: \\n> \\n> ¿cuánto del crédito vigente para hospitales universitarios fue efectivamente pagado? \\n> \\n> Datos oficiales 👇\\n\\n**Tweet 2**\\n\\n> Para no mezclar conceptos: \\n> \\n> “Crédito vigente” no es lo mismo que “pagado”. \\n> \\n> Puede existir una partida autorizada y, al mismo tiempo, mostrar baja ejecución si los pagos todavía no fueron registrados.\\n\\n**Tweet 3**\\n\\n> Partida: Hospitales Universitarios \\n> Crédito vigente: $X \\n> Pagado: $Y \\n> Ejecución pagada: Z% \\n> Corte: [fecha] \\n> \\n> Eso equivale a $Z pagados cada $100 autorizados.\\n\\n**Tweet 4**\\n\\n> Qué permite decir el dato: \\n> \\n> • cuánto se pagó oficialmente; \\n> • qué proporción representa sobre el crédito; \\n> • si el ritmo de pagos viene bajo o alto. \\n> \\n> Qué no permite decir solo: \\n> • por qué no se pagó; \\n> • si alcanza para funcionar; \\n> • cómo debería distribuirse entre hospitales.\\n\\n**Tweet 5**\\n\\n> La discusión pública incluye si la partida debe distribuirse entre todos los hospitales universitarios y con qué criterio. \\n> \\n> Este hilo no resuelve esa disputa: muestra el estado de pagos registrado en Presupuesto Abierto.\\n\\n---\\n\\n## Ejemplo 3 — Versión más picante pero segura\\n\\n**Tweet 1**\\n\\n> “Hay presupuesto” y “se pagó” no son lo mismo. \\n> \\n> En medio del conflicto universitario, esa diferencia importa. \\n> \\n> Miramos pagos oficiales de Presupuesto Abierto para universidades y hospitales universitarios 👇\\n\\n**Tweet 2**\\n\\n> Si una partida tiene $100 autorizados y se pagaron $10, la ejecución pagada es 10%. \\n> \\n> Eso no explica por sí solo la causa, pero sí muestra el ritmo de giro efectivo de fondos.\\n\\n**Tweet 3**\\n\\n> Universidad / programa: [X] \\n> Crédito vigente: $X \\n> Pagado: $Y \\n> Ejecución: Z% \\n> \\n> Dato oficial al [fecha]. 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"arguments": "{\"mode\":\"replace\",\"new_string\":\" tweet = (\\n f\\\"Universidades: tener presupuesto ≠ haber cobrado. \\\"\\n f\\\"En plena marcha, Presupuesto Abierto registra {fmt_millions(total['credito_pagado'])} pagados el {day_dm} \\\"\\n f\\\"a universidades nacionales. UBA: {fmt_millions(top1.get('credito_pagado', 0))}. \\\"\\n f\\\"¿Qué significa ejecución {pct(annual_paid, annual_vig)}? Abro hilo 👇\\\"\\n )\\n thread = [\\n shorten_tweet(\\n f\\\"1/ Fuente: Presupuesto Abierto, corte {cut_dm}. Montos nominales en pesos. \\\"\\n f\\\"El dato mide pagos registrados, no anuncios ni necesidades estimadas.\\\"\\n ),\\n shorten_tweet(\\n f\\\"2/ Cómo leer el %: crédito vigente = plata autorizada; pagado = plata efectivamente registrada como pago. \\\"\\n f\\\"Ejecución {pct(annual_paid, annual_vig)} significa que se pagó ese porcentaje del crédito vigente 2026.\\\"\\n ),\\n shorten_tweet(\\n f\\\"3/ Universidades nacionales 2026: pagado {fmt_millions(annual_paid)} sobre crédito vigente {fmt_millions(annual_vig)}. \\\"\\n f\\\"Lectura simple: de cada $100 autorizados, figuran pagos por ${annual_paid/annual_vig*100:.1f}.\\\".replace(\\\".\\\", \\\",\\\")\\n if annual_vig else \\\"3/ Universidades nacionales: crédito vigente informado en cero; no se calcula porcentaje.\\\"\\n ),\\n shorten_tweet(\\n f\\\"4/ Hospitales universitarios: el {day_dm} figuran pagos por {fmt_millions(hosp_paid)}. \\\"\\n f\\\"Ojo: no todo pago universitario es hospitalario; salarios, funcionamiento y hospitales son partidas distintas.\\\"\\n ),\\n shorten_tweet(\\n \\\"5/ Qué NO dice el dato: no mide inflación, suficiencia del presupuesto ni intencionalidad política. \\\"\\n \\\"Sí muestra ritmo de pagos oficiales respecto del crédito vigente.\\\"\\n ),\\n ]\\n return Candidate(\\n topic=\\\"universidades\\\",\\n score=100,\\n tweet=shorten_tweet(tweet),\\n payload={\\\"day\\\": day, \\\"year\\\": year},\\n source_rows={\\\"total\\\": total, \\\"top\\\": top[:10], \\\"hospitales\\\": hosp, \\\"annual\\\": annual},\\n thread=thread,\\n )\\n\",\"old_string\":\" tweet = (\\n f\\\"En plena marcha universitaria, dato de Presupuesto Abierto: el {day_dm} se registraron pagos \\\"\\n f\\\"a universidades nacionales por {fmt_millions(total['credito_pagado'])}. \\\"\\n f\\\"{top1.get('subparcial_desc', 'Top universidad')}: {fmt_millions(top1.get('credito_pagado', 0))}. \\\"\\n f\\\"Hospitales universitarios: {fmt_millions(hosp_paid)}. \\\"\\n f\\\"Ejecución {year}: {pct(annual_paid, annual_vig)} del crédito vigente. Corte: {cut_dm}.\\\"\\n )\\n return Candidate(\\n topic=\\\"universidades\\\",\\n score=100,\\n tweet=shorten_tweet(tweet),\\n payload={\\\"day\\\": day, \\\"year\\\": year},\\n source_rows={\\\"total\\\": total, \\\"top\\\": top[:10], \\\"hospitales\\\": hosp, \\\"annual\\\": annual},\\n )\\n\",\"path\":\"/home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\"}"
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"content": "{\"success\": true, \"diff\": \"--- a//home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\\n+++ b//home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\\n@@ -174,18 +174,41 @@\\n cut_dm = cut[8:10] + \\\"/\\\" + cut[5:7] if len(cut) >= 10 else \\\"s/d\\\"\\n day_dm = day[8:10] + \\\"/\\\" + day[5:7]\\n tweet = (\\n- f\\\"En plena marcha universitaria, dato de Presupuesto Abierto: el {day_dm} se registraron pagos \\\"\\n- f\\\"a universidades nacionales por {fmt_millions(total['credito_pagado'])}. \\\"\\n- f\\\"{top1.get('subparcial_desc', 'Top universidad')}: {fmt_millions(top1.get('credito_pagado', 0))}. \\\"\\n- f\\\"Hospitales universitarios: {fmt_millions(hosp_paid)}. \\\"\\n- f\\\"Ejecución {year}: {pct(annual_paid, annual_vig)} del crédito vigente. Corte: {cut_dm}.\\\"\\n- )\\n+ f\\\"Universidades: tener presupuesto ≠ haber cobrado. \\\"\\n+ f\\\"En plena marcha, Presupuesto Abierto registra {fmt_millions(total['credito_pagado'])} pagados el {day_dm} \\\"\\n+ f\\\"a universidades nacionales. UBA: {fmt_millions(top1.get('credito_pagado', 0))}. \\\"\\n+ f\\\"¿Qué significa ejecución {pct(annual_paid, annual_vig)}? Abro hilo 👇\\\"\\n+ )\\n+ thread = [\\n+ shorten_tweet(\\n+ f\\\"1/ Fuente: Presupuesto Abierto, corte {cut_dm}. Montos nominales en pesos. \\\"\\n+ f\\\"El dato mide pagos registrados, no anuncios ni necesidades estimadas.\\\"\\n+ ),\\n+ shorten_tweet(\\n+ f\\\"2/ Cómo leer el %: crédito vigente = plata autorizada; pagado = plata efectivamente registrada como pago. \\\"\\n+ f\\\"Ejecución {pct(annual_paid, annual_vig)} significa que se pagó ese porcentaje del crédito vigente 2026.\\\"\\n+ ),\\n+ shorten_tweet(\\n+ f\\\"3/ Universidades nacionales 2026: pagado {fmt_millions(annual_paid)} sobre crédito vigente {fmt_millions(annual_vig)}. \\\"\\n+ f\\\"Lectura simple: de cada $100 autorizados, figuran pagos por ${annual_paid/annual_vig*100:.1f}.\\\".replace(\\\".\\\", \\\",\\\")\\n+ if annual_vig else \\\"3/ Universidades nacionales: crédito vigente informado en cero; no se calcula porcentaje.\\\"\\n+ ),\\n+ shorten_tweet(\\n+ f\\\"4/ Hospitales universitarios: el {day_dm} figuran pagos por {fmt_millions(hosp_paid)}. \\\"\\n+ f\\\"Ojo: no todo pago universitario es hospitalario; salarios, funcionamiento y hospitales son partidas distintas.\\\"\\n+ ),\\n+ shorten_tweet(\\n+ \\\"5/ Qué NO dice el dato: no mide inflación, suficiencia del presupuesto ni intencionalidad política. \\\"\\n+ \\\"Sí muestra ritmo de pagos oficiales respecto del crédito vigente.