{
  "session_id": "20260512_161415_072b34",
  "model": "gpt-5.5",
  "base_url": "https://chatgpt.com/backend-api/codex",
  "platform": "discord",
  "session_start": "2026-05-12T16:14:15.530138",
  "last_updated": "2026-05-12T16:16:25.788990",
  "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. 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. 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<tool_persistence>\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</tool_persistence>\n\n<mandatory_tool_use>\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</mandatory_tool_use>\n\n<act_dont_ask>\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</act_dont_ask>\n\n<prerequisite_checks>\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</prerequisite_checks>\n\n<verification>\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</verification>\n\n<missing_context>\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</missing_context>\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) [96% — 1,325/1,375 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 muy breves/directas; límites claros en Discord/plataformas.\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\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<available_skills>\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 + specialist-roster conventions + ...\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, and create 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    - 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  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</available_skills>\n\nOnly proceed without loading a skill if genuinely none are relevant to the task.\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\nConversation started: Tuesday, May 12, 2026 04:14 PM\nModel: gpt-5.5\nProvider: openai-codex\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 ![alt](url) and they will be sent as attachments.",
  "tools": [
    {
      "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": "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=<umbrella>` 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 off-limits — all write actions refuse with a message pointing the user to `hermes curator unpin <name>`. Don't try to route around this by renaming or recreating.",
        "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": "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": 66,
  "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!",
      "codex_reasoning_items": [
        {
          "type": "reasoning",
          "encrypted_content": "gAAAAABqAzyCYYIeHQdELAmAusJQpgbuv2LLO9eXw5-yYdpM-d9I0YNQQ_IDIjravtlGhFnpTNUK5tVfdx4-s7h8iqsNA_DOV4JEDX3uUGz7hKLv-rCVApGSSBn1UzM3_H6siCnsdv7au5XxvTSRUW8Mnv36y4rt7o1iCF3G2eud63iAwblNIzT-rxhHrqycUozNkZwxZEjjICzw2W5_NEdM12dEMeniltMXBLlFlht3N0be2U-aRXf8tAGxLgBJREExSSSYUoBHEO-130EZ6lDBhjNZ89z6p24OuojBgJsOVqHR7tbRZb-GM6OT7dR-f04uVenf4GifdLySr9IkCEPg_o6VmC-mWJRnyrDOsBXypZnmUb-TimG1B3UXO0v-4XZFJtQvSDzKhsQkr90iR3VGkR5QvqD_ajPH2vrFyT-5cgF0gSfE8o8N3uD9wmbxVCXEuo6lIOFSYHRYcVDuRCL8O87fibJaUV-0NRIwd7nRDw3eHWPfua_x6V5bdzAwKFR3B7hNcb3dtYgukaZrnTT1s8g2HhTadh6s_IgI-iRArQMBrES6wwwHjdXRxk1t_Gp0RYsXz-nUwhiLqSRDheUyWJpncXBG0cq8Er-7PYoPa-LnP8Mrf9IdoTp1NzXskKPaC1Y5KjPRt6oOQLJXwIexHcUuTL01Ok0wl6aL-HtQgsPTqk_VIAKUfpgCDFLIXHBCO0Ene7iVQLW620xS9Qn7nWYKH1GnReWQk4fTYfUEq4oGpqWx_rAux9eXbN1t1vNHqwLiQUWON_9Jmwf8gob0oH0R7IlyCZxAmgxEpB75y0bMG6IepHyEnD7exm1n9JO4PZDlp5zmb_p4lE3Rfwvj2wIouXHqYkb216W8t8QILF6Rt9QTnBnA3lmp2LdDrClbYcYgMo9tdQ2QDdwRKtCQjSTOvVLdDvfFU7wognKHnSCEGXuAR8PY3xPzSXDWQGfpvoM2Kvp__buEh8TjOSFZmo_elCIutFa88DIjLxyi5VdeekuRUBystAI8wkuzpoEHguCLopOWksJlDinEEFniD5BqvMhA1g==",
          "id": "rs_0965b568e0b96b22016a033c7ec66881918440002e564d695e",
          "summary": [
            {
              "type": "summary_text",
              "text": "**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!"
            }
          ]
        }
      ]
    },
    {
      "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. 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:\n## Active Task\nUser asked: “[nachlakes] y te podes fijar si podes hacerlo completo completo de principio a fin? dame factos factos. que onda la parte delicada? te voy a dar un poco mas de thinking para que puedas investigar a fondo lo que podemos hacer con esto. me gusta la idea y si la gente la pide debe ser algo que la gente quiere. Hace una investigacion completa y fijate que es lo que la gente quiere ver, y arma un reporte ejecutivo de factibilidad, gracias.”\n\n## Goal\nEl usuario quiere evaluar si se puede construir de punta a punta un bot/producto de transparencia pública que publique automáticamente en X/Twitter cada vez que se registren transferencias del Gobierno Nacional argentino a provincias, universidades, municipios, fondos fiduciarios, etc., incluyendo monto, fecha, destino, ítem presupuestario, acumulado anual y porcentaje ejecutado vs presupuesto anual. Quiere un reporte ejecutivo de factibilidad con “factos factos”, identificación de la “parte delicada”, demanda/expectativas de usuarios, fuentes oficiales, arquitectura MVP, riesgos y recomendación.\n\n## Constraints & Preferences\n- Responder en español rioplatense/informal pero claro, como venía la conversación.\n- El usuario pidió “factos factos”: evitar humo; usar evidencia concreta, fuentes oficiales, ejemplos reales y caveats técnicos.\n- El usuario quiere investigación “completa de principio a fin”, no solo idea general.\n- El producto deseado es principalmente bot de X/Twitter, pero se mencionó también posible web/dashboard/histórico.\n- Mantener foco en Argentina, Presupuesto Abierto, datos.gob.ar, Ministerio de Economía, transferencias de Nación.\n- No prometer “transferencia bancaria individual en tiempo real” si los datos no lo permiten.\n- Diferenciar claramente:\n  - ejecución presupuestaria/devengado/pagado,\n  - transferencias presupuestarias inciso 5,\n  - coparticipación/transferencias automáticas a provincias,\n  - transferencias no automáticas/discrecionales,\n  - nivel de agregación presupuestaria vs beneficiario final.\n- Si se habla de X/Twitter API, aclarar que publicar automáticamente requiere Developer Account y probablemente plan pago; confirmar precios actuales antes de implementar.\n- No incluir credenciales/secrets. No hubo valores de credenciales preservables; si aparecieran, reemplazar por `[REDACTED]`.\n\n## Completed Actions\n1. ABRIÓ tweet original `https://x.com/__microdancing/status/2054160914438291840` — navegación directa tuvo limitaciones de acceso/rendering [tool: browser_navigate].\n2. CONSULTÓ skill `xurl` — se abrió documentación del skill para leer contenido de X/Twitter, pero el binario/comando no estaba disponible luego [tool: skill_view].\n3. EJECUTÓ `xurl read 2054160914438291840` — falló con `/usr/bin/bash: line 3: xurl: command not found`, exit code 127 [tool: terminal].\n4. BUSCÓ web por `\"2054160914438291840\" OR \"__microdancing\"` — encontró resultados amplios, no permitió reconstruir replies/quotes completos de forma confiable [tool: web_search].\n5. INTENTÓ Twitter oEmbed `https://publish.twitter.com/oembed?url=https://x.com/__microdancing/status/2054160914438291840` — inaccesible/not found [tool: web_extract].\n6. INTENTÓ endpoint syndication `https://cdn.syndication.twimg.com/tweet-result?id=2054160914438291840&lang=en` — HTTP 200 pero devolvió `{}`, sin contenido [tool: terminal].\n7. PROBÓ APIs alternativas `api.fxtwitter.com`, `api.vxtwitter.com`, `api.fixupx.com` para el status — salida truncada/limitada; no se recuperaron replies ni quote tweets confiables [tool: terminal].\n8. BUSCÓ fuente oficial de datos con queries sobre Presupuesto Abierto/API/transferencias — ubicó Presupuesto Abierto y datasets de Administración Pública Nacional como fuente principal [tool: web_search].\n9. EXTRAJO páginas oficiales:\n   - `https://www.presupuestoabierto.gob.ar/api/`\n   - `https://www.presupuestoabierto.gob.ar/sici/datos-abiertos`\n   - `https://www.presupuestoabierto.gob.ar/sici/ejecucion-presup-de-las-transferencias`\n   Resultado: páginas con documentación/datos abiertos pero extracción limitada [tool: web_extract].\n10. INSPECCIONÓ HTML/API de Presupuesto Abierto con Python/requests — encontró esquemas JSON como `https://www.presupuestoabierto.gob.ar/api/jsonCredito`, pero API POST requiere Authorization [tool: terminal].\n11. CONSULTÓ schema `jsonCredito` — confirmó existencia de estructura de consulta con campos/definiciones, operadores, filtros, etc. [tool: terminal].\n12. PROBÓ query POST al endpoint de crédito de Presupuesto Abierto — devolvió `401 application/json;charset=ISO-8859-1 {\"statusCode\":401,\"message\":\"Debe indicar el header Authorization en la petición\",\"detail\":\"\"}`. Conclusión: API interactiva no es usable anónimamente sin header Authorization [tool: terminal].\n13. BUSCÓ CKAN/datos.gob.ar `presupuesto abierto credito gasto` — identificó datasets de `sspre-presupuesto-administracion-publica-nacional` y recursos relacionados [tool: terminal].\n14. CONSULTÓ package `sspre-presupuesto-administracion-publica-nacional` y variantes por año — se detectaron recursos/datasets de crédito por año, incluyendo 2026 [tool: terminal].\n15. DESCARGÓ dataset oficial `https://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/credito-diario-2026.zip` — HTTP 200, `application/zip`, tamaño aprox. 11 MB, usable públicamente sin auth [tool: terminal].\n16. ABRIÓ ZIP `credito-diario-2026.zip` con Python — confirmó CSV interno y columnas útiles: `impacto_presupuestario_fecha`, `jurisdiccion_desc`, `entidad_desc`, `programa_desc`, `inciso_desc`, `principal_desc`, `parcial_desc`, `subparcial_desc`, `ubicacion_geografica_desc`, `credito_devengado`, `credito_pagado`, `ultima_actualizacion_fecha`, etc. [tool: terminal].\n17. FILTRÓ dataset 2026 por `inciso_id = 5` — confirmó que inciso 5 corresponde a “Transferencias” y hay filas reales para publicar [tool: terminal].\n18. RESPONDIÓ primera factibilidad: sí, MVP factible en 1–2 días; caveat principal: no son transferencias bancarias individuales en tiempo real sino ejecución presupuestaria diaria agregada; propuso cron + CSV + SQLite/Postgres/Supabase + publicación X [assistant].\n19. USUARIO pidió agregar “transferido hasta ahora en 2026 vs presupuesto anual: monto o porcentaje” — se investigó viabilidad de acumulados/porcentajes [user].\n20. PROBÓ `credito-mensual-2026.zip` y comparaciones con diario — detectó que para acumulado/denominador anual conviene usar dataset anual/mensual, no solo diario, porque en diario algunas filas con pagos tienen `credito_presupuestado`/`credito_vigente` en cero [tool: terminal].\n21. RESPONDIÓ que el porcentaje es factible con fórmula:\n    - `porcentaje_ejecutado = credito_pagado_acumulado / credito_vigente * 100`\n    - opcional contra `credito_presupuestado`\n    Recomendó usar `credito_vigente` como denominador principal [assistant].\n22. CREÓ TODO list de investigación para reporte ejecutivo:\n    - recuperar tweet/replies/demanda,\n    - auditar fuentes oficiales,\n    - probar pipeline real,\n    - diseñar MVP end-to-end,\n    - entregar reporte [tool: todo].\n23. LANZÓ tareas delegadas para investigar:\n    - fuentes oficiales de presupuesto,\n    - demanda/expectativas de usuarios,\n    - arquitectura end-to-end del bot/dashboard [tool: delegate_task].\n24. CONSULTÓ fecha/hora ambiente — salida:\n    - `2026-05-12 15:10:32 UTC`\n    - `2026-05-12 12:10:32 -03`\n    Esto importa porque los datasets de 2026 están disponibles hasta mayo 2026 en el entorno [tool: terminal].\n25. BUSCÓ precios/planes de X API 2026 con varias queries — resultados de búsqueda indican que hay restricciones/precios; no se consolidó precio exacto en respuesta final todavía. Debe verificarse antes de afirmar montos [tool: web_search].\n26. BUSCÓ nuevamente contenido/replies del tweet con `api.fxtwitter.com` y endpoints `/replies` — no se obtuvieron replies/quotes completos confiables; hay que basar demanda en señales indirectas o aclarar limitación [tool: terminal].\n27. BUSCÓ web por frases del tweet:\n    - `\"hay que hacer un bot\" \"transferencia del gobierno nacional\"`\n    - `\"transferencias\" \"provincias\" \"universidades\" \"bot\" \"Presupuesto Abierto\"`\n    - `\"transferencias a universidades nacionales\" \"Presupuesto Abierto\" \"Twitter\" OR \"X\"`\n    - `\"Presupuesto Abierto\" \"bot\" \"Twitter\" Argentina presupuesto`\n    Resultado: hay interés general en transparencia/transferencias y casos análogos, pero no evidencia cuantitativa robusta de demanda específica salvo tweet inicial/señales indirectas [tool: web_search].\n28. EXTRAJO páginas:\n    - `https://www.presupuestoabierto.gob.ar/sici/que-incluye`\n    - `https://www.presupuestoabierto.gob.ar/sici/acerca-de`\n    - `https://www.presupuestoabierto.gob.ar/sici/analisis-transversales-home`\n    - `https://github.com/jazzido/pautabot`\n    - `https://opc.gob.ar/provincias/`\n    Resultado: confirmó contexto de Presupuesto Abierto y existencia de proyectos tipo bot/transparencia como `pautabot` (bot de pauta oficial) como antecedente conceptual [tool: web_extract].\n29. EXTRAJO docs no oficiales/relacionadas:\n    - `https://presupuesto-abierto.argentina.apidocs.ar/`\n    - `https://presupuesto-abierto.argentina.apidocs.ar/operations/post-credito`\n    - `https://www.presupuestoabierto.gob.ar/sici/api-pac`\n    - `https://www.datos.gob.ar/apis`\n    - `https://www.presupuestoabierto.gob.ar/sici/datos-abiertos`\n    Resultado: confirmó que hay documentación/API, aunque el endpoint oficial de crédito probado requiere Authorization [tool: web_extract].\n30. INVESTIGÓ fuentes de coparticipación/transferencias automáticas:\n    - Búsquedas sobre DNAP, coparticipación, transferencias automáticas provincias, CSV/API [tool: web_search].\n31. EXTRAJO página `https://www.argentina.gob.ar/economia/sechacienda/asuntosprovinciales/ron` — encontró links a archivos diarios/mensuales/anuales de “Recursos de Origen Nacional” (RON) para coparticipación/transferencias automáticas a provincias:\n    - `internet_diario26_4_2.xls`\n    - `internet_diario_abril26_19_1.xls`\n    - `internet_diario_mar26_22.xls`\n    - `internet_diario_feb26_22.xls`\n    - `internet_diario_ene26_21.xls`\n    - históricos `montos_diarios_ano_2024.zip`, etc.\n    - consolidados `informacion_consolidada_2026_1.xlsx`, `serie_ron_2003_2025.csv`, etc. [tool: terminal].\n32. DESCARGÓ algunos archivos RON:\n    - `https://www.argentina.gob.ar/sites/default/files/internet_diario26_4_2.xls` — HTTP 200, `application/vnd.ms-excel`, 1,138,176 bytes.\n    - `internet_diario_abril26_19_1.xls` — HTTP 200, Excel.\n    - `informacion_consolidada_2026_1.xlsx` — HTTP 200, xlsx.\n    - `serie_ron_2003_2025.csv` — HTTP 200, CSV con header `ano;provincia;impuesto;regimen;monto` y primeras filas tipo `2003;buenos aires;coparticipacion federal de impuestos ley 23548;...` [tool: execute_code].\n33. INTENTÓ leer Excel RON con pandas/openpyxl/xlrd — ambiente no tiene paquetes:\n    - `pandas False openpyxl False xlrd False`\n    - errores `ModuleNotFoundError(\"No module named 'pandas'\")`.\n    Tampoco había `libreoffice`, `ssconvert`, `in2csv` disponibles. No se parsearon Excel en profundidad [tool: terminal].\n34. PROTOTIPÓ ejemplo real de evento UBA:\n    - Fuente: `credito-diario-2026.zip`.\n    - Filtro: `inciso_id == 5`, fecha `2026-05-05 00:00:00`, `subparcial_desc == \"Universidad de Buenos Aires\"`, `credito_pagado > 0`.\n    - Encontró 3 filas:\n      1. `credito_pagado = 32455,015624` millones? / unidades presupuestarias; `Ministerio de Capital Humano`, `Secretaría de Educación`, programa `Desarrollo de la Educacion Superior`, actividad `Asistencia Financiera para el Pago de Salario del Personal no Docente`, principal `Transferencias a universidades nacionales`, parcial `... para financiar gastos corrientes`, subparcial `Universidad de Buenos Aires`, fuente `Tesoro Nacional`, ubicación `Ciudad Autónoma de Buenos Aires`.\n      2. `credito_pagado = 28449,187754`, actividad `Asistencia Financiera para el Pago de Salario Docente y Autoridades Superiores`.\n      3. `credito_pagado = 1664,038468`, actividad `Asistencia Financiera a Hospitales Universitarios`.\n    [tool: execute_code].\n35. CRUZÓ ejemplo UBA con `credito-anual-2026.zip`:\n    - Evento UBA 2026-05-05: 3 filas, suma `62568.241846` en unidades del dataset.\n    - Interpretando dataset como millones de pesos, salida formateada: `$62.6 mil millones`.\n    - Pagado acumulado anual para UBA: `262403.287296` -> `$262.4 mil millones`.\n    - Crédito vigente anual UBA: `799460.3925720002` -> `$799.5 mil millones`.\n    - Porcentaje ejecutado: `32.82255002675041%`.\n    - Desglose:\n      - `$28.4 mil millones` docentes/autoridades superiores.\n      - `$32.5 mil millones` no docentes.\n      - `$1.7 mil millones` hospitales universitarios.\n    [tool: execute_code].\n36. PROTOTIPÓ ejemplo provincia/ATN:\n    - Chubut event: `$4.0 mil millones`.\n    - annual paid `$6.5 mil millones`.\n    - crédito vigente `0`, por lo tanto porcentaje `N/A`.\n    - Campos: `Ministerio del Interior`, `Relaciones con las Provincias y Desarrollo Regional`, `Aportes del Tesoro Nacional (ATN)`, `Transferencias a instituciones provinciales y municipales para financiar gastos corrientes`, `Transferencias a la Administración Pública Provincial para financiar gastos corrientes`, `Administración Central Provincial`.\n    - Esto ilustra caveat crítico: algunas partidas tienen pagos con crédito vigente 0 en dataset anual, por lo que porcentaje no siempre es interpretable; hay que manejar `N/A`/“sin crédito vigente informado”.\n    [tool: execute_code].\n37. ACTUALIZÓ TODO list:\n    - tweet-context completado,\n    - data-sources completado,\n    - prototype completado,\n    - architecture completado,\n    - report en progreso [tool: todo].\n\n## Active State\n- No hay repositorio local ni working directory relevante; no se modificaron archivos persistentes.\n- No hay branch Git.\n- No hay tests formales.\n- No hay procesos/servidores corriendo.\n- Todo el trabajo fue exploratorio con herramientas web/terminal/execute_code.\n- Ambiente observado:\n  - fecha/hora: `2026-05-12 15:10:32 UTC`, `2026-05-12 12:10:32 -03`.\n  - Python disponible con `requests`, `zipfile`, `csv`, etc.\n  - `pandas`, `openpyxl`, `xlrd` no instalados.\n  - `libreoffice`, `ssconvert`, `in2csv` no disponibles.\n- Datos descargados/consultados remotamente:\n  - `credito-diario-2026.zip`: accesible, CSV parseable.\n  - `credito-anual-2026.zip`: accesible, usado para acumulados/presupuesto.\n  - `credito-mensual-2026.zip`: accesible/probado parcialmente.\n  - RON/copoticipación: páginas y archivos Excel/CSV accesibles; Excel no parseado por falta de librerías.\n\n## In Progress\nSe estaba preparando el reporte ejecutivo final de factibilidad para el usuario. Ya se completó la investigación base y faltaba redactar una respuesta estructurada con:\n- resumen ejecutivo,\n- fuentes oficiales,\n- qué puede y no puede prometer el bot,\n- parte delicada,\n- propuesta de producto/MVP,\n- arquitectura end-to-end,\n- ejemplos reales,\n- demanda/lo que la gente querría ver,\n- riesgos/costos,\n- recomendación y plan de implementación.\n\n## Blocked\n- No se pudo leer el tweet/replies/quotes en forma completa:\n  - `xurl` no estaba instalado: `/usr/bin/bash: line 3: xurl: command not found`.\n  - Twitter oEmbed inaccesible/not found.\n  - syndication endpoint devolvió `{}`.\n  - fxtwitter/vxtwitter/fixupx no devolvieron replies confiables.\n  - Conclusión para reporte: no afirmar métricas de demanda del tweet salvo el texto original y la intuición/señal indirecta; si se menciona demanda, aclarar que no se pudo cuantificar replies/likes/quotes con las herramientas disponibles.\n- API oficial de Presupuesto Abierto por POST requiere Authorization:\n  - error exacto: `401 application/json;charset=ISO-8859-1 {\"statusCode\":401,\"message\":\"Debe indicar el header Authorization en la petición\",\"detail\":\"\"}`.\n  - Solución: usar datasets CSV/ZIP públicos de `dgsiaf-repo.mecon.gob.ar` y/o CKAN/datos.gob.ar.\n- Archivos Excel de RON/coparticipación no se parsearon por falta de dependencias:\n  - `pandas False openpyxl False xlrd False`\n  - `ModuleNotFoundError(\"No module named 'pandas'\")`\n  - no hay `libreoffice`, `ssconvert`, `in2csv`.\n  - Solución futura: instalar librerías o parsear con herramientas adecuadas; para reporte basta con mencionar fuente accesible y necesidad de ETL adicional.\n- X/Twitter API: no se confirmó precio exacto actual; se debe mencionar como riesgo/costo a verificar. No afirmar un monto específico sin fuente actual.\n\n## Key Decisions\n- Fuente principal para “transferencias presupuestarias”:\n  - Usar Presupuesto Abierto / datasets de crédito APN (`credito-diario`, `credito-anual`, opcional `credito-mensual`) porque son públicos, descargables sin auth y contienen clasificación presupuestaria suficiente.\n  - Razón: API interactiva requiere Authorization; CSV/ZIP públicos funcionan.\n- Detección de eventos:\n  - Usar `credito-diario-{año}.zip` para novedades.\n  - Filtrar `inciso_id == 5` (“Transferencias”).\n  - Usar `credito_pagado > 0` como señal más cercana a “transferido/pagado”; opcional `credito_devengado > 0` para compromiso/obligación.\n  - Razón: `pagado` se parece más a caja/transferencia efectiva que `devengado`, aunque sigue sin ser comprobante bancario individual.