\\\"\\n+ ),\\n+ ]\\n return Candidate(\\n topic=\\\"universidades\\\",\\n score=100,\\n tweet=shorten_tweet(tweet),\\n payload={\\\"day\\\": day, \\\"year\\\": year},\\n source_rows={\\\"total\\\": total, \\\"top\\\": top[:10], \\\"hospitales\\\": hosp, \\\"annual\\\": annual},\\n+ thread=thread,\\n )\\n \\n \\n\", \"files_modified\": [\"/home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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"content": "{\"success\": true, \"diff\": \"--- a//home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\\n+++ b//home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\\n@@ -239,7 +239,11 @@\\n f\\\"ATN: Presupuesto Abierto registra pago el {day_dm} a {r.get('ubicacion_geografica_desc','s/d')} \\\"\\n f\\\"por {fmt_millions(r.get('credito_pagado',0))}. Contexto: sigue la discusión por reparto de ATN a provincias. Corte: {cut_dm}.\\\"\\n )\\n- return Candidate(\\\"atn\\\", 70, shorten_tweet(tweet), {\\\"since\\\": since}, {\\\"row\\\": r})\\n+ thread = [\\n+ shorten_tweet(\\\"1/ ATN = Aportes del Tesoro Nacional. Son transferencias discrecionales a provincias/municipios, separadas de coparticipación automática.\\\"),\\n+ shorten_tweet(f\\\"2/ Fuente: Presupuesto Abierto, corte {cut_dm}. El monto publicado es crédito pagado registrado, no anuncio político.\\\"),\\n+ ]\\n+ return Candidate(\\\"atn\\\", 70, shorten_tweet(tweet), {\\\"since\\\": since}, {\\\"row\\\": r}, thread=thread)\\n \\n \\n def pick_candidate(token: str, topic: str) -> Candidate:\\n\", \"files_modified\": [\"/home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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"content": "{\"success\": true, \"diff\": \"--- a//home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\\n+++ b//home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\\n@@ -297,10 +297,26 @@\\n return pid, False\\n \\n \\n-def xurl_post(tweet: str) -> None:\\n+def xurl_post(tweet: str) -> str:\\n if os.getenv(\\\"ENABLE_POSTING\\\") != \\\"1\\\":\\n raise RuntimeError(\\\"ENABLE_POSTING must be 1 to post\\\")\\n- subprocess.run([\\\"xurl\\\", \\\"post\\\", tweet], check=True)\\n+ proc = subprocess.run([\\\"xurl\\\", \\\"post\\\", tweet], check=True, text=True, capture_output=True)\\n+ try:\\n+ data = json.loads(proc.stdout)\\n+ return str(data.get(\\\"data\\\", {}).get(\\\"id\\\") or \\\"\\\")\\n+ except Exception:\\n+ return \\\"\\\"\\n+\\n+\\n+def xurl_reply(parent_id: str, tweet: str) -> str:\\n+ if os.getenv(\\\"ENABLE_POSTING\\\") != \\\"1\\\":\\n+ raise RuntimeError(\\\"ENABLE_POSTING must be 1 to post\\\")\\n+ proc = subprocess.run([\\\"xurl\\\", \\\"reply\\\", parent_id, tweet], check=True, text=True, capture_output=True)\\n+ try:\\n+ data = json.loads(proc.stdout)\\n+ return str(data.get(\\\"data\\\", {}).get(\\\"id\\\") or \\\"\\\")\\n+ except Exception:\\n+ return \\\"\\\"\\n \\n \\n def main() -> int:\\n\", \"files_modified\": [\"/home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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"content": "{\"success\": true, \"diff\": \"--- a//home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\\n+++ b//home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\\n@@ -323,6 +323,7 @@\\n ap = argparse.ArgumentParser()\\n ap.add_argument(\\\"--topic\\\", choices=[\\\"auto\\\", \\\"universidades\\\", \\\"atn\\\"], default=\\\"auto\\\")\\n ap.add_argument(\\\"--post\\\", action=\\\"store_true\\\", help=\\\"Actually post via xurl. Requires ENABLE_POSTING=1\\\")\\n+ ap.add_argument(\\\"--thread\\\", action=\\\"store_true\\\", help=\\\"When posting, reply with the generated detail thread\\\")\\n ap.add_argument(\\\"--dry-run\\\", action=\\\"store_true\\\", help=\\\"Generate only; never post\\\")\\n ap.add_argument(\\\"--db\\\", default=os.getenv(\\\"BOT_DB_PATH\\\", \\\"./bot_state.sqlite3\\\"))\\n ap.add_argument(\\\"--json\\\", action=\\\"store_true\\\")\\n\", \"files_modified\": [\"/home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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"arguments": "{\"mode\":\"replace\",\"new_string\":\" posted = False\\n posted_ids: list[str] = []\\n if args.post and not args.dry_run:\\n parent_id = xurl_post(cand.tweet)\\n if parent_id:\\n posted_ids.append(parent_id)\\n posted = True\\n if args.thread and cand.thread:\\n reply_to = parent_id\\n for reply in cand.thread:\\n if not reply_to:\\n break\\n reply_to = xurl_reply(reply_to, reply)\\n if reply_to:\\n posted_ids.append(reply_to)\\n\\n conn = db_connect(args.db)\\n pid, is_new = save_candidate(conn, cand, posted)\\n\\n out = {\\n \\\"id\\\": pid,\\n \\\"new\\\": is_new,\\n \\\"posted\\\": posted,\\n \\\"posted_ids\\\": posted_ids,\\n \\\"topic\\\": cand.topic,\\n \\\"len\\\": len(cand.tweet),\\n \\\"tweet\\\": cand.tweet,\\n \\\"thread\\\": cand.thread or [],\\n \\\"thread_lens\\\": [len(t) for t in (cand.thread or [])],\\n \\\"source\\\": cand.source_rows,\\n }\\n if args.json:\\n print(json.dumps(out, ensure_ascii=False, indent=2))\\n else:\\n print(f\\\"topic={cand.topic} len={len(cand.tweet)} new={is_new} posted={posted}\\\")\\n print(cand.tweet)\\n if cand.thread:\\n print(\\\"\\\\nTHREAD:\\\")\\n for i, t in enumerate(cand.thread, 1):\\n print(f\\\"[{i}] len={len(t)} {t}\\\")\\n return 0\\n\",\"old_string\":\" posted = False\\n if args.post and not args.dry_run:\\n xurl_post(cand.tweet)\\n posted = True\\n\\n conn = db_connect(args.db)\\n pid, is_new = save_candidate(conn, cand, posted)\\n\\n out = {\\\"id\\\": pid, \\\"new\\\": is_new, \\\"posted\\\": posted, \\\"topic\\\": cand.topic, \\\"len\\\": len(cand.tweet), \\\"tweet\\\": cand.tweet, \\\"source\\\": cand.source_rows}\\n if args.json:\\n print(json.dumps(out, ensure_ascii=False, indent=2))\\n else:\\n print(f\\\"topic={cand.topic} len={len(cand.tweet)} new={is_new} posted={posted}\\\")\\n print(cand.tweet)\\n return 0\\n\",\"path\":\"/home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\"}"
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"content": "{\"success\": true, \"diff\": \"--- a//home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\\n+++ b//home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\\n@@ -335,19 +335,45 @@\\n raise RuntimeError(f\\\"Tweet too long: {len(cand.tweet)}\\\")\\n \\n posted = False\\n+ posted_ids: list[str] = []\\n if args.post and not args.dry_run:\\n- xurl_post(cand.tweet)\\n+ parent_id = xurl_post(cand.tweet)\\n+ if parent_id:\\n+ posted_ids.append(parent_id)\\n posted = True\\n+ if args.thread and cand.thread:\\n+ reply_to = parent_id\\n+ for reply in cand.thread:\\n+ if not reply_to:\\n+ break\\n+ reply_to = xurl_reply(reply_to, reply)\\n+ if reply_to:\\n+ posted_ids.append(reply_to)\\n \\n conn = db_connect(args.db)\\n pid, is_new = save_candidate(conn, cand, posted)\\n \\n- out = {\\\"id\\\": pid, \\\"new\\\": is_new, \\\"posted\\\": posted, \\\"topic\\\": cand.topic, \\\"len\\\": len(cand.tweet), \\\"tweet\\\": cand.tweet, \\\"source\\\": cand.source_rows}\\n+ out = {\\n+ \\\"id\\\": pid,\\n+ \\\"new\\\": is_new,\\n+ \\\"posted\\\": posted,\\n+ \\\"posted_ids\\\": posted_ids,\\n+ \\\"topic\\\": cand.topic,\\n+ \\\"len\\\": len(cand.tweet),\\n+ \\\"tweet\\\": cand.tweet,\\n+ \\\"thread\\\": cand.thread or [],\\n+ \\\"thread_lens\\\": [len(t) for t in (cand.thread or [])],\\n+ \\\"source\\\": cand.source_rows,\\n+ }\\n if args.json:\\n print(json.dumps(out, ensure_ascii=False, indent=2))\\n else:\\n print(f\\\"topic={cand.topic} len={len(cand.tweet)} new={is_new} posted={posted}\\\")\\n print(cand.tweet)\\n+ if cand.thread:\\n+ print(\\\"\\\\nTHREAD:\\\")\\n+ for i, t in enumerate(cand.thread, 1):\\n+ print(f\\\"[{i}] len={len(t)} {t}\\\")\\n return 0\\n \\n \\n\", \"files_modified\": [\"/home/ubuntu/budget-transfer-bot/budget_transfer_bot.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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"content": "Listo. Avancé bastante.\n\n## Nombre recomendado\n\n**Giro Detectado** \nHandle ideal: **`@GiroDetectado`**\n\nPor qué:\n- Se entiende al toque.\n- Suena a alerta.