\n- Acumulado y porcentaje:\n  - Usar `credito-anual-{año}.zip` para `credito_pagado` acumulado y `credito_vigente`.\n  - Fórmula: `credito_pagado_acumulado / credito_vigente * 100`.\n  - Razón: el dataset diario puede tener denominadores 0 o no adecuados para presupuesto anual; el anual resume mejor crédito vigente y acumulados.\n- Denominador recomendado:\n  - `credito_vigente` por defecto, no `credito_presupuestado`.\n  - Razón: el presupuesto vigente incorpora ampliaciones/reasignaciones; el inicial puede quedar obsoleto.\n- Nivel de agregación:\n  - No publicar cada fila cruda: genera ruido y puede duplicar partidas.\n  - Agrupar por fecha + destino (`subparcial`/ubicación según caso) + programa/actividad + partida + fuente de financiamiento.\n  - Razón: el CSV está muy granular y varias filas forman un único “evento comunicable” (ej. UBA tiene docente, no docente, hospitales).\n- Caveat semántico:\n  - No llamar “transferencia bancaria individual” ni “en tiempo real”.\n  - Llamar “registro presupuestario de pago/devengado en Presupuesto Abierto”.\n  - Razón: los datos no tienen CUIT beneficiario final, CBU, orden de pago individual ni timestamp bancario; son registros presupuestarios agregados.\n- Producto recomendado:\n  - Bot con resúmenes diarios/alertas, no firehose total.\n  - Dashboard web/histórico para detalle.\n  - Razón: X tiene límites, costos y riesgo de spam; la web permite navegación y transparencia completa.\n\n## Resolved Questions\n- “¿Es factible hacer un bot que twittee transferencias del gobierno nacional a provincias/universidades/etc.?”\n  - Sí, factible como bot de registros de ejecución presupuestaria usando Presupuesto Abierto. No es real-time bancario ni transferencia individual exacta.\n- “¿La fuente existe?”\n  - Sí. Principal: `credito-diario-2026.zip` en `https://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/credito-diario-2026.zip`.\n  - Datasets complementarios: `credito-anual-2026.zip`, `credito-mensual-2026.zip`.\n  - Fuente adicional para coparticipación/automáticas: página RON de Secretaría de Hacienda/Asuntos Provinciales con Excel/CSV.\n- “¿Cómo se filtran transferencias?”\n  - En datasets de crédito APN, `inciso_id = 5` corresponde a Transferencias.\n- “¿Se puede agregar ‘transferido hasta ahora en 2026 vs presupuesto anual’?”\n  - Sí. Usar acumulado `credito_pagado` vs `credito_vigente` en dataset anual; calcular porcentaje. Si `credito_vigente = 0`, mostrar `N/A` o “sin crédito vigente informado”.\n- “¿Qué columnas útiles hay?”\n  - `impacto_presupuestario_fecha`, `jurisdiccion_desc`, `entidad_desc`, `servicio_desc`, `programa_desc`, `actividad_desc`, `inciso_desc`, `principal_desc`, `parcial_desc`, `subparcial_desc`, `fuente_financiamiento_desc`, `ubicacion_geografica_desc`, `unidad_ejecutora_desc`, `credito_devengado`, `credito_pagado`, `credito_vigente`, `ultima_actualizacion_fecha` según dataset.\n- “¿Qué tan difícil?”\n  - MVP técnico en pocos días si es solo bot + SQLite/Postgres + cron.\n  - Producto robusto con dashboard, validaciones, clasificación de destinatarios, métricas y publicación prolija: 2–4 semanas.\n- “¿Qué es la parte delicada?”\n  - Definir correctamente qué cuenta como “destino” y “transferencia”; evitar confundir partida presupuestaria agregada con transferencia bancaria individual; manejar créditos vigentes 0; evitar duplicados/ruido; distinguir transferencias a provincias/universidades de coparticipación automática; interpretación de unidades monetarias.\n\n## Pending User Asks\n- Falta entregar el reporte ejecutivo final de factibilidad solicitado en el último mensaje.\n- El reporte debe incluir:\n  - “factos factos” con datos/ejemplos reales,\n  - evaluación completa de punta a punta,\n  - explicación de la parte delicada,\n  - investigación de qué quiere ver la gente/demanda,\n  - arquitectura recomendada,\n  - riesgos/costos,\n  - veredicto y plan.\n\n## Relevant Files\nNo hay archivos locales creados/modificados. Recursos remotos relevantes:\n- `https://x.com/__microdancing/status/2054160914438291840` — tweet original que motivó la idea.\n- `https://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/credito-diario-2026.zip` — fuente principal para detectar registros diarios.\n- `https://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/credito-anual-2026.zip` — fuente para acumulado anual y crédito vigente.\n- `https://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/credito-mensual-2026.zip` — posible fuente intermedia/resumen mensual.\n- `https://www.presupuestoabierto.gob.ar/api/jsonCredito` — schema/API de crédito; API POST requiere Authorization.\n- `https://www.presupuestoabierto.gob.ar/sici/datos-abiertos` — datos abiertos Presupuesto Abierto.\n- `https://www.presupuestoabierto.gob.ar/sici/ejecucion-presup-de-las-transferencias` — visualización/análisis de transferencias.\n- `https://www.argentina.gob.ar/economia/sechacienda/asuntosprovinciales/ron` — fuente RON/coparticipación/transferencias automáticas a provincias.\n- `https://www.argentina.gob.ar/sites/default/files/serie_ron_2003_2025.csv` — serie histórica RON CSV con columnas `ano;provincia;impuesto;regimen;monto`.\n- `https://www.argentina.gob.ar/sites/default/files/internet_diario26_4_2.xls` — archivo diario RON 2026, Excel.\n- `https://www.argentina.gob.ar/sites/default/files/informacion_consolidada_2026_1.xlsx` — consolidado RON 2026, Excel.\n- `https://github.com/jazzido/pautabot` — antecedente de bot de transparencia pública (pauta oficial), útil como ejemplo conceptual.\n\n## Remaining Work\n- Redactar el reporte ejecutivo final en español, con una estructura sugerida:\n  1. Veredicto corto.\n  2. Qué se puede construir exactamente.\n  3. Qué NO se puede afirmar con esos datos.\n  4. Fuentes oficiales y confiabilidad.\n  5. Ejemplos reales del prototipo:\n     - UBA 2026-05-05: `$62.6 mil millones`, acumulado `$262.4 mil millones`, vigente `$799.5 mil millones`, ejecución `32.8%`.\n     - ATN/Chubut: `$4.0 mil millones`, acumulado `$6.5 mil millones`, crédito vigente 0 -> porcentaje `N/A`.\n  6. Parte delicada:\n     - nivel de agregación,\n     - destino,\n     - universo de transferencias,\n     - pagado vs devengado,\n     - unidades,\n     - crédito vigente 0,\n     - ruido/duplicados,\n     - X API.\n  7. Qué quiere ver la gente:\n     - alertas entendibles,\n     - ranking por provincia/universidad,\n     - grandes montos,\n     - comparación vs presupuesto,\n     - contexto “qué programa/para qué”,\n     - fuente/link reproducible,\n     - histórico/buscador,\n     - no spam.\n     Aclarar que no se pudo cuantificar replies/quotes por limitaciones de acceso; inferencia basada en el tweet y patrones de productos de transparencia.\n  8. MVP recomendado:\n     - bot diario/alertas de montos grandes,\n     - dashboard web,\n     - endpoints/API,\n     - newsletter/Telegram opcional.\n  9. Arquitectura:\n     - downloader,\n     - parser,\n     - normalizer,\n     - classifier,\n     - state DB,\n     - deduper,\n     - publisher,\n     - observability.\n  10. Roadmap:\n      - Día 1–2: prototipo.\n      - Semana 1: MVP bot.\n      - Semana 2–4: dashboard, validación, clasificación.\n  11. Costos:\n      - hosting barato,\n      - DB,\n      - X API a verificar,\n      - dominio,\n      - mantenimiento.\n  12. Recomendación final:\n      - construir, pero posicionarlo como “monitor de registros presupuestarios de transferencias” y no “tracker bancario en tiempo real”.\n\n## Critical Context\n- Tweet original citado en respuesta previa:\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- Dataset principal probado:\n  - `credito-diario-2026.zip` accesible sin auth.\n  - Contiene datos reales al 10 de mayo de 2026 según observación previa: “Última actualización del ejercicio 2026: 10 Mayo 2026.”\n- Filtro clave:\n  - `inciso_id = 5` → Transferencias.\n- Campos de interés para tweets:\n  - fecha: `impacto_presupuestario_fecha`\n  - jurisdicción: `jurisdiccion_desc`\n  - entidad/servicio: `entidad_desc`, `servicio_desc`\n  - programa/actividad: `programa_desc`, `actividad_desc`\n  - partida: `principal_desc`, `parcial_desc`, `subparcial_desc`\n  - destino territorial: `ubicacion_geografica_desc`\n  - fuente: `fuente_financiamiento_desc`\n  - monto: `credito_pagado` o `credito_devengado`\n  - actualización: `ultima_actualizacion_fecha`\n- Fórmulas:\n  - Evento diario: suma de `credito_pagado` de filas nuevas/fecha.\n  - Acumulado anual: suma/valor `credito_pagado` en `credito-anual` para misma clave conceptual.\n  - Porcentaje: `credito_pagado_acumulado / credito_vigente * 100`.\n  - Si `credito_vigente <= 0`: mostrar `N/A`/“sin crédito vigente informado”, no dividir.\n- Ejemplo UBA:\n  - Fecha: `2026-05-05 00:00:00`.\n  - Destino: `Universidad de Buenos Aires`.\n  - Filas: 3.\n  - Monto evento: `62568.241846` en unidad dataset; interpretado/formateado como `$62.6 mil millones` si el dataset está en millones de pesos.\n  - Acumulado anual pagado: `262403.287296` -> `$262.4 mil millones`.\n  - Crédito vigente: `799460.3925720002` -> `$799.5 mil millones`.\n  - Ejecución: `32.82255002675041%`.\n  - Desglose:\n    - `$32.5 mil millones` no docentes.\n    - `$28.4 mil millones` docentes/autoridades.\n    - `$1.7 mil millones` hospitales universitarios.\n  - Programas/campos:\n    - `Ministerio de Capital Humano`\n    - `Secretaría de Educación`\n    - `Desarrollo de la Educacion Superior`\n    - `Transferencias a universidades nacionales`\n    - `Tesoro Nacional`\n    - `Ciudad Autónoma de Buenos Aires`.\n- Ejemplo Chubut/ATN:\n  - Evento: `$4.0 mil millones`.\n  - Anual pagado: `$6.5 mil millones`.\n  - Vigente: `$0`, porcentaje `N/A`.\n  - Campos:\n    - `Ministerio del Interior`\n    - `Relaciones con las Provincias y Desarrollo Regional`\n    - `Aportes del Tesoro Nacional (ATN)`\n    - `Transferencias a instituciones provinciales y municipales para financiar gastos corrientes`\n    - `Transferencias a la Administración Pública Provincial para financiar gastos corrientes`\n    - `Administración Central Provincial`.\n- Error de API oficial:\n  - `401 ... \"Debe indicar el header Authorization en la petición\"`.\n- Error xurl:\n  - `xurl: command not found`.\n- Limitación de demanda:\n  - No se pudieron recuperar replies/quotes/likes del tweet. Si se habla de “la gente quiere”, debe formularse como hipótesis informada/señal cualitativa, no como métrica validada.\n- Importante de unidades:\n  - En los outputs se formateó como si valores tipo `62568.241846` fueran millones de pesos (`$62.6 mil millones`). Antes de producción hay que verificar oficialmente la unidad del dataset para evitar publicar montos mal escalados."