\n- No queda encerrado solo en universidades/provincias.\n- Sirve para “la caja se movió” sin sonar militante.\n- Es más fuerte que “PresuBot” o nombres demasiado técnicos.\n\nAlternativa más editorial:\n\n**La Caja Pública** — `@LaCajaPublica`\n\nPero para Twitter bot, me quedo con **Giro Detectado**.\n\n---\n\n## Bio / descripción\n\nBio corta:\n\n> Bot argentino de datos presupuestarios. Detecta pagos y transferencias relevantes de Nación usando fuentes oficiales. Presupuesto Abierto, sin humo.\n\nBio más picante:\n\n> La caja pública, en datos oficiales. Pagos, transferencias y ejecución presupuestaria de Nación. Fuente: Presupuesto Abierto.\n\nTagline:\n\n> El dato oficial. La lectura es tuya.\n\n---\n\n## Assets creados\n\nPerfil:\n\nMEDIA:/home/ubuntu/budget-transfer-bot/assets/profile-giro-detectado.png\n\nBanner:\n\nMEDIA:/home/ubuntu/budget-transfer-bot/assets/banner-giro-detectado.png\n\nTambién dejé SVG editables:\n\n```text\n/home/ubuntu/budget-transfer-bot/assets/profile-giro-detectado.svg\n/home/ubuntu/budget-transfer-bot/assets/banner-giro-detectado.svg\n```\n\n---\n\n## Scouting Twitter Argentina / estrategia\n\nNo tengo X autenticado todavía, así que no puedo leer trends internos reales. Usé web pública + noticias + mirrors/señales accesibles.\n\nConclusión:\n\n### Cadencia recomendada\n\nPara cuenta nueva:\n\n```text\n3 a 5 tweets por día máximo\n1 thread fuerte cuando haya tema caliente\n0 tweets si no hay dato relevante\n```\n\nNo firehose.\n\nFormato diario ideal:\n\n1. **Tweet/hilo principal**: el dato más conectado con agenda.\n2. **1-2 alertas** si aparece pago relevante.\n3. **Resumen nocturno** solo si hubo movimientos.\n\n### Lenguaje que pega\n\nTono:\n\n```text\nneutral-picante\ndato duro\nrioplatense\nsin parecer ministerio\nsin militar\n```\n\nFrases útiles:\n\n- “tener presupuesto ≠ haber cobrado”\n- “la caja se movió”\n- “Presupuesto Abierto registra…”\n- “dato oficial”\n- “pagado, no anunciado”\n- “crédito vigente vs pagado”\n\nEvitar:\n\n- “escándalo”\n- “motosierra”\n- “relato”\n- “fake”\n- hashtags partidarios permanentes\n\n### Tags\n\nNo taguearía políticos por defecto. Parece spam/militancia.\n\nSí eventualmente:\n- universidades si el dato las menciona y el tono es neutro;\n- OPC / fuente institucional si corresponde;\n- periodistas solo si responden/piden el dato.\n\nHashtags: máximo 0-2.\n\nÚtiles:\n\n```text\n#PresupuestoAbierto\n#DatosAbiertos\n#Universidades\n#ATN\n#Provincias\n#GastoPúblico\n```\n\n---\n\n## Cambio importante al bot\n\nActualicé el bot para soportar **hook + thread**.\n\nAntes hacía un tweet único con demasiada data. Ahora genera:\n\n1. Tweet principal con hook.\n2. Thread explicando:\n - fuente;\n - qué significa ejecución;\n - crédito vigente vs pagado;\n - detalle universidades;\n - hospitales universitarios;\n - caveats.\n\nCommit:\n\n```text\na742618 feat: add branding assets and thread output\n```\n\n---\n\n## Ejemplo generado ahora\n\nTweet principal:\n\n> Universidades: tener presupuesto ≠ haber cobrado. En plena marcha, Presupuesto Abierto registra $366 mil millones pagados el 05/05 a universidades nacionales. UBA: $62,6 mil millones. ¿Qué significa ejecución 29,4%? Abro hilo 👇\n\nThread:\n\n> 1/ Fuente: Presupuesto Abierto, corte 12/05. Montos nominales en pesos. El dato mide pagos registrados, no anuncios ni necesidades estimadas.\n\n> 2/ Cómo leer el %: crédito vigente = plata autorizada; pagado = plata efectivamente registrada como pago. Ejecución 29,4% significa que se pagó ese porcentaje del crédito vigente 2026.\n\n> 3/ Universidades nacionales 2026: pagado $1,54 billones sobre crédito vigente $5,23 billones. Lectura simple: de cada $100 autorizados, figuran pagos por $29,4.\n\n> 4/ Hospitales universitarios: el 05/05 figuran pagos por $2,5 mil millones. Ojo: no todo pago universitario es hospitalario; salarios, funcionamiento y hospitales son partidas distintas.\n\n> 5/ Qué NO dice el dato: no mide inflación, suficiencia del presupuesto ni intencionalidad política. Sí muestra ritmo de pagos oficiales respecto del crédito vigente.\n\nEsto responde bien a tu duda: **29,4% significa que de cada $100 autorizados para universidades nacionales en 2026, figuran pagos por $29,4 al corte.** No significa que “alcance” ni que “debería estar en 29,4”; significa ritmo de pago registrado.\n\n---\n\n## Estado técnico\n\nRepo:\n\n```bash\n/home/ubuntu/budget-transfer-bot\n```\n\nComando preview:\n\n```bash\ncd /home/ubuntu/budget-transfer-bot\nPRESUPUESTO_ABIERTO_TOKEN=... .venv/bin/python budget_transfer_bot.py --topic auto --dry-run --json\n```\n\nComando post real, cuando X esté autenticado:\n\n```bash\nENABLE_POSTING=1 PRESUPUESTO_ABIERTO_TOKEN=... .venv/bin/python budget_transfer_bot.py --topic auto --post --thread\n```\n\n---\n\n## Qué necesito de vos\n\nSolo 3 cosas:\n\n1. **Crear/reservar cuenta X**\n - Ideal: `@GiroDetectado`\n - Backup: `@LaCajaPublica`, `@PresuBotAR`, `@RadarPresu`\n\n2. **Autenticar xurl**\n En la máquina:\n\n ```bash\n export PATH=\"$HOME/.local/bin:$PATH\"\n\n xurl auth apps add presupuesto-bot --client-id TU_CLIENT_ID --client-secret TU_CLIENT_SECRET\n xurl auth oauth2 --app presupuesto-bot TU_HANDLE\n xurl auth default presupuesto-bot TU_HANDLE\n xurl whoami\n ```\n\n3. **Confirmarme línea editorial**\n Mi recomendación:\n - nombre: **Giro Detectado**\n - tono: neutral-picante;\n - 1 thread principal por día;\n - hasta 3-5 tweets/día si hay datos;\n - no taguear políticos por defecto;\n - autopost recién después de 2-3 días de dry-run.",
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"text": "Listo. Avancé bastante.\n\n## Nombre recomendado\n\n**Giro Detectado** \nHandle ideal: **`@GiroDetectado`**\n\nPor qué:\n- Se entiende al toque.\n- Suena a alerta.\n- No queda encerrado solo en universidades/provincias.\n- Sirve para “la caja se movió” sin sonar militante.\n- Es más fuerte que “PresuBot” o nombres demasiado técnicos.\n\nAlternativa más editorial:\n\n**La Caja Pública** — `@LaCajaPublica`\n\nPero para Twitter bot, me quedo con **Giro Detectado**.\n\n---\n\n## Bio / descripción\n\nBio corta:\n\n> Bot argentino de datos presupuestarios. Detecta pagos y transferencias relevantes de Nación usando fuentes oficiales. Presupuesto Abierto, sin humo.\n\nBio más picante:\n\n> La caja pública, en datos oficiales. Pagos, transferencias y ejecución presupuestaria de Nación. Fuente: Presupuesto Abierto.\n\nTagline:\n\n> El dato oficial. La lectura es tuya.\n\n---\n\n## Assets creados\n\nPerfil:\n\nMEDIA:/home/ubuntu/budget-transfer-bot/assets/profile-giro-detectado.png\n\nBanner:\n\nMEDIA:/home/ubuntu/budget-transfer-bot/assets/banner-giro-detectado.png\n\nTambién dejé SVG editables:\n\n```text\n/home/ubuntu/budget-transfer-bot/assets/profile-giro-detectado.svg\n/home/ubuntu/budget-transfer-bot/assets/banner-giro-detectado.svg\n```\n\n---\n\n## Scouting Twitter Argentina / estrategia\n\nNo tengo X autenticado todavía, así que no puedo leer trends internos reales. Usé web pública + noticias + mirrors/señales accesibles.\n\nConclusión:\n\n### Cadencia recomendada\n\nPara cuenta nueva:\n\n```text\n3 a 5 tweets por día máximo\n1 thread fuerte cuando haya tema caliente\n0 tweets si no hay dato relevante\n```\n\nNo firehose.\n\nFormato diario ideal:\n\n1. **Tweet/hilo principal**: el dato más conectado con agenda.\n2. **1-2 alertas** si aparece pago relevante.\n3. **Resumen nocturno** solo si hubo movimientos.\n\n### Lenguaje que pega\n\nTono:\n\n```text\nneutral-picante\ndato duro\nrioplatense\nsin parecer ministerio\nsin militar\n```\n\nFrases útiles:\n\n- “tener presupuesto ≠ haber cobrado”\n- “la caja se movió”\n- “Presupuesto Abierto registra…”\n- “dato oficial”\n- “pagado, no anunciado”\n- “crédito vigente vs pagado”\n\nEvitar:\n\n- “escándalo”\n- “motosierra”\n- “relato”\n- “fake”\n- hashtags partidarios permanentes\n\n### Tags\n\nNo taguearía políticos por defecto. Parece spam/militancia.\n\nSí eventualmente:\n- universidades si el dato las menciona y el tono es neutro;\n- OPC / fuente institucional si corresponde;\n- periodistas solo si responden/piden el dato.\n\nHashtags: máximo 0-2.\n\nÚtiles:\n\n```text\n#PresupuestoAbierto\n#DatosAbiertos\n#Universidades\n#ATN\n#Provincias\n#GastoPúblico\n```\n\n---\n\n## Cambio importante al bot\n\nActualicé el bot para soportar **hook + thread**.\n\nAntes hacía un tweet único con demasiada data. Ahora genera:\n\n1. Tweet principal con hook.\n2. Thread explicando:\n - fuente;\n - qué significa ejecución;\n - crédito vigente vs pagado;\n - detalle universidades;\n - hospitales universitarios;\n - caveats.\n\nCommit:\n\n```text\na742618 feat: add branding assets and thread output\n```\n\n---\n\n## Ejemplo generado ahora\n\nTweet principal:\n\n> Universidades: tener presupuesto ≠ haber cobrado. En plena marcha, Presupuesto Abierto registra $366 mil millones pagados el 05/05 a universidades nacionales. UBA: $62,6 mil millones. ¿Qué significa ejecución 29,4%? Abro hilo 👇\n\nThread:\n\n> 1/ Fuente: Presupuesto Abierto, corte 12/05. Montos nominales en pesos. El dato mide pagos registrados, no anuncios ni necesidades estimadas.\n\n> 2/ Cómo leer el %: crédito vigente = plata autorizada; pagado = plata efectivamente registrada como pago. Ejecución 29,4% significa que se pagó ese porcentaje del crédito vigente 2026.\n\n> 3/ Universidades nacionales 2026: pagado $1,54 billones sobre crédito vigente $5,23 billones. Lectura simple: de cada $100 autorizados, figuran pagos por $29,4.\n\n> 4/ Hospitales universitarios: el 05/05 figuran pagos por $2,5 mil millones. Ojo: no todo pago universitario es hospitalario; salarios, funcionamiento y hospitales son partidas distintas.\n\n> 5/ Qué NO dice el dato: no mide inflación, suficiencia del presupuesto ni intencionalidad política. Sí muestra ritmo de pagos oficiales respecto del crédito vigente.\n\nEsto responde bien a tu duda: **29,4% significa que de cada $100 autorizados para universidades nacionales en 2026, figuran pagos por $29,4 al corte.** No significa que “alcance” ni que “debería estar en 29,4”; significa ritmo de pago registrado.\n\n---\n\n## Estado técnico\n\nRepo:\n\n```bash\n/home/ubuntu/budget-transfer-bot\n```\n\nComando preview:\n\n```bash\ncd /home/ubuntu/budget-transfer-bot\nPRESUPUESTO_ABIERTO_TOKEN=... .venv/bin/python budget_transfer_bot.py --topic auto --dry-run --json\n```\n\nComando post real, cuando X esté autenticado:\n\n```bash\nENABLE_POSTING=1 PRESUPUESTO_ABIERTO_TOKEN=... .venv/bin/python budget_transfer_bot.py --topic auto --post --thread\n```\n\n---\n\n## Qué necesito de vos\n\nSolo 3 cosas:\n\n1. **Crear/reservar cuenta X**\n - Ideal: `@GiroDetectado`\n - Backup: `@LaCajaPublica`, `@PresuBotAR`, `@RadarPresu`\n\n2. **Autenticar xurl**\n En la máquina:\n\n ```bash\n export PATH=\"$HOME/.local/bin:$PATH\"\n\n xurl auth apps add presupuesto-bot --client-id TU_CLIENT_ID --client-secret TU_CLIENT_SECRET\n xurl auth oauth2 --app presupuesto-bot TU_HANDLE\n xurl auth default presupuesto-bot TU_HANDLE\n xurl whoami\n ```\n\n3. **Confirmarme línea editorial**\n Mi recomendación:\n - nombre: **Giro Detectado**\n - tono: neutral-picante;\n - 1 thread principal por día;\n - hasta 3-5 tweets/día si hay datos;\n - no taguear políticos por defecto;\n - autopost recién después de 2-3 días de dry-run."
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"content": "[nachlakes] LaCajaPublica me encanto. Podes usar el modelo ChatGPT Imagen 2 para crear el PFP y el banner por favor? el que hiciste, como sea que lo hayas hecho, es una poronga."
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"content": "{\"bytes_written\": 4791, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}}\n\n[Subdirectory context discovered: ~/CLAUDE.md]\n# CLAUDE.md\n\nThis file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.\n\n## Environment\n\nUbuntu 24.04 LTS, ARM64 (Oracle Cloud VPS). This is the home directory of an AI agent named **Pipo**, serving user **Ignacio/Chicho**.\n\n- Node.js v22, npm 10, Python 3.12, Git 2.43, Bitwarden CLI, Tailscale\n- Tailscale IP: `100.87.116.90`, hostname: `miopenclaw-vnic.tail9799d2.ts.net`\n\n## Key Directories\n\n| Path | Purpose |\n|------|---------|\n| `~/.openclaw/workspace/` | Main agent workspace (canonical) |\n| `~/openclaw-workspace/` | Secondary git repo with project artifacts |\n| `~/.openclaw/openclaw.json` | OpenClaw platform config (gateway, channels, skills) |\n| `~/.bw/` | Bitwarden session token |\n\n## Shell Helpers (from `~/.bash_aliases`)\n\n```bash\nbw-sync # Load saved Bitwarden session\nbw-unlock # Unlock vault and save session\ng \"prompt\" # Gemini CLI wrapper\nc \"prompt\" # Codex safe mode (read-only, no internet)\ncn \"prompt\" # Codex network mode (full access)\npipo-deploy [name] # Expose port to Tailscale at /preview//\npipo-undeploy # Remove Tailscale preview route\npj # Job controller (~/.openclaw/workspace/ops/cli-jobs/jobctl.sh)\n```\n\n## Critical Constraints\n\n**OpenClaw gateway** (port 18789): Restarting severs any active agent session. Prefer config hot-reload when possible (`openclaw config set ...`). If a restart is truly needed (e.g. fixing broken Telegram delivery), it is allowed — Ignacio authorizes it. Use `openclaw gateway restart` and verify logs afterward.\n\n**Chromium browser tool**: ALWAYS use profile `openclaw` (connected to headless Chromium on port 9222). NEVER use profile `chrome` — that profile requires a manual extension that does not exist on this VPS.\n\n**Tailscale serve**: Port 443 root (`/`) is reserved for the OpenClaw dashboard. Use preview ports 3001–3010 for apps and expose them via `pipo-deploy`.\n\n## Deployment Pattern\n\n1. Start your app on a port in range 3001–3010\n2. Run `pipo-deploy `\n3. App is accessible at `https://miopenclaw-vnic.tail9799d2.ts.net/preview//`\n\n## Agent Workspace Structure (`~/.openclaw/workspace/`)\n\n- `SOUL.md` / `AGENTS.md` — agent persona and session protocol\n- `MEMORIES.md` — long-term curated memory (canonical; `MEMORY.md` is a compat alias)\n- `memory/YYYY-MM-DD.md` — daily session logs\n- `HEARTBEAT.md` — periodic task checklist (empty = skip heartbeat)\n- `skills/` — installed agent skills (bitwarden, openclaw-bitwarden, parallel-preview-orchestrator)\n- `ops/` — operational scripts (cli-jobs, docker-cli-stack)\n- `node_modules/` — Playwright installed here\n\n## Secrets\n\nRetrieved from Bitwarden vault. After `bw-sync`, use:\n```bash\nbw get username \"item-name\"\nbw get password \"item-name\"\n```\n\nAPI keys (Gemini, OpenAI/Codex, GitHub) are auto-loaded from `~/.openclaw/openclaw.json` into the shell environment via `~/.bash_aliases`.",