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          "type": "reasoning",
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          "id": "rs_0db05e419df56d4e016a0344736ea88191b062152d8f9f16f8",
          "summary": []
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"todos\": [{\"id\": \"tweet-context\", \"content\": \"Recuperar contenido del tweet/replies y señales de demanda pública\", \"status\": \"completed\"}, {\"id\": \"data-sources\", \"content\": \"Auditar fuentes oficiales disponibles: Presupuesto Abierto, datos.gob.ar, CSV/API, actualización y campos\", \"status\": \"completed\"}, {\"id\": \"prototype\", \"content\": \"Probar pipeline real: descargar 2026, filtrar transferencias, calcular acumulados/porcentajes y detectar limitaciones\", \"status\": \"completed\"}, {\"id\": \"architecture\", \"content\": \"Diseñar MVP end-to-end: ingestión, storage, publicación, UI/API, costos y riesgos\", \"status\": \"completed\"}, {\"id\": \"report\", \"content\": \"Entregar reporte ejecutivo de factibilidad con factos, parte delicada y recomendación\", \"status\": \"completed\"}], \"summary\": {\"total\": 5, \"pending\": 0, \"in_progress\": 0, \"completed\": 5, \"cancelled\": 0}}",
      "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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      "content": "[nachlakes] 5545c371-fd88-47aa-995f-e5264833c94e\n\ntoken para presupuesto abierto api asi te es mas facil seguramente"
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    {
      "role": "tool",
      "content": "{\"success\": true, \"name\": \"hermes-agent\", \"description\": \"Complete guide to using and extending Hermes Agent — CLI usage, setup, configuration, spawning additional agents, gateway platforms, skills, voice, tools, profiles, and a concise contributor reference. Load this skill when helping users configure Hermes, troubleshoot issues, spawn agent instances, or make code contributions.\", \"tags\": [\"hermes\", \"setup\", \"configuration\", \"multi-agent\", \"spawning\", \"cli\", \"gateway\", \"development\"], \"related_skills\": [\"claude-code\", \"codex\", \"opencode\"], \"content\": \"---\\nname: hermes-agent\\ndescription: Complete guide to using and extending Hermes Agent — CLI usage, setup, configuration, spawning additional agents, gateway platforms, skills, voice, tools, profiles, and a concise contributor reference. Load this skill when helping users configure Hermes, troubleshoot issues, spawn agent instances, or make code contributions.\\nversion: 2.0.0\\nauthor: Hermes Agent + Teknium\\nlicense: MIT\\nmetadata:\\n  hermes:\\n    tags: [hermes, setup, configuration, multi-agent, spawning, cli, gateway, development]\\n    homepage: https://github.com/NousResearch/hermes-agent\\n    related_skills: [claude-code, codex, opencode]\\n---\\n\\n# Hermes Agent\\n\\nHermes Agent is an open-source AI agent framework by Nous Research that runs in your terminal, messaging platforms, and IDEs. It belongs to the same category as Claude Code (Anthropic), Codex (OpenAI), and OpenClaw — autonomous coding and task-execution agents that use tool calling to interact with your system. Hermes works with any LLM provider (OpenRouter, Anthropic, OpenAI, DeepSeek, local models, and 15+ others) and runs on Linux, macOS, and WSL.\\n\\nWhat makes Hermes different:\\n\\n- **Self-improving through skills** — Hermes learns from experience by saving reusable procedures as skills. When it solves a complex problem, discovers a workflow, or gets corrected, it can persist that knowledge as a skill document that loads into future sessions. Skills accumulate over time, making the agent better at your specific tasks and environment.\\n- **Persistent memory across sessions** — remembers who you are, your preferences, environment details, and lessons learned. Pluggable memory backends (built-in, Honcho, Mem0, and more) let you choose how memory works.\\n- **Multi-platform gateway** — the same agent runs on Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Email, and 8+ other platforms with full tool access, not just chat.\\n- **Provider-agnostic** — swap models and providers mid-workflow without changing anything else. Credential pools rotate across multiple API keys automatically.\\n- **Profiles** — run multiple independent Hermes instances with isolated configs, sessions, skills, and memory.\\n- **Extensible** — plugins, MCP servers, custom tools, webhook triggers, cron scheduling, and the full Python ecosystem.\\n\\nPeople use Hermes for software development, research, system administration, data analysis, content creation, home automation, and anything else that benefits from an AI agent with persistent context and full system access.\\n\\n**This skill helps you work with Hermes Agent effectively** — setting it up, configuring features, spawning additional agent instances, troubleshooting issues, finding the right commands and settings, and understanding how the system works when you need to extend or contribute to it.\\n\\n**Docs:** https://hermes-agent.nousresearch.com/docs/\\n\\n## Quick Start\\n\\n```bash\\n# Install\\ncurl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash\\n\\n# Interactive chat (default)\\nhermes\\n\\n# Single query\\nhermes chat -q \\\"What is the capital of France?\\\"\\n\\n# Setup wizard\\nhermes setup\\n\\n# Change model/provider\\nhermes model\\n\\n# Check health\\nhermes doctor\\n```\\n\\n---\\n\\n## CLI Reference\\n\\n### Global Flags\\n\\n```\\nhermes [flags] [command]\\n\\n  --version, -V             Show version\\n  --resume, -r SESSION      Resume session by ID or title\\n  --continue, -c [NAME]     Resume by name, or most recent session\\n  --worktree, -w            Isolated git worktree mode (parallel agents)\\n  --skills, -s SKILL        Preload skills (comma-separate or repeat)\\n  --profile, -p NAME        Use a named profile\\n  --yolo                    Skip dangerous command approval\\n  --pass-session-id         Include session ID in system prompt\\n```\\n\\nNo subcommand defaults to `chat`.\\n\\n### Chat\\n\\n```\\nhermes chat [flags]\\n  -q, --query TEXT          Single query, non-interactive\\n  -m, --model MODEL         Model (e.g. anthropic/claude-sonnet-4)\\n  -t, --toolsets LIST       Comma-separated toolsets\\n  --provider PROVIDER       Force provider (openrouter, anthropic, nous, etc.)\\n  -v, --verbose             Verbose output\\n  -Q, --quiet               Suppress banner, spinner, tool previews\\n  --checkpoints             Enable filesystem checkpoints (/rollback)\\n  --source TAG              Session source tag (default: cli)\\n```\\n\\n### Configuration\\n\\n```\\nhermes setup [section]      Interactive wizard (model|terminal|gateway|tools|agent)\\nhermes model                Interactive model/provider picker\\nhermes config               View current config\\nhermes config edit          Open config.yaml in $EDITOR\\nhermes config set KEY VAL   Set a config value\\nhermes config path          Print config.yaml path\\nhermes config env-path      Print .env path\\nhermes config check         Check for missing/outdated config\\nhermes config migrate       Update config with new options\\nhermes login [--provider P] OAuth login (nous, openai-codex)\\nhermes logout               Clear stored auth\\nhermes doctor [--fix]       Check dependencies and config\\nhermes status [--all]       Show component status\\n```\\n\\n### Tools & Skills\\n\\n```\\nhermes tools                Interactive tool enable/disable (curses UI)\\nhermes tools list           Show all tools and status\\nhermes tools enable NAME    Enable a toolset\\nhermes tools disable NAME   Disable a toolset\\n\\nhermes skills list          List installed skills\\nhermes skills search QUERY  Search the skills hub\\nhermes skills install ID    Install a skill\\nhermes skills inspect ID    Preview without installing\\nhermes skills config        Enable/disable skills per platform\\nhermes skills check         Check for updates\\nhermes skills update        Update outdated skills\\nhermes skills uninstall N   Remove a hub skill\\nhermes skills publish PATH  Publish to registry\\nhermes skills browse        Browse all available skills\\nhermes skills tap add REPO  Add a GitHub repo as skill source\\n```\\n\\n### MCP Servers\\n\\n```\\nhermes mcp serve            Run Hermes as an MCP server\\nhermes mcp add NAME         Add an MCP server (--url or --command)\\nhermes mcp remove NAME      Remove an MCP server\\nhermes mcp list             List configured servers\\nhermes mcp test NAME        Test connection\\nhermes mcp configure NAME   Toggle tool selection\\n```\\n\\n### Gateway (Messaging Platforms)\\n\\n```\\nhermes gateway run          Start gateway foreground\\nhermes gateway install      Install as background service\\nhermes gateway start/stop   Control the service\\nhermes gateway restart      Restart the service\\nhermes gateway status       Check status\\nhermes gateway setup        Configure platforms\\n```\\n\\nSupported platforms: Telegram, Discord, Slack, WhatsApp, Signal, Email, SMS, Matrix, Mattermost, Home Assistant, DingTalk, Feishu, WeCom, API Server, Webhooks, Open WebUI.