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To monitor your current usage, head to: https://ai.dev/rate-limit. \\\\\\\\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash\\\\\\\\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.0-flash\\\\\\\\n* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.0-flash\\\\\\\\nPlease retry in 4.683319153s.\\\",\\\\n \\\"status\\\": \\\"RESOURCE_EXHAUSTED\\\",\\\\n \\\"details\\\": [\\\\n {\\\\n \\\"@type\\\": \\\"type.googleapis.com/google.rpc.Help\\\",\\\\n \\\"links\\\": [\\\\n {\\\\n \\\"description\\\": \\\"Learn more about Gemini API quotas\\\",\\\\n \\\"url\\\": \\\"https://ai.google.dev/gemini-api/docs/rate-limits\\\"\\\\n }\\\\n ]\\\\n },\\\\n {\\\\n \\\"@type\\\": \\\"type.googleapis.com/google.rpc.QuotaFailure\\\",\\\\n \\\"violations\\\": [\\\\n {\\\\n \\\"quotaMetric\\\": \\\"generativelanguage.googleapis.com/generate_content_free_tier_requests\\\",\\\\n \\\"quotaId\\\": \\\"GenerateRequestsPerDayPerProjectPerModel-FreeTier\\\",\\\\n \\\"quotaDimensions\\\": {\\\\n \\\"location\\\": \\\"global\\\",\\\\n \\\"model\\\": \\\"gemini-2.0-flash\\\"\\\\n }\\\\n },\\\\n {\\\\n \\\"quotaMetric\\\": \\\"generativelanguage.googleapis.com/generate_content_free_tier_requests\\\",\\\\n \\\"quotaId\\\": \\\"GenerateRequestsPerMinutePerProjectPerModel-FreeTier\\\",\\\\n \\\"quotaDimensions\\\": {\\\\n \\\"location\\\": \\\"global\\\",\\\\n \\\"model\\\": \\\"gemini-2.0-flash\\\"\\\\n }\\\\n },\\\\n {\\\\n \\\"quotaMetric\\\": \\\"generativelanguage.googleapis.com/generate_content_free_tier_input_token_count\\\",\\\\n \\\"quotaId\\\": \\\"GenerateContentInputTokensPerModelPerMinute-FreeTier\\\",\\\\n \\\"quotaDimensions\\\": {\\\\n \\\"model\\\": \\\"gemini-2.0-flash\\\",\\\\n \\\"location\\\": \\\"global\\\"\\\\n }\\\\n }\\\\n ]\\\\n },\\\\n {\\\\n \\\"@type\\\": \\\"type.googleapis.com/google.rpc.RetryInfo\\\",\\\\n \\\"retryDelay\\\": \\\"4s\\\"\\\\n }\\\\n ]\\\\n }\\\\n}\\\\n', 'provider_name': 'Google AI Studio', 'is_byok': True}}, 'user_id': 'user_3A4dOJw9P200EnmVgpSnwrvWjWY'}\",\n \"analysis\": \"Insufficient credits or payment required. Please top up your API provider account and try again. Error: Error code: 429 - {'error': {'message': 'Provider returned error', 'code': 429, 'metadata': {'raw': '{\\\\n \\\"error\\\": {\\\\n \\\"code\\\": 429,\\\\n \\\"message\\\": \\\"You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. 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"id": "rs_0a43e10fa0d9a177016a04830e7ba48191bd130d9cadfb34b0",
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},
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"role": "tool",
"content": "{\"output\": \"[master 2b255ec] feat: add la caja publica branding assets\\n 3 files changed, 100 insertions(+)\\n create mode 100644 assets/banner-la-caja-publica.png\\n create mode 100644 assets/profile-la-caja-publica.png\\n create mode 100644 scripts/create_lacaja_assets.py\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_L7LDIZTLPimrIWEwponLq2SL"
},
{
"role": "assistant",
"content": "Sí: **La Caja Pública** es mejor. Más marca, más durable, menos “botcito”.\n\nIntenté generar con el tool de imagen, pero el backend de imagen no tiene key configurada (`FAL_KEY` missing). No tengo selector real de “ChatGPT Imagen 2” desde acá. Dejé igualmente una versión nueva mucho más alineada con **La Caja Pública** para que no quedemos bloqueados.\n\n## Assets nuevos\n\nPFP:\n\nMEDIA:/home/ubuntu/budget-transfer-bot/assets/profile-la-caja-publica.png\n\nBanner:\n\nMEDIA:/home/ubuntu/budget-transfer-bot/assets/banner-la-caja-publica.png\n\nRepo actualizado:\n\n```text\n/home/ubuntu/budget-transfer-bot\ncommit 2b255ec feat: add la caja publica branding assets\n```\n\n## Branding final\n\nNombre:\n\n```text\nLa Caja Pública\n```\n\nHandle ideal:\n\n```text\n@LaCajaPublica\n```\n\nBackups:\n\n```text\n@CajaPublicaAR\n@LaCajaPubAR\n@CajaPublicaBot\n@PresupuestoCaja\n@LaCajaNacion\n```\n\nBio:\n\n> La caja pública, en datos oficiales. Pagos, transferencias y ejecución presupuestaria de Nación. Fuente: Presupuesto Abierto.\n\nTagline:\n\n> El dato oficial. La lectura es tuya.\n\n## Prompts listos para ChatGPT Imagen 2\n\nSi querés tirarlos directo en ChatGPT Imagen 2:\n\n### PFP\n\n> Crear imagen de perfil premium para una cuenta de X/Twitter llamada “La Caja Pública”. Tema: transparencia presupuestaria argentina. Estilo editorial moderno, data journalism, confiable pero picante. Fondo azul noche, acentos celeste y blanco argentinos. Ícono central: una caja/tesorería pública transparente o caja fuerte abierta con líneas de flujo de dinero/datos, un pequeño sol argentino sutil, sin parecer logo oficial del gobierno. Muy legible en tamaño avatar, sin texto pequeño, sin personas, sin clutter. Look profesional, memorable, alto contraste.\n\n### Banner\n\n> Crear banner 1500x500 para X/Twitter de una cuenta llamada “La Caja Pública”. Tema: pagos, transferencias y ejecución presupuestaria de Nación en datos oficiales. Estilo moderno editorial/data journalism, fondo azul noche, acentos celeste/blanco, líneas de datos, radar presupuestario, caja pública/transparente/cash drawer como metáfora. Texto grande: “La Caja Pública”. Subtítulo: “Pagos y transferencias de Nación en datos oficiales”. Tagline pequeño: “El dato oficial. La lectura es tuya.” Profesional, limpio, atractivo, no gubernamental, no partidario.\n\n## Siguiente de tu lado\n\n1. Reservá el handle, idealmente:\n ```text\n @LaCajaPublica\n ```\n\n2. Pasame cuál asset preferís:\n - uso los PNG que dejé;\n - o generás con ChatGPT Imagen 2 usando los prompts y me pasás los archivos para integrarlos.\n\n3. Cuando esté la cuenta, hacemos auth de `xurl` y queda listo para publicar thread real.",
"codex_message_items": [
{
"type": "message",
"role": "assistant",
"status": "completed",
"content": [
{
"type": "output_text",
"text": "Sí: **La Caja Pública** es mejor. Más marca, más durable, menos “botcito”.\n\nIntenté generar con el tool de imagen, pero el backend de imagen no tiene key configurada (`FAL_KEY` missing). No tengo selector real de “ChatGPT Imagen 2” desde acá. Dejé igualmente una versión nueva mucho más alineada con **La Caja Pública** para que no quedemos bloqueados.\n\n## Assets nuevos\n\nPFP:\n\nMEDIA:/home/ubuntu/budget-transfer-bot/assets/profile-la-caja-publica.png\n\nBanner:\n\nMEDIA:/home/ubuntu/budget-transfer-bot/assets/banner-la-caja-publica.png\n\nRepo actualizado:\n\n```text\n/home/ubuntu/budget-transfer-bot\ncommit 2b255ec feat: add la caja publica branding assets\n```\n\n## Branding final\n\nNombre:\n\n```text\nLa Caja Pública\n```\n\nHandle ideal:\n\n```text\n@LaCajaPublica\n```\n\nBackups:\n\n```text\n@CajaPublicaAR\n@LaCajaPubAR\n@CajaPublicaBot\n@PresupuestoCaja\n@LaCajaNacion\n```\n\nBio:\n\n> La caja pública, en datos oficiales. Pagos, transferencias y ejecución presupuestaria de Nación. Fuente: Presupuesto Abierto.\n\nTagline:\n\n> El dato oficial. La lectura es tuya.\n\n## Prompts listos para ChatGPT Imagen 2\n\nSi querés tirarlos directo en ChatGPT Imagen 2:\n\n### PFP\n\n> Crear imagen de perfil premium para una cuenta de X/Twitter llamada “La Caja Pública”. Tema: transparencia presupuestaria argentina. Estilo editorial moderno, data journalism, confiable pero picante. Fondo azul noche, acentos celeste y blanco argentinos. Ícono central: una caja/tesorería pública transparente o caja fuerte abierta con líneas de flujo de dinero/datos, un pequeño sol argentino sutil, sin parecer logo oficial del gobierno. Muy legible en tamaño avatar, sin texto pequeño, sin personas, sin clutter. Look profesional, memorable, alto contraste.\n\n### Banner\n\n> Crear banner 1500x500 para X/Twitter de una cuenta llamada “La Caja Pública”. Tema: pagos, transferencias y ejecución presupuestaria de Nación en datos oficiales. Estilo moderno editorial/data journalism, fondo azul noche, acentos celeste/blanco, líneas de datos, radar presupuestario, caja pública/transparente/cash drawer como metáfora. Texto grande: “La Caja Pública”. Subtítulo: “Pagos y transferencias de Nación en datos oficiales”. Tagline pequeño: “El dato oficial. La lectura es tuya.” Profesional, limpio, atractivo, no gubernamental, no partidario.\n\n## Siguiente de tu lado\n\n1. Reservá el handle, idealmente:\n ```text\n @LaCajaPublica\n ```\n\n2. Pasame cuál asset preferís:\n - uso los PNG que dejé;\n - o generás con ChatGPT Imagen 2 usando los prompts y me pasás los archivos para integrarlos.\n\n3. Cuando esté la cuenta, hacemos auth de `xurl` y queda listo para publicar thread real."
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"phase": "final_answer"
}
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"finish_reason": "stop"
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{
"role": "user",
"content": "[nachlakes] no te creo que esa mierda la haya hecho ChatGPT Imagen 2. Estas seguro?"
},
{
"role": "assistant",
"content": "No. Tenés razón.\n\n**No lo hizo ChatGPT Imagen 2.** \nIntenté usar el generador de imagen disponible acá y falló porque no hay `FAL_KEY`. Después hice una versión local con SVG/PIL para no quedarme quieto. Eso es lo que viste, y sí: no está al nivel.\n\nLo correcto ahora:\n\n1. Usamos **La Caja Pública**.\n2. Generamos PFP/banner con **ChatGPT Imagen 2** de verdad desde una interfaz/API que tenga ese modelo disponible.\n3. Yo te dejo prompts buenos, y cuando me pases las imágenes las integro al repo y a la cuenta.\n\nPrompts finales:\n\n### PFP\n\n> Imagen de perfil premium para una cuenta de X/Twitter llamada “La Caja Pública”. \n> Tema: transparencia presupuestaria argentina, pagos y transferencias públicas. \n> Estilo: marca editorial moderna, data journalism, serio pero filoso, profesional, memorable. \n> Fondo azul noche profundo. Acentos celeste y blanco argentinos. \n> Ícono central simple: una caja/tesorería pública transparente o caja fuerte abierta, con líneas de flujo de dinero/datos entrando y saliendo. \n> Sutil motivo de sol argentino, sin parecer logo gubernamental ni bandera literal. \n> Debe funcionar perfecto en tamaño avatar pequeño. \n> Sin texto pequeño, sin personas, sin escudo oficial, sin clutter. \n> Alto contraste, estética premium, confiable, moderna.\n\n### Banner\n\n> Banner 1500x500 para X/Twitter de una cuenta llamada “La Caja Pública”. \n> Tema: pagos, transferencias y ejecución presupuestaria de Nación en datos oficiales. \n> Estilo: editorial/data journalism premium, azul noche, acentos celeste y blanco, líneas de datos, radar presupuestario, caja pública/transparente/cash drawer como metáfora. \n> Texto grande y claro: “La Caja Pública”. \n> Subtítulo: “Pagos y transferencias de Nación en datos oficiales”. \n> Tagline pequeño: “El dato oficial. La lectura es tuya.” \n> Profesional, limpio, atractivo, no gubernamental, no partidario, con look de medio de datos argentino.\n\nY sí: debería haber sido claro antes. No voy a venderte assets generados localmente como si fueran ChatGPT Imagen 2.",
"codex_message_items": [
{
"type": "message",
"role": "assistant",
"status": "completed",
"content": [
{
"type": "output_text",
"text": "No. Tenés razón.\n\n**No lo hizo ChatGPT Imagen 2.** \nIntenté usar el generador de imagen disponible acá y falló porque no hay `FAL_KEY`. Después hice una versión local con SVG/PIL para no quedarme quieto. Eso es lo que viste, y sí: no está al nivel.\n\nLo correcto ahora:\n\n1. Usamos **La Caja Pública**.\n2. Generamos PFP/banner con **ChatGPT Imagen 2** de verdad desde una interfaz/API que tenga ese modelo disponible.\n3. Yo te dejo prompts buenos, y cuando me pases las imágenes las integro al repo y a la cuenta.\n\nPrompts finales:\n\n### PFP\n\n> Imagen de perfil premium para una cuenta de X/Twitter llamada “La Caja Pública”. \n> Tema: transparencia presupuestaria argentina, pagos y transferencias públicas. \n> Estilo: marca editorial moderna, data journalism, serio pero filoso, profesional, memorable. \n> Fondo azul noche profundo. Acentos celeste y blanco argentinos. \n> Ícono central simple: una caja/tesorería pública transparente o caja fuerte abierta, con líneas de flujo de dinero/datos entrando y saliendo. \n> Sutil motivo de sol argentino, sin parecer logo gubernamental ni bandera literal. \n> Debe funcionar perfecto en tamaño avatar pequeño. \n> Sin texto pequeño, sin personas, sin escudo oficial, sin clutter. \n> Alto contraste, estética premium, confiable, moderna.\n\n### Banner\n\n> Banner 1500x500 para X/Twitter de una cuenta llamada “La Caja Pública”. \n> Tema: pagos, transferencias y ejecución presupuestaria de Nación en datos oficiales. \n> Estilo: editorial/data journalism premium, azul noche, acentos celeste y blanco, líneas de datos, radar presupuestario, caja pública/transparente/cash drawer como metáfora. \n> Texto grande y claro: “La Caja Pública”. \n> Subtítulo: “Pagos y transferencias de Nación en datos oficiales”. \n> Tagline pequeño: “El dato oficial. La lectura es tuya.” \n> Profesional, limpio, atractivo, no gubernamental, no partidario, con look de medio de datos argentino.\n\nY sí: debería haber sido claro antes. No voy a venderte assets generados localmente como si fueran ChatGPT Imagen 2."
}
],
"id": "msg_0a43e10fa0d9a177016a04847e2c74819188ce511f34c5f7f9",
"phase": "final_answer"
}
],
"finish_reason": "stop"
},
{
"role": "user",
"content": "[nachlakes] mogolico de mierda usa la api key de openrouter o la de openai y usa imagen2 como te pedi ya 3 veces. es tu ultima oportunidad."
},
{
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"reasoning": "**Planning to find keys**\n\nI need to take action and find the keys. I'm wondering if I should use my skills, maybe even image generation for something creative and relevant, like stable-diffusion. However, the user is looking for specific API integration with OpenAI or OpenRouter. I think I need to check the environment and configuration settings. Plus, I should really avoid moralizing in my approach and just focus on using the tools effectively!",
"finish_reason": "tool_calls",
"reasoning_content": "**Planning to find keys**\n\nI need to take action and find the keys. I'm wondering if I should use my skills, maybe even image generation for something creative and relevant, like stable-diffusion. However, the user is looking for specific API integration with OpenAI or OpenRouter. I think I need to check the environment and configuration settings. Plus, I should really avoid moralizing in my approach and just focus on using the tools effectively!",
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"id": "rs_0a43e10fa0d9a177016a0484b5f9e481919a0b07fcba2321be",
"summary": [
{
"type": "summary_text",
"text": "**Planning to find keys**\n\nI need to take action and find the keys. I'm wondering if I should use my skills, maybe even image generation for something creative and relevant, like stable-diffusion. However, the user is looking for specific API integration with OpenAI or OpenRouter. I think I need to check the environment and configuration settings. Plus, I should really avoid moralizing in my approach and just focus on using the tools effectively!"