\\n\\nPlatform docs: https://hermes-agent.nousresearch.com/docs/user-guide/messaging/\\n\\n### Sessions\\n\\n```\\nhermes sessions list        List recent sessions\\nhermes sessions browse      Interactive picker\\nhermes sessions export OUT  Export to JSONL\\nhermes sessions rename ID T Rename a session\\nhermes sessions delete ID   Delete a session\\nhermes sessions prune       Clean up old sessions (--older-than N days)\\nhermes sessions stats       Session store statistics\\n```\\n\\n### Cron Jobs\\n\\n```\\nhermes cron list            List jobs (--all for disabled)\\nhermes cron create SCHED    Create: '30m', 'every 2h', '0 9 * * *'\\nhermes cron edit ID         Edit schedule, prompt, delivery\\nhermes cron pause/resume ID Control job state\\nhermes cron run ID          Trigger on next tick\\nhermes cron remove ID       Delete a job\\nhermes cron status          Scheduler status\\n```\\n\\n### Webhooks\\n\\n```\\nhermes webhook subscribe N  Create route at /webhooks/<name>\\nhermes webhook list         List subscriptions\\nhermes webhook remove NAME  Remove a subscription\\nhermes webhook test NAME    Send a test POST\\n```\\n\\n### Profiles\\n\\n```\\nhermes profile list         List all profiles\\nhermes profile create NAME  Create (--clone, --clone-all, --clone-from)\\nhermes profile use NAME     Set sticky default\\nhermes profile delete NAME  Delete a profile\\nhermes profile show NAME    Show details\\nhermes profile alias NAME   Manage wrapper scripts\\nhermes profile rename A B   Rename a profile\\nhermes profile export NAME  Export to tar.gz\\nhermes profile import FILE  Import from archive\\n```\\n\\n### Credential Pools\\n\\n```\\nhermes auth add             Interactive credential wizard\\nhermes auth list [PROVIDER] List pooled credentials\\nhermes auth remove P INDEX  Remove by provider + index\\nhermes auth reset PROVIDER  Clear exhaustion status\\n```\\n\\n### Other\\n\\n```\\nhermes insights [--days N]  Usage analytics\\nhermes update               Update to latest version\\nhermes pairing list/approve/revoke  DM authorization\\nhermes plugins list/install/remove  Plugin management\\nhermes honcho setup/status  Honcho memory integration\\nhermes memory setup/status/off  Memory provider config\\nhermes completion bash|zsh  Shell completions\\nhermes acp                  ACP server (IDE integration)\\nhermes claw migrate         Migrate from OpenClaw\\nhermes uninstall            Uninstall Hermes\\n```\\n\\n---\\n\\n## Slash Commands (In-Session)\\n\\nType these during an interactive chat session.\\n\\n### Session Control\\n```\\n/new (/reset)        Fresh session\\n/clear               Clear screen + new session (CLI)\\n/retry               Resend last message\\n/undo                Remove last exchange\\n/title [name]        Name the session\\n/compress            Manually compress context\\n/stop                Kill background processes\\n/rollback [N]        Restore filesystem checkpoint\\n/background <prompt> Run prompt in background\\n/queue <prompt>      Queue for next turn\\n/resume [name]       Resume a named session\\n```\\n\\n### Configuration\\n```\\n/config              Show config (CLI)\\n/model [name]        Show or change model\\n/provider            Show provider info\\n/prompt [text]       View/set system prompt (CLI)\\n/personality [name]  Set personality\\n/reasoning [level]   Set reasoning (none|low|medium|high|xhigh|show|hide)\\n/verbose             Cycle: off → new → all → verbose\\n/voice [on|off|tts]  Voice mode\\n/yolo                Toggle approval bypass\\n/skin [name]         Change theme (CLI)\\n/statusbar           Toggle status bar (CLI)\\n```\\n\\n### Tools & Skills\\n```\\n/tools               Manage tools (CLI)\\n/toolsets            List toolsets (CLI)\\n/skills              Search/install skills (CLI)\\n/skill <name>        Load a skill into session\\n/cron                Manage cron jobs (CLI)\\n/reload-mcp          Reload MCP servers\\n/plugins             List plugins (CLI)\\n```\\n\\n### Info\\n```\\n/help                Show commands\\n/commands [page]     Browse all commands (gateway)\\n/usage               Token usage\\n/insights [days]     Usage analytics\\n/status              Session info (gateway)\\n/profile             Active profile info\\n```\\n\\n### Exit\\n```\\n/quit (/exit, /q)    Exit CLI\\n```\\n\\n---\\n\\n## Key Paths & Config\\n\\n```\\n~/.hermes/config.yaml       Main configuration\\n~/.hermes/.env              API keys and secrets\\n~/.hermes/skills/           Installed skills\\n~/.hermes/sessions/         Session transcripts\\n~/.hermes/logs/             Gateway and error logs\\n~/.hermes/auth.json         OAuth tokens and credential pools\\n~/.hermes/hermes-agent/     Source code (if git-installed)\\n```\\n\\nProfiles use `~/.hermes/profiles/<name>/` with the same layout.\\n\\n### Config Sections\\n\\nEdit with `hermes config edit` or `hermes config set section.key value`.\\n\\n| Section | Key options |\\n|---------|-------------|\\n| `model` | `default`, `provider`, `base_url`, `api_key`, `context_length` |\\n| `agent` | `max_turns` (90), `tool_use_enforcement` |\\n| `terminal` | `backend` (local/docker/ssh/modal), `cwd`, `timeout` (180) |\\n| `compression` | `enabled`, `threshold` (0.50), `target_ratio` (0.20) |\\n| `display` | `skin`, `tool_progress`, `show_reasoning`, `show_cost` |\\n| `stt` | `enabled`, `provider` (local/groq/openai) |\\n| `tts` | `provider` (edge/elevenlabs/openai/kokoro/fish) |\\n| `memory` | `memory_enabled`, `user_profile_enabled`, `provider` |\\n| `security` | `tirith_enabled`, `website_blocklist` |\\n| `delegation` | `model`, `provider`, `max_iterations` (50) |\\n| `smart_model_routing` | `enabled`, `cheap_model` |\\n| `checkpoints` | `enabled`, `max_snapshots` (50) |\\n\\nFull config reference: https://hermes-agent.nousresearch.com/docs/user-guide/configuration\\n\\n### Providers\\n\\n18 providers supported. Set via `hermes model` or `hermes setup`.\\n\\n### Reasoning effort gotcha\\n\\nHermes' persistent reasoning setting lives at `agent.reasoning_effort` in `~/.hermes/config.yaml`.\\n\\nUse one of these:\\n```bash\\nhermes config set agent.reasoning_effort xhigh\\n```\\nOr inside Hermes:\\n```text\\n/reasoning xhigh\\n```\\n\\nDo not rely on a top-level config key like `OPENAI_REASONING_EFFORT: xhigh` for Hermes CLI/gateway behavior. Hermes reads `agent.reasoning_effort`, not that top-level key.\\n\\nAlso, reasoning support is model/provider-specific:\\n- OpenAI Codex / GPT-5 Responses-style models: effort values like `low|medium|high|xhigh` can apply.\\n- OpenRouter models that expose effort controls: effort can apply.\\n- DeepSeek and some Kimi/Moonshot models: reasoning is selected by choosing a thinking/reasoner model variant, not by an effort dropdown.\\n- Some Mistral models only support a reasoning toggle, not `xhigh`.\\n- Web UI may clamp or clear unsupported effort values per model/provider.\\n\\nSo `agent.reasoning_effort: xhigh` is a good global default, but it will only be honored by models/providers that actually support effort-style reasoning.