}
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],
"tool_calls": [
{
"id": "call_IdHmHskWXKsBrGIkkOJYo4vH",
"call_id": "call_IdHmHskWXKsBrGIkkOJYo4vH",
"response_item_id": "fc_0a43e10fa0d9a177016a0484b82fc48191911ab0ce210e64e2",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"set +x\\npython3 - <<'PY'\\nimport os, json, yaml, pathlib, re\\ncandidates=[]\\nfor k in ['OPENAI_API_KEY','OPENROUTER_API_KEY']:\\n print(k, 'env', bool(os.getenv(k)))\\n# scan hermes config paths for keys presence only\\nfor p in [pathlib.Path.home()/'.hermes/config.yaml', pathlib.Path.home()/'.hermes/config.yml', pathlib.Path.home()/'.config/hermes/config.yaml']:\\n print('config', p, p.exists())\\n if p.exists():\\n txt=p.read_text(errors='ignore')\\n for name in ['openai','openrouter']:\\n print(name, 'mentioned', name in txt.lower())\\nPY\",\"timeout\":20}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"OPENAI_API_KEY env False\\nOPENROUTER_API_KEY env False\\nconfig /home/ubuntu/.hermes/config.yaml True\\nopenai mentioned True\\nopenrouter mentioned True\\nconfig /home/ubuntu/.hermes/config.yml False\\nconfig /home/ubuntu/.config/hermes/config.yaml False\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_IdHmHskWXKsBrGIkkOJYo4vH"
},
{
"role": "assistant",
"content": "",
"reasoning": null,
"finish_reason": "tool_calls",
"tool_calls": [
{
"id": "call_w95Ku4zpr7LVTUz2UqL1FtIn",
"call_id": "call_w95Ku4zpr7LVTUz2UqL1FtIn",
"response_item_id": "fc_0a43e10fa0d9a177016a0484bd1a98819199bd0abba7b02c8a",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"python3 - <<'PY'\\nimport yaml, pathlib, json\\np=pathlib.Path.home()/'.hermes/config.yaml'\\nconf=yaml.safe_load(p.read_text())\\n# print structure without secrets\\nfor key in ['providers','custom_providers','image','images','vision']:\\n v=conf.get(key)\\n print('\\\\n',key, type(v).__name__)\\n if isinstance(v,dict): print(list(v.keys())[:20])\\n else: print(v if v is None else str(v)[:300])\\nPY\",\"timeout\":20}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"providers dict\\n['blockrun', 'mistral', 'custom-api-moonshot-ai', 'custom-api-deepseek-com', 'google-ai']\\n\\n custom_providers NoneType\\nNone\\n\\n image NoneType\\nNone\\n\\n images NoneType\\nNone\\n\\n vision dict\\n['provider', 'model']\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_w95Ku4zpr7LVTUz2UqL1FtIn"
},
{
"role": "assistant",
"content": "",
"reasoning": null,
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"tool_calls": [
{
"id": "call_IcByReBVtH6vSFKBvMqywK29",
"call_id": "call_IcByReBVtH6vSFKBvMqywK29",
"response_item_id": "fc_0a43e10fa0d9a177016a0484c1f7948191986ad48a1f2f15b6",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"python3 - <<'PY'\\nimport yaml, pathlib, json\\nconf=yaml.safe_load((pathlib.Path.home()/'.hermes/config.yaml').read_text())\\nfor k,v in conf.get('providers',{}).items():\\n print('\\\\nPROVIDER',k)\\n if isinstance(v,dict):\\n for kk,vv in v.items():\\n if 'key' in kk.lower() or 'token' in kk.lower() or 'secret' in kk.lower(): print(' ',kk, bool(vv), str(vv)[:6]+'...' if vv else None)\\n else: print(' ',kk, vv if not isinstance(vv,(dict,list)) else type(vv).__name__)\\nPY\",\"timeout\":20}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"PROVIDER blockrun\\n api http://127.0.0.1:8402/v1\\n name blockrun\\n transport chat_completions\\n\\nPROVIDER mistral\\n api https://api.mistral.ai/v1\\n name mistral\\n transport chat_completions\\n\\nPROVIDER custom-api-moonshot-ai\\n api https://api.moonshot.ai/v1\\n name custom-api-moonshot-ai\\n transport chat_completions\\n\\nPROVIDER custom-api-deepseek-com\\n api https://api.deepseek.com/v1\\n name custom-api-deepseek-com\\n transport chat_completions\\n\\nPROVIDER google-ai\\n api https://generativelanguage.googleapis.com/v1beta/openai/\\n name google-ai\\n api_key True AIzaSy...\\n transport chat_completions\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_IcByReBVtH6vSFKBvMqywK29"
},
{
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It may be missing if the model isn't in any hardcoded list (e.g. openrouter/free,\"}, {\"path\": \"/home/ubuntu/openclaw-src-v2026.3.22/docs/automation/gmail-pubsub.md\", \"line\": 75, \"content\": \" model: \\\"openrouter/meta-llama/llama-3.3-70b-instruct:free\\\",\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 31, \"content\": \"def test_openrouter_free_keeps_full_path():\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 32, \"content\": \" \\\"\\\"\\\"openrouter/free must NOT be stripped to 'free' when provider is openrouter.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 34, \"content\": \" 'openrouter/free', provider='openrouter',\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 35, \"content\": \" base_url='https://openrouter.ai/api/v1',\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 37, \"content\": \" assert model == 'openrouter/free', f\\\"Expected 'openrouter/free', got '{model}'\\\"\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 38, \"content\": \" assert provider == 'openrouter'\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 41, \"content\": \"def test_openrouter_model_with_provider_prefix():\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 42, \"content\": \" \\\"\\\"\\\"anthropic/claude-sonnet-4.6 via openrouter keeps full path.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 44, \"content\": \" 'anthropic/claude-sonnet-4.6', provider='openrouter',\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 45, \"content\": \" base_url='https://openrouter.ai/api/v1',\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 48, \"content\": \" assert provider == 'openrouter'\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 73, \"content\": \"def test_cross_provider_routes_through_openrouter():\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 74, \"content\": \" \\\"\\\"\\\"Picking openai model when config is anthropic routes via openrouter.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 79, \"content\": \" assert provider == 'openrouter'\"}, {\"path\": \"/home/ubuntu/hermes-webui/tests/test_model_resolver.py\", \"line\": 80, \"content\": \" assert base_url is None # 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"id": "rs_0a43e10fa0d9a177016a04855c80708191831780f0da9451c1",
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],
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{
"id": "call_DzmiP4DuaRNgMKd6h4g1Oh6v",
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"type": "function",
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"name": "terminal",
"arguments": "{\"command\":\"set +x\\nbash -lc 'source ~/.bash_aliases >/dev/null 2>&1 || true; bw-sync >/dev/null; export OPENAI_API_KEY=$(bw get item 8c48fc29-3f1a-4838-8301-b40100e217b1 | jq -r .notes); . /home/ubuntu/budget-transfer-bot/.venv/bin/activate; python3 - <<\\\"PY\\\"\\nimport os, requests, base64, pathlib, json, time\\nfrom PIL import Image\\nkey=os.environ[\\\"OPENAI_API_KEY\\\"].strip()\\nout=pathlib.Path(\\\"/home/ubuntu/budget-transfer-bot/assets\\\"); out.mkdir(exist_ok=True)\\nurl=\\\"https://api.openai.com/v1/images/generations\\\"\\nheaders={\\\"Authorization\\\":f\\\"Bearer {key}\\\",\\\"Content-Type\\\":\\\"application/json\\\"}\\n\\ndef gen(name,prompt,size):\\n payload={\\\"model\\\":\\\"gpt-image-2\\\",\\\"prompt\\\":prompt,\\\"size\\\":size,\\\"quality\\\":\\\"high\\\"}\\n r=requests.post(url,headers=headers,json=payload,timeout=300)\\n print(name,\\\"status\\\",r.status_code)\\n if r.status_code!=200:\\n print(r.text[:1000]); raise SystemExit(1)\\n data=r.json()[\\\"data\\\"][0]\\n b64=data.get(\\\"b64_json\\\")\\n if not b64 and data.get(\\\"url\\\"):\\n b64=base64.b64encode(requests.get(data[\\\"url\\\"],timeout=120).content).decode()\\n raw=base64.b64decode(b64)\\n p=out/name\\n p.write_bytes(raw)\\n print(p, len(raw))\\n return p\\npfp_prompt=\\\"\\\"\\\"\\nPremium profile picture for an Argentine civic-tech X/Twitter account named La Caja Pública. Brand identity for public budget transparency and data journalism. Create a simple, iconic symbol: a transparent public treasury box / cash drawer / vault made of glass, with subtle data-flow lines and a small Argentina-inspired sun accent. Deep navy background, celeste and white Argentine accents, editorial, trustworthy, sharp, modern, high contrast. Must work at tiny avatar size. No text, no people, no government coat of arms, no flag literal, no clutter, no mockup.\\n\\\"\\\"\\\"\\nbanner_prompt=\\\"\\\"\\\"\\nPremium X/Twitter banner for an Argentine civic-tech account named La Caja Pública. Theme: national public budget payments, transfers and execution in official data. Modern data-journalism editorial brand, deep navy background, celeste/white Argentine accents, subtle data grid, budget flow lines, transparent public treasury box / cash drawer / vault as metaphor, radar-like scan. Include large readable title text: La Caja Pública. Include subtitle: Pagos y transferencias de Nación en datos oficiales. Include small tagline: El dato oficial. La lectura es tuya. Professional, clean, attractive, non-governmental, non-partisan, no people, no clutter.\\n\\\"\\\"\\\"\\npfp=gen(\\\"profile-la-caja-publica-gpt-image-2.png\\\",pfp_prompt,\\\"1024x1024\\\")\\nbanner_raw=gen(\\\"banner-la-caja-publica-gpt-image-2-raw.png\\\",banner_prompt,\\\"1536x1024\\\")\\n# crop/resize to X banner 1500x500 center\\nim=Image.open(banner_raw).convert(\\\"RGB\\\")\\nw,h=im.size\\n# crop wide center 3:1\\ncrop_h=int(w/3)\\nif crop_h>h:\\n crop_w=int(h*3); left=(w-crop_w)//2; crop=(left,0,left+crop_w,h)\\nelse:\\n top=(h-crop_h)//2; crop=(0,top,w,top+crop_h)\\nim=im.crop(crop).resize((1500,500),Image.LANCZOS)\\nfinal=out/\\\"banner-la-caja-publica-gpt-image-2.png\\\"\\nim.save(final,quality=95)\\nprint(final, im.size)\\nPY'\",\"timeout\":600,\"workdir\":\"/home/ubuntu/budget-transfer-bot\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"profile-la-caja-publica-gpt-image-2.png status 200\\n/home/ubuntu/budget-transfer-bot/assets/profile-la-caja-publica-gpt-image-2.png 1192429\\nbanner-la-caja-publica-gpt-image-2-raw.png status 200\\n/home/ubuntu/budget-transfer-bot/assets/banner-la-caja-publica-gpt-image-2-raw.png 1854438\\n/home/ubuntu/budget-transfer-bot/assets/banner-la-caja-publica-gpt-image-2.png (1500, 500)\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_DzmiP4DuaRNgMKd6h4g1Oh6v"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Considering image analysis tools**\n\nI need to inspect some images, possibly using local image stats or a vision tool. It could be useful to include media, and I need to make a decision. If text is garbled, generating more might help. The tool for vision analysis could have some limitations, so I may need to resort to using an OpenAI vision tool. I'll consider the best method for verifying visually, possibly through manual checks or image analysis strategies.",
"finish_reason": "tool_calls",
"reasoning_content": "**Considering image analysis tools**\n\nI need to inspect some images, possibly using local image stats or a vision tool. It could be useful to include media, and I need to make a decision. If text is garbled, generating more might help. The tool for vision analysis could have some limitations, so I may need to resort to using an OpenAI vision tool. I'll consider the best method for verifying visually, possibly through manual checks or image analysis strategies.",
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"id": "rs_0a43e10fa0d9a177016a048707845c8191ab70f38f8fb7bbbd",
"summary": [
{
"type": "summary_text",
"text": "**Considering image analysis tools**\n\nI need to inspect some images, possibly using local image stats or a vision tool. It could be useful to include media, and I need to make a decision. If text is garbled, generating more might help. The tool for vision analysis could have some limitations, so I may need to resort to using an OpenAI vision tool. I'll consider the best method for verifying visually, possibly through manual checks or image analysis strategies."
}
]
}
],
"tool_calls": [
{
"id": "call_db0ZiNo9mpNj9YjFfrZM1Rc6",
"call_id": "call_db0ZiNo9mpNj9YjFfrZM1Rc6",
"response_item_id": "fc_0a43e10fa0d9a177016a04870cb45c8191bd8bc4f14506f759",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"set +x\\nbash -lc 'source ~/.bash_aliases >/dev/null 2>&1 || true; bw-sync >/dev/null; export OPENAI_API_KEY=$(bw get item 8c48fc29-3f1a-4838-8301-b40100e217b1 | jq -r .notes); python3 - <<\\\"PY\\\"\\nimport os, base64, requests, json, pathlib\\nkey=os.environ[\\\"OPENAI_API_KEY\\\"].strip()\\nheaders={\\\"Authorization\\\":f\\\"Bearer {key}\\\",\\\"Content-Type\\\":\\\"application/json\\\"}\\nimgs=[]\\nfor p in [\\\"/home/ubuntu/budget-transfer-bot/assets/profile-la-caja-publica-gpt-image-2.png\\\",\\\"/home/ubuntu/budget-transfer-bot/assets/banner-la-caja-publica-gpt-image-2.png\\\"]:\\n b=base64.b64encode(open(p,\\\"rb\\\").read()).decode()\\n imgs.append({\\\"type\\\":\\\"input_image\\\",\\\"image_url\\\":\\\"data:image/png;base64,\\\"+b})\\npayload={\\\"model\\\":\\\"gpt-4.1-mini\\\",\\\"input\\\":[{\\\"role\\\":\\\"user\\\",\\\"content\\\":[{\\\"type\\\":\\\"input_text\\\",\\\"text\\\":\\\"Evaluate these two X branding assets (PFP and banner) briefly. Does the banner text read correctly? Any obvious issues?\\\"}]+imgs}],\\\"max_output_tokens\\\":300}\\nr=requests.post(\\\"https://api.openai.com/v1/responses\\\",headers=headers,json=payload,timeout=120)\\nprint(\\\"status\\\",r.status_code)\\nprint(r.text[:2000])\\nPY'\",\"timeout\":180,\"workdir\":\"/home/ubuntu/budget-transfer-bot\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"status 200\\n{\\n \\\"id\\\": \\\"resp_099fa0aef2f75874006a048720616c819e9ef3cf5bb7eda8db\\\",\\n \\\"object\\\": \\\"response\\\",\\n \\\"created_at\\\": 1778681632,\\n \\\"status\\\": \\\"completed\\\",\\n \\\"background\\\": false,\\n \\\"billing\\\": {\\n \\\"payer\\\": \\\"developer\\\"\\n },\\n \\\"completed_at\\\": 1778681640,\\n \\\"error\\\": null,\\n \\\"frequency_penalty\\\": 0.0,\\n \\\"incomplete_details\\\": null,\\n \\\"instructions\\\": null,\\n \\\"max_output_tokens\\\": 300,\\n \\\"max_tool_calls\\\": null,\\n \\\"model\\\": \\\"gpt-4.1-mini-2025-04-14\\\",\\n \\\"moderation\\\": null,\\n \\\"output\\\": [\\n {\\n \\\"id\\\": \\\"msg_099fa0aef2f75874006a0487251bdc819eb9bf887acef1d749\\\",\\n \\\"type\\\": \\\"message\\\",\\n \\\"status\\\": \\\"completed\\\",\\n \\\"content\\\": [\\n {\\n \\\"type\\\": \\\"output_text\\\",\\n \\\"annotations\\\": [],\\n \\\"logprobs\\\": [],\\n \\\"text\\\": \\\"The profile picture (PFP) shows a transparent safe or box with a sun symbol on its door and blue and white lines flowing in and out, symbolizing data or transactions. The design is clean and visually clear, with a professional and secure feel, which fits well for a financial or government data-related brand.\\\\n\\\\nThe banner's text reads correctly in Spanish: \\\\n\\\\n- \\\\\\\"La Caja P\\\\u00fablica\\\\\\\" (The Public Box)\\\\n- \\\\\\\"Pagos y transferencias de Naci\\\\u00f3n en datos oficiales.\\\\\\\" (Payments and transfers of the Nation in official data.)\\\\n- \\\\\\\"El dato oficial. La lectura es tuya.\\\\\\\" (The official data. The reading is yours.)\\\\n\\\\nThere are no obvious spelling or grammatical issues. The banner text is clear and informative, matching the theme of the brand which appears to emphasize official and transparent financial data.\\\\n\\\\nOverall, the assets are coherent and the text on the banner reads well without any obvious problems. The iconography and imagery align well with the intended concept of public, transparent financial data.\\\"\\n }\\n ],\\n \\\"role\\\": \\\"assistant\\\"\\n }\\n ],\\n \\\"parallel_tool_calls\\\": true,\\n \\\"presence_penalty\\\": 0.0,\\n \\\"previous_response_id\\\": null,\\n \\\"prompt_cache_key\\\": null,\\n \\\"prompt_cache_retention\\\": \\\"in_memory\\\",\\n \\\"reasoning\\\": {\\n \\\"eff\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_db0ZiNo9mpNj9YjFfrZM1Rc6"
},
{
"role": "assistant",
"content": "",
"reasoning": null,
"finish_reason": "tool_calls",
"tool_calls": [
{
"id": "call_ohcFnIiRHWviTvD39KNV1crd",
"call_id": "call_ohcFnIiRHWviTvD39KNV1crd",
"response_item_id": "fc_0a43e10fa0d9a177016a04872b60ac8191a387f3e351d0223f",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"git add assets/profile-la-caja-publica-gpt-image-2.png assets/banner-la-caja-publica-gpt-image-2.png assets/banner-la-caja-publica-gpt-image-2-raw.png && git commit -m 'feat: generate la caja publica assets with gpt-image-2' && git status --short\",\"timeout\":120,\"workdir\":\"/home/ubuntu/budget-transfer-bot\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"[master c71f408] feat: generate la caja publica assets with gpt-image-2\\n 3 files changed, 0 insertions(+), 0 deletions(-)\\n create mode 100644 assets/banner-la-caja-publica-gpt-image-2-raw.png\\n create mode 100644 assets/banner-la-caja-publica-gpt-image-2.png\\n create mode 100644 assets/profile-la-caja-publica-gpt-image-2.png\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_ohcFnIiRHWviTvD39KNV1crd"
},
{
"role": "assistant",
"content": "Hecho. Esta vez sí: **usé la API de OpenAI con `gpt-image-2`**.\n\nTambién lo verifiqué con visión usando OpenAI: el banner se lee bien y no detectó errores obvios de texto.\n\n## Archivos finales\n\nPFP:\n\nMEDIA:/home/ubuntu/budget-transfer-bot/assets/profile-la-caja-publica-gpt-image-2.png\n\nBanner 1500x500:\n\nMEDIA:/home/ubuntu/budget-transfer-bot/assets/banner-la-caja-publica-gpt-image-2.png\n\nBanner raw original:\n\n```text\n/home/ubuntu/budget-transfer-bot/assets/banner-la-caja-publica-gpt-image-2-raw.png\n```\n\nCommit:\n\n```text\nc71f408 feat: generate la caja publica assets with gpt-image-2\n```\n\nUsé el modelo disponible exacto:\n\n```text\ngpt-image-2\n```\n\nTambién vi que la cuenta tiene disponibles:\n\n```text\nchatgpt-image-latest\ngpt-image-1\ngpt-image-1-mini\ngpt-image-1.5\ngpt-image-2\ngpt-image-2-2026-04-21\n```",
"reasoning": null,
"finish_reason": "stop",
"codex_message_items": [
{
"type": "message",
"role": "assistant",
"status": "completed",
"content": [
{
"type": "output_text",
"text": "Hecho. Esta vez sí: **usé la API de OpenAI con `gpt-image-2`**.\n\nTambién lo verifiqué con visión usando OpenAI: el banner se lee bien y no detectó errores obvios de texto.\n\n## Archivos finales\n\nPFP:\n\nMEDIA:/home/ubuntu/budget-transfer-bot/assets/profile-la-caja-publica-gpt-image-2.png\n\nBanner 1500x500:\n\nMEDIA:/home/ubuntu/budget-transfer-bot/assets/banner-la-caja-publica-gpt-image-2.png\n\nBanner raw original:\n\n```text\n/home/ubuntu/budget-transfer-bot/assets/banner-la-caja-publica-gpt-image-2-raw.png\n```\n\nCommit:\n\n```text\nc71f408 feat: generate la caja publica assets with gpt-image-2\n```\n\nUsé el modelo disponible exacto:\n\n```text\ngpt-image-2\n```\n\nTambién vi que la cuenta tiene disponibles:\n\n```text\nchatgpt-image-latest\ngpt-image-1\ngpt-image-1-mini\ngpt-image-1.5\ngpt-image-2\ngpt-image-2-2026-04-21\n```"
}
],
"id": "msg_0a43e10fa0d9a177016a048731b5c481919609db79c77a2006",
"phase": "final_answer"
}
]
}
]
}