\\n\\n\\n| Provider | Auth | Key env var |\\n|----------|------|-------------|\\n| OpenRouter | API key | `OPENROUTER_API_KEY` |\\n| Anthropic | API key | `ANTHROPIC_API_KEY` |\\n| Nous Portal | OAuth | `hermes login --provider nous` |\\n| OpenAI Codex | OAuth | `hermes login --provider openai-codex` |\\n| GitHub Copilot | Token | `COPILOT_GITHUB_TOKEN` |\\n| DeepSeek | API key | `DEEPSEEK_API_KEY` |\\n| Hugging Face | Token | `HF_TOKEN` |\\n| Z.AI / GLM | API key | `GLM_API_KEY` |\\n| MiniMax | API key | `MINIMAX_API_KEY` |\\n| Kimi / Moonshot | API key | `KIMI_API_KEY` |\\n| Alibaba / DashScope | API key | `DASHSCOPE_API_KEY` |\\n| Kilo Code | API key | `KILOCODE_API_KEY` |\\n| Custom endpoint | Config | `model.base_url` + `model.api_key` in config.yaml |\\n\\nPlus: AI Gateway, OpenCode Zen, OpenCode Go, MiniMax CN, GitHub Copilot ACP.\\n\\nFull provider docs: https://hermes-agent.nousresearch.com/docs/integrations/providers\\n\\n### Toolsets\\n\\nEnable/disable via `hermes tools` (interactive) or `hermes tools enable/disable NAME`.\\n\\n| Toolset | What it provides |\\n|---------|-----------------|\\n| `web` | Web search and content extraction |\\n| `browser` | Browser automation (Browserbase, Camofox, or local Chromium) |\\n| `terminal` | Shell commands and process management |\\n| `file` | File read/write/search/patch |\\n| `code_execution` | Sandboxed Python execution |\\n| `vision` | Image analysis |\\n| `image_gen` | AI image generation |\\n| `tts` | Text-to-speech |\\n| `skills` | Skill browsing and management |\\n| `memory` | Persistent cross-session memory |\\n| `session_search` | Search past conversations |\\n| `delegation` | Subagent task delegation |\\n| `cronjob` | Scheduled task management |\\n| `clarify` | Ask user clarifying questions |\\n| `moa` | Mixture of Agents (off by default) |\\n| `homeassistant` | Smart home control (off by default) |\\n\\nTool changes take effect on `/reset` (new session). They do NOT apply mid-conversation to preserve prompt caching.\\n\\n---\\n\\n## Voice & Transcription\\n\\n### STT (Voice → Text)\\n\\nVoice messages from messaging platforms are auto-transcribed.\\n\\nProvider priority (auto-detected):\\n1. **Local faster-whisper** — free, no API key: `pip install faster-whisper`\\n2. **Groq Whisper** — free tier: set `GROQ_API_KEY`\\n3. **OpenAI Whisper** — paid: set `VOICE_TOOLS_OPENAI_KEY`\\n\\nConfig:\\n```yaml\\nstt:\\n  enabled: true\\n  provider: local        # local, groq, openai\\n  local:\\n    model: base          # tiny, base, small, medium, large-v3\\n```\\n\\n### TTS (Text → Voice)\\n\\n| Provider | Env var | Free? |\\n|----------|---------|-------|\\n| Edge TTS | None | Yes (default) |\\n| ElevenLabs | `ELEVENLABS_API_KEY` | Free tier |\\n| OpenAI | `VOICE_TOOLS_OPENAI_KEY` | Paid |\\n| Kokoro (local) | None | Free |\\n| Fish Audio | `FISH_AUDIO_API_KEY` | Free tier |\\n\\nVoice commands: `/voice on` (voice-to-voice), `/voice tts` (always voice), `/voice off`.\\n\\n---\\n\\n## Spawning Additional Hermes Instances\\n\\nRun additional Hermes processes as fully independent subprocesses — separate sessions, tools, and environments.\\n\\n### When to Use This vs delegate_task\\n\\n| | `delegate_task` | Spawning `hermes` process |\\n|-|-----------------|--------------------------|\\n| Isolation | Separate conversation, shared process | Fully independent process |\\n| Duration | Minutes (bounded by parent loop) | Hours/days |\\n| Tool access | Subset of parent's tools | Full tool access |\\n| Interactive | No | Yes (PTY mode) |\\n| Use case | Quick parallel subtasks | Long autonomous missions |\\n\\n### One-Shot Mode\\n\\n```\\nterminal(command=\\\"hermes chat -q 'Research GRPO papers and write summary to ~/research/grpo.md'\\\", timeout=300)\\n\\n# Background for long tasks:\\nterminal(command=\\\"hermes chat -q 'Set up CI/CD for ~/myapp'\\\", background=true)\\n```\\n\\n### Interactive PTY Mode (via tmux)\\n\\nHermes uses prompt_toolkit, which requires a real terminal. Use tmux for interactive spawning:\\n\\n```\\n# Start\\nterminal(command=\\\"tmux new-session -d -s agent1 -x 120 -y 40 'hermes'\\\", timeout=10)\\n\\n# Wait for startup, then send a message\\nterminal(command=\\\"sleep 8 && tmux send-keys -t agent1 'Build a FastAPI auth service' Enter\\\", timeout=15)\\n\\n# Read output\\nterminal(command=\\\"sleep 20 && tmux capture-pane -t agent1 -p\\\", timeout=5)\\n\\n# Send follow-up\\nterminal(command=\\\"tmux send-keys -t agent1 'Add rate limiting middleware' Enter\\\", timeout=5)\\n\\n# Exit\\nterminal(command=\\\"tmux send-keys -t agent1 '/exit' Enter && sleep 2 && tmux kill-session -t agent1\\\", timeout=10)\\n```\\n\\n### Multi-Agent Coordination\\n\\n```\\n# Agent A: backend\\nterminal(command=\\\"tmux new-session -d -s backend -x 120 -y 40 'hermes -w'\\\", timeout=10)\\nterminal(command=\\\"sleep 8 && tmux send-keys -t backend 'Build REST API for user management' Enter\\\", timeout=15)\\n\\n# Agent B: frontend\\nterminal(command=\\\"tmux new-session -d -s frontend -x 120 -y 40 'hermes -w'\\\", timeout=10)\\nterminal(command=\\\"sleep 8 && tmux send-keys -t frontend 'Build React dashboard for user management' Enter\\\", timeout=15)\\n\\n# Check progress, relay context between them\\nterminal(command=\\\"tmux capture-pane -t backend -p | tail -30\\\", timeout=5)\\nterminal(command=\\\"tmux send-keys -t frontend 'Here is the API schema from the backend agent: ...' Enter\\\", timeout=5)\\n```\\n\\n### Session Resume\\n\\n```\\n# Resume most recent session\\nterminal(command=\\\"tmux new-session -d -s resumed 'hermes --continue'\\\", timeout=10)\\n\\n# Resume specific session\\nterminal(command=\\\"tmux new-session -d -s resumed 'hermes --resume 20260225_143052_a1b2c3'\\\", timeout=10)\\n```\\n\\n### Tips\\n\\n- **Prefer `delegate_task` for quick subtasks** — less overhead than spawning a full process\\n- **Use `-w` (worktree mode)** when spawning agents that edit code — prevents git conflicts\\n- **Set timeouts** for one-shot mode — complex tasks can take 5-10 minutes\\n- **Use `hermes chat -q` for fire-and-forget** — no PTY needed\\n- **Use tmux for interactive sessions** — raw PTY mode has `\\\\r` vs `\\\\n` issues with prompt_toolkit\\n- **For scheduled tasks**, use the `cronjob` tool instead of spawning — handles delivery and retry\\n\\n---\\n\\n## Troubleshooting\\n\\n### Voice not working\\n1. Check `stt.enabled: true` in config.yaml\\n2. Verify provider: `pip install faster-whisper` or set API key\\n3. Restart gateway: `/restart`\\n\\n### Tool not available\\n1. `hermes tools` — check if toolset is enabled for your platform\\n2. Some tools need env vars (check `.env`)\\n3. `/reset` after enabling tools\\n\\n### Model/provider issues\\n1. `hermes doctor` — check config and dependencies\\n2. `hermes login` — re-authenticate OAuth providers\\n3. Check `.env` has the right API key\\n\\n### Changes not taking effect\\n- **Tools/skills:** `/reset` starts a new session with updated toolset\\n- **Config changes:** `/restart` reloads gateway config\\n- **Code changes:** Restart the CLI or gateway process\\n\\n### Skills not showing\\n1. `hermes skills list` — verify installed\\n2. `hermes skills config` — check platform enablement\\n3. Load explicitly: `/skill name` or `hermes -s name`\\n\\n### `hermes update` hit a merge conflict\\n\\nSymptoms: gateway fails with `SyntaxError: expected 'except' or 'finally' block` in `api_server.py`, or `git status` shows `both modified` files.\\n\\nRoot cause: local customizations (e.g., custom API endpoints, method renames) were stashed before the update, then re-applied on top of refactored upstream code, leaving conflict markers (`<<<<<<< Updated upstream`) in source files.\\n\\nFix:\\n```bash\\ncd ~/.hermes/hermes-agent\\n# Check for conflict markers:\\ngrep -rn \\\"<<<<<<\\\\|======\\\\|>>>>>>\\\" gateway/\\n# Discard stale local changes:\\ngit checkout -- gateway/platforms/api_server.py gateway/platforms/discord.py gateway/run.py\\n# Also clean .orig files and clear pycache:\\nfind gateway/ -name '*.orig' -delete\\nfind . -type d -name '__pycache__' -exec rm -rf {} + 2>/dev/null\\n# Restart:\\nhermes gateway run --replace\\n```\\n\\nTo preserve local customizations across updates:\\n- Don't let `hermes update` auto-restore the stash — review the diff first with `git stash show -p stash@{0}`\\n- If the upstream already includes your changes, drop the stash entirely\\n- For persistent local patches, consider a fork or document them as patches to re-apply after update\\n\\n### Gateway issues\\nCheck logs first:\\n```bash\\ngrep -i \\\"failed to send\\\\\\\\|error\\\" ~/.hermes/logs/gateway.log | tail -20\\n```\\n\\n---\\n\\n## Where to Find Things\\n\\n| Looking for... | Location |\\n|----------------|----------|\\n| Config options | `hermes config edit` or [Configuration docs](https://hermes-agent.nousresearch.com/docs/user-guide/configuration) |\\n| Available tools | `hermes tools list` or [Tools reference](https://hermes-agent.nousresearch.com/docs/reference/tools-reference) |\\n| Slash commands | `/help` in session or [Slash commands reference](https://hermes-agent.nousresearch.com/docs/reference/slash-commands) |\\n| Skills catalog | `hermes skills browse` or [Skills catalog](https://hermes-agent.nousresearch.com/docs/reference/skills-catalog) |\\n| Provider setup | `hermes model` or [Providers guide](https://hermes-agent.nousresearch.com/docs/integrations/providers) |\\n| Platform setup | `hermes gateway setup` or [Messaging docs](https://hermes-agent.nousresearch.com/docs/user-guide/messaging/) |\\n| MCP servers | `hermes mcp list` or [MCP guide](https://hermes-agent.nousresearch.com/docs/user-guide/features/mcp) |\\n| Profiles | `hermes profile list` or [Profiles docs](https://hermes-agent.nousresearch.com/docs/user-guide/profiles) |\\n| Cron jobs | `hermes cron list` or [Cron docs](https://hermes-agent.nousresearch.com/docs/user-guide/features/cron) |\\n| Memory | `hermes memory status` or [Memory docs](https://hermes-agent.nousresearch.com/docs/user-guide/features/memory) |\\n| Env variables | `hermes config env-path` or [Env vars reference](https://hermes-agent.nousresearch.com/docs/reference/environment-variables) |\\n| CLI commands | `hermes --help` or [CLI reference](https://hermes-agent.nousresearch.com/docs/reference/cli-commands) |\\n| Gateway logs | `~/.hermes/logs/gateway.log` |\\n| Session files | `~/.hermes/sessions/` or `hermes sessions browse` |\\n| Source code | `~/.hermes/hermes-agent/` |\\n\\n---\\n\\n## Contributor Quick Reference\\n\\nFor occasional contributors and PR authors. Full developer docs: https://hermes-agent.nousresearch.com/docs/developer-guide/\\n\\n### Project Layout\\n\\n```\\nhermes-agent/\\n├── run_agent.py          # AIAgent — core conversation loop\\n├── model_tools.py        # Tool discovery and dispatch\\n├── toolsets.py           # Toolset definitions\\n├── cli.py                # Interactive CLI (HermesCLI)\\n├── hermes_state.py       # SQLite session store\\n├── agent/                # Prompt builder, compression, display, adapters\\n├── hermes_cli/           # CLI subcommands, config, setup, commands\\n│   ├── commands.py       # Slash command registry (CommandDef)\\n│   ├── config.py         # DEFAULT_CONFIG, env var definitions\\n│   └── main.py           # CLI entry point and argparse\\n├── tools/                # One file per tool\\n│   └── registry.py       # Central tool registry\\n├── gateway/              # Messaging gateway\\n│   └── platforms/        # Platform adapters (telegram, discord, etc.)\\n├── cron/                 # Job scheduler\\n├── tests/                # ~3000 pytest tests\\n└── website/              # Docusaurus docs site\\n```\\n\\nConfig: `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys).\\n\\n### Adding a Tool (3 files)\\n\\n**1. Create `tools/your_tool.py`:**\\n```python\\nimport json, os\\nfrom tools.registry import registry\\n\\ndef check_requirements() -> bool:\\n    return bool(os.getenv(\\\"EXAMPLE_API_KEY\\\"))\\n\\ndef example_tool(param: str, task_id: str = None) -> str:\\n    return json.dumps({\\\"success\\\": True, \\\"data\\\": \\\"...\\\"})\\n\\nregistry.register(\\n    name=\\\"example_tool\\\",\\n    toolset=\\\"example\\\",\\n    schema={\\\"name\\\": \\\"example_tool\\\", \\\"description\\\": \\\"...\\\", \\\"parameters\\\": {...}},\\n    handler=lambda args, **kw: example_tool(\\n        param=args.get(\\\"param\\\", \\\"\\\"), task_id=kw.get(\\\"task_id\\\")),\\n    check_fn=check_requirements,\\n    requires_env=[\\\"EXAMPLE_API_KEY\\\"],\\n)\\n```\\n\\n**2. Add import** in `model_tools.py` → `_discover_tools()` list.\\n\\n**3. Add to `toolsets.py`** → `_HERMES_CORE_TOOLS` list.\\n\\nAll handlers must return JSON strings. Use `get_hermes_home()` for paths, never hardcode `~/.hermes`.\\n\\n### Adding a Slash Command\\n\\n1. Add `CommandDef` to `COMMAND_REGISTRY` in `hermes_cli/commands.py`\\n2. Add handler in `cli.py` → `process_command()`\\n3. (Optional) Add gateway handler in `gateway/run.py`\\n\\nAll consumers (help text, autocomplete, Telegram menu, Slack mapping) derive from the central registry automatically.\\n\\n### Agent Loop (High Level)\\n\\n```\\nrun_conversation():\\n  1. Build system prompt\\n  2. Loop while iterations < max:\\n     a. Call LLM (OpenAI-format messages + tool schemas)\\n     b. If tool_calls → dispatch each via handle_function_call() → append results → continue\\n     c. If text response → return\\n  3. Context compression triggers automatically near token limit\\n```\\n\\n### Testing\\n\\n```bash\\nsource venv/bin/activate  # or .venv/bin/activate\\npython -m pytest tests/ -o 'addopts=' -q   # Full suite\\npython -m pytest tests/tools/ -q            # Specific area\\n```\\n\\n- Tests auto-redirect `HERMES_HOME` to temp dirs — never touch real `~/.hermes/`\\n- Run full suite before pushing any change\\n- Use `-o 'addopts='` to clear any baked-in pytest flags\\n\\n### Commit Conventions\\n\\n```\\ntype: concise subject line\\n\\nOptional body.\\n```\\n\\nTypes: `fix:`, `feat:`, `refactor:`, `docs:`, `chore:`\\n\\n### Key Rules\\n\\n- **Never break prompt caching** — don't change context, tools, or system prompt mid-conversation\\n- **Message role alternation** — never two assistant or two user messages in a row\\n- Use `get_hermes_home()` from `hermes_constants` for all paths (profile-safe)\\n- Config values go in `config.yaml`, secrets go in `.env`\\n- New tools need a `check_fn` so they only appear when requirements are met\\n\", \"path\": \"autonomous-ai-agents/hermes-agent/SKILL.md\", \"skill_dir\": \"/home/ubuntu/.hermes/skills/autonomous-ai-agents/hermes-agent\", \"linked_files\": null, \"usage_hint\": null, \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\", \"metadata\": {\"hermes\": {\"tags\": [\"hermes\", \"setup\", \"configuration\", \"multi-agent\", \"spawning\", \"cli\", \"gateway\", \"development\"], \"homepage\": \"https://github.com/NousResearch/hermes-agent\", \"related_skills\": [\"claude-code\", \"codex\", \"opencode\"]}}}",
      "tool_call_id": "call_TUinY4cg8VErVOdN28zMbts9"
    },
    {
      "role": "assistant",
      "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.",
      "codex_reasoning_items": [
        {
          "type": "reasoning",
          "encrypted_content": "gAAAAABqA0626sbfSzexwpgnk8lHyYfWGtaywMnrnyB0hdRlHpViZBHhN7x52kbrJk8wYZy9kqLH8NJqmwh-_hvxm6ocCyL3bFhDuYdo2q7zP7yA41R0Fe5ZsVT6J-UwDAizEu2xnRdYPTbyOKXHBo7wZiNCQbJ1G4Op7IADvhdKp3ERWgnG4QeHxItQzFfRiq9NoHla_TZX5ClJnCcpL-MHiUK6ULzvP2_BWqop0loPOOlSf53_630M-NXio7sgKLJKllgNHspUAkkN18ne6L_ThklbyKt20DtTCez8qP0bQTBgMhVxMgMGd-vttGGzvIwV40cXH0KhRw39lVMzU3SdwR96Z8f2BfVcmrIVzm8X7EsYle6o04Pi7Avlc42zaWdg17Lvo37RvhIcV-nK_ciuDLp9hqohZXxSWZMUO8PaP3tjDpL7k15SJd5qDUjxv8sMH4UxpE434l26Glz59VA9g0seq_6pyiJPgNIOurDiUyJWz0ZbaiNTrxJv-WcW1ANJSOPl-XhHAzMilankyIab-x_OZhGF3XQYeWaSsErJLAOcguvks6RJDis3nWHzGzAXcPhtSJW7sQfSBx8U-T1iY9mOom8Fbj-P3xazl7G2Tf7ACtuu8Mg7EmVqdQFRtbzphMr32fphJNJMH4l5O5qnXA-VODChM2JCWMSoOkhOPq6rJogOIR48VNR2Y3-lWRwcJE5aFVHIbSGAXw7TTWZbRkLS5h8ZXFIiQ_fyWiLLcEeQ1TGH8JBFnN-YqpPRmEWUJDY9V5_vVo1WL3s8bu9beFPmVO3uqAqJW3MZvWYymGsfN9JiEQ6wM5nKXJIIyeHxcBDYUqLLHC-T74321QydYy-1GHatgL1gjgTrkDnyQEQro6rxgti0XE6IEhD5SVYOGpLBbXee0_y2RuJ_FtmwlKNDEttcp8oQP9_D0ccuym9ENxQpjurT-gxixciD9o1WAohw0ZLoYk1ibiQJzwGa-O4qdf4zQbfemm-t0VewgyrzBgFYfA7_yLqQkiQzdJi-AJjCJyooRyETgWQKiyt2AvxlnISXLEPTb5voF17oTe7xME66ahbOWxaXG1HXhqxVDi9vo9_h_fAr1cWi10OthtgO2Sa8m2a8PC8xzGNYmp_PdGyK-OIb3JNqrx1vQ9lO6GDWD6T6KAd_wq2weK3MjDWR7usCA7dZ-rp0ATgeRCyiHvJsWLf-ii0p515bYeHeZRwc2ut95k_BvXODfFNecOSkz15QL9UegWIEXeHgF9lM0dfRMsx7xszOQhulD1iehzfvWLGm5kNO5b1tn5v-iBB65sMmFZWMUobp-9PjTVSbAf8ShQAIP_aB0Z3cK08djmvRGH_bczAv9ZA18AfZTbn4GTFWkvD0NnUpWFOIBh6z32EdXX6dBfv4JArWXYPin0wNSq87WZTToyieRh0v3fh7AM7GDaeg2aHYDEbKavRaP9MCY4nHZVhmxtdYTIhjCd00rrGwomySo66t4CR5NPYFZFU57JUv0QpJAZe-_vhlJRnlkxuTDv4h6-tQMTYePoPy2-NweSmICPJgtg0KENgy0z4INnkP_-8tvK3gymyGLcUNauwrX9VHNZI06eonCIZwUmE349jMB8wmkRaILKVJOAAvlEG1bvm03Q8rBA-KGUj9o9pe7gAx0hFZvdsWyfPl3oAl6OrZusrcsiYhcvphlRsjpySHMZftmMJ7JogZ6Mp6jGuAyVdObnwl0zBG_Zb2eYTUmiyVfJfMySJKfpKq16I5RVuwSNzJvDIEGgsMi__91NOOwspn2Ziy5uvEgvE-igHWyoMeXNVqK4GpMwOoa97YLi31Z5hvU1DFK9X8-Zola3sBh5Az8b8049w7GyvfaCLkZ-vUGYPOJbik91hOWCzhYttAIvLMNg1hdNekLmLGfCIXL17B8dVw4BSHecasAjiSeTI2Tc1b5CMJLj0J78HoWL4jABiS8NgklKy87CNikAwxwFfvbsD4hEm8yIJY6vnqznahiAZ6MN6mIsLRKA2SX4bWd-I1Pj6CFv5GvEQW70rEbM_y1KahJDlXqI9rRAxtRMOBWFPspk1jymKkApTpE6LlAoGQfk8Cu3yRRKou0CHLR6GKNWRpbEDa_1tj3K3ENlZqdha5w4f_yTRMfSnkdKkVRgMVEN8BEHfbOmEAPdW1v-jUnYEROi_rM9hE762-OjcbRBu7vhJV_yNtk1BZUCdzuXh4ImGuxiq0u6aXgK0JQTxTTfTf-kvISToF8s7vi-0ry7dcMEABTxm7zzEBsITkAHBuqFN-knPHy6Z7U9SILKuReYXWdh-FvOU9QGxFDnf3eHWCuXM5kx0ge_yMfTMJHU5pohBPfVEzTeEwH4u3zdJJYacEeQzo7Ic-WjEeOpHeE_NgExWfg-qr6qxCGhqRfY7huWpysa3BGqQgUoPjTrqhwAhos32kxh9A_jAatbEIuMfFDUkgiGuTihbXvVHHvkU_UqrkuG07f2KakKiZXUX65brHU__q7prE1CFBCmxctNjxt4a7Cuq9LSkj6lhG7_B2SFrxoCYZFMRWbdAbtH0mfYV-ke4IFH_U1m1VQyiYe7AAFtTPdUy-Fv5CxrIzoPBhGHJs_8eGROSV9W2gjcMibtv5J121S5Fi7P89JxdPiJAOjMNERJYPzLBjTJudLuYdIk1AwMZQytSC8RTWUQyGfSqTLMggDqiMFL3qWzVIt4KheIKI5LuGT1dnPmC4kRZmZjNElceonFhO7DgjwxwRodNu0Q-9YEKbL8CUtQxoOV5ze7iA2_BcRTa4TwfHdljLrplfvkMq4dmZMOwWnNaWXb9buyEzE-MPbHEMukvwjTDbC1kYRuGP9SONqtS22Q-vI1IrIlSXe921Ci3TJm0DbRv64miGFG6Qh3i6hiMGsg9D_34JHqmMg3fxe0_aHh0imb-lV2c2IBCyU5nL_wHFXYj32YID3Bn6Sf5oB8mz7owEhQnheN92gUMXNAskFVXndkdfv-4rVVI8V7ldwEtpcIY6LbWFf2ao75sx_E3Btt_PUqhgRGH1xkkzj-coO6D4YfD2QbvcAHm_5KDaTVWkeBvQv78NsU7FJ-oZ0Ee-jV5Mpo5Gmrl6Wc1moTIBDg0A8Kf1LD1xMB5l7uAxvL3oRs32qOqEQ1Exfdp4yGwqP5sl2EQSZcvV-3sLf8tYiiM-SiTdGFXwYxqYJh644_rqxGsFNMoKaIYM0-6rOG9bD7yJ85w_dkPNkaPEL7ixrO0IqIQCSuQXlWQgZmmBkKUxWJINr8KzI2_Q8MmRgbiwJpFPpyt8x_D4YCE5MLrIFAVeDVVQQRrMfraadqfhG9d512rv0LqyGLaXJRjAmB28EA2xgoCgUb8t1Z2QiEqFKPPH-jDhLDbOK3Vcs2MbyigAn6YLR4wXCP9EF2dfbOTMTEVASdUeOzbVoss1q-Tq67JHk56Bj-a4JdcMfqtWieDMJMz95GqOiGiFo9juJVETgUxlf3RzjitxFTx4jzYJgSzBIZsvIViTEcvT_OWAfCi07cWYdFUrjIeZhDSKljdGqx2xT-5zxXbB6eBgCTyiOIuvAOKuYKy2E1DjIQhAbLYRDRASDWPSupMjmabXFn0AKuVZEv1J9OLKCnOZ850MaKHTdxKNRwqoiTqF497x9JmhQXH-tOAHTuekGfGDVatIaEc6jholPFVU0Lmol70Ceiwwu-Lia_LOwsPXmdsnwUgKCb1G2Uu4n42H84FQtjpsV7VqJdoD_-OHdOu6pIgfsgDeuSo8pedDl93roqVXPIFU578oNTDhQwulRj5--FebuLr2BCX32FXlWyt-sh7ZkAesPnaGFwGJ1T2nPr2ieHx97DeNGTOwj0uo9Nv9sOgJjQmg8sWYi8jGqtXSO4J_2of5LeeF1zQ5vuFOb4JPtU22VFCqyHtH9SdickglhUBI4qCunmKJY0beqUC4bj7aRzDtUUq313qUzIgjnn40oYhbljsIkOLIxoRYIL_hzxBvY7R9ngrsNq7_AE55mHyfDb0CMh9DhXZu6Az8ge5P1hr8WD_d7qfTe_DCOUhvoQBLDcUpivqEp_n79IQ8nkkpn7dd0MpnfQpjN4JyYgA=",
          "id": "rs_0a43e10fa0d9a177016a034ea3d81c81919f50774051d418e3",
          "summary": []
        }
      ]
    },
    {
      "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\"?"
    },
    {
      "role": "assistant",
      "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'/'sessions', Path.home()/'.hermes'/'webui'/'sessions']\\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 roots:\\n    if root.exists():\\n        files += [p for p in root.rglob('*') if p.is_file() and p.stat().st_size < 5_000_000]\\nfiles.sort(key=lambda p: p.stat().st_mtime, reverse=True)\\ntoken=None\\nfor p in files[:200]:\\n    try:\\n        txt=p.read_text(errors='ignore')\\n    except Exception:\\n        continue\\n    matches=pat.findall(txt)\\n    # prefer the token-like UUID from the latest user message; don't print it\\n    if matches:\\n        token=matches[-1]\\n        break\\n\\nif not token:\\n    print(json.dumps({'ok': False, 'error': 'no_uuid_token_found_in_recent_session_files'}))\\n    raise SystemExit(0)\\n\\nprint(json.dumps({'ok': True, 'token_found': True, 'token_len': len(token)}))\\n\\nbase='https://www.presupuestoabierto.gob.ar'\\nheaders_variants = {\\n    'Authorization raw': {'Authorization': token},\\n    'Authorization Bearer': {'Authorization': f'Bearer {token}'},\\n    'X-API-Key': {'X-API-Key': token},\\n}\\n\\n# First inspect known schema endpoint and likely API endpoints.\\nurls = [\\n    base+'/api/jsonCredito',\\n    base+'/api/v1/credito',\\n    base+'/api/credito',\\n]\\nfor url in urls:\\n    try:\\n        r=requests.get(url, timeout=20)\\n        print(json.dumps({'probe':'GET','url':url,'status':r.status_code,'ctype':r.headers.get('content-type','')[:80],'body_start':r.text[:220].replace(token,'[REDACTED]')}))\\n    except Exception as e:\\n        print(json.dumps({'probe':'GET','url':url,'error':repr(e)}))\\n\\n# Try minimal POSTs against likely credito endpoints with auth variants.\\n# Query shape kept deliberately tiny; goal is auth validation, not full data retrieval.\\npayloads = [\\n    {},\\n    {'title':'credito','ejercicio':2026},\\n    {'ejercicios':[2026]},\\n    {'columns':[], 'filters':[]},\\n]\\nfor endpoint in [base+'/api/v1/credito', base+'/api/credito']:\\n    for hname,h in headers_variants.items():\\n        hh = dict(h)\\n        hh.update({'Content-Type':'application/json','Accept':'application/json'})\\n        for i,payload in enumerate(payloads):\\n            try:\\n                r=requests.post(endpoint, headers=hh, json=payload, timeout=30)\\n                body=r.text[:500].replace(token,'[REDACTED]')\\n                print(json.dumps({'probe':'POST','endpoint':endpoint,'auth':hname,'payload_idx':i,'status':r.status_code,'ctype':r.headers.get('content-type','')[:80],'body_start':body}, ensure_ascii=False))\\n                # If auth passed but payload invalid, enough. If 200, stop this endpoint/auth.\\n                if r.status_code not in (401,403,404):\\n                    break\\n            except Exception as e:\\n                print(json.dumps({'probe':'POST','endpoint':endpoint,'auth':hname,'payload_idx':i,'error':repr(e)}))\\nPY\", \"timeout\": 120}"
          }
        }
      ],
      "finish_reason": "tool_calls",
      "codex_reasoning_items": [
        {
          "type": "reasoning",
          "encrypted_content": 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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": "{\"output\": \"{\\\"ok\\\": true, \\\"token_found\\\": true, \\\"token_len\\\": 36}\\n{\\\"probe\\\": \\\"GET\\\", \\\"url\\\": \\\"https://www.presupuestoabierto.gob.ar/api/jsonCredito\\\", \\\"status\\\": 200, \\\"ctype\\\": \\\"text/plain;charset=UTF-8\\\", \\\"body_start\\\": \\\"{\\\\n\\\\t\\\\\\\"$schema\\\\\\\": \\\\\\\"http://json-schema.org/draft-07/schema#\\\\\\\",\\\\n\\\\t\\\\\\\"$id\\\\\\\": \\\\\\\"https://www.presupuestoabierto.gob.ar/api/json/query-credito.schema.json\\\\\\\",\\\\n\\\\t\\\\\\\"title\\\\\\\": \\\\\\\"Esquema que describe consultas sobre el credito del presupuesto\\\\\\\",\\\\n\\\\t\\\\\\\"\\\"}\\n{\\\"probe\\\": \\\"GET\\\", \\\"url\\\": \\\"https://www.presupuestoabierto.gob.ar/api/v1/credito\\\", \\\"status\\\": 405, \\\"ctype\\\": \\\"application/json\\\", \\\"body_start\\\": \\\"{\\\\\\\"timestamp\\\\\\\":\\\\\\\"2026-05-12T16:03:03.254+00:00\\\\\\\",\\\\\\\"status\\\\\\\":405,\\\\\\\"error\\\\\\\":\\\\\\\"Method Not Allowed\\\\\\\",\\\\\\\"path\\\\\\\":\\\\\\\"/api/v1/credito\\\\\\\"}\\\"}\\n{\\\"probe\\\": \\\"GET\\\", \\\"url\\\": \\\"https://www.presupuestoabierto.gob.ar/api/credito\\\", \\\"status\\\": 404, \\\"ctype\\\": \\\"application/json\\\", \\\"body_start\\\": \\\"{\\\\\\\"timestamp\\\\\\\":\\\\\\\"2026-05-12T16:03:03.417+00:00\\\\\\\",\\\\\\\"status\\\\\\\":404,\\\\\\\"error\\\\\\\":\\\\\\\"Not Found\\\\\\\",\\\\\\\"path\\\\\\\":\\\\\\\"/api/credito\\\\\\\"}\\\"}\\n{\\\"probe\\\": \\\"POST\\\", \\\"endpoint\\\": \\\"https://www.presupuestoabierto.gob.ar/api/v1/credito\\\", \\\"auth\\\": \\\"Authorization raw\\\", \\\"payload_idx\\\": 0, \\\"status\\\": 400, \\\"ctype\\\": \\\"application/json\\\", \\\"body_start\\\": \\\"{\\\\\\\"statusCode\\\\\\\":400,\\\\\\\"message\\\\\\\":\\\\\\\"Internal error: [1,2][] The object must have a property whose name is \\\\\\\\\\\\\\\"columns\\\\\\\\\\\\\\\".\\\\\\\",\\\\\\\"detail\\\\\\\":\\\\\\\"\\\\\\\"}\\\"}\\n{\\\"probe\\\": \\\"POST\\\", \\\"endpoint\\\": \\\"https://www.presupuestoabierto.gob.ar/api/v1/credito\\\", \\\"auth\\\": \\\"Authorization Bearer\\\", \\\"payload_idx\\\": 0, \\\"status\\\": 400, \\\"ctype\\\": \\\"application/json\\\", \\\"body_start\\\": \\\"{\\\\\\\"statusCode\\\\\\\":400,\\\\\\\"message\\\\\\\":\\\\\\\"Internal error: [1,2][] The object must have a property whose name is \\\\\\\\\\\\\\\"columns\\\\\\\\\\\\\\\".\\\\\\\",\\\\\\\"detail\\\\\\\":\\\\\\\"\\\\\\\"}\\\"}\\n{\\\"probe\\\": \\\"POST\\\", \\\"endpoint\\\": \\\"https://www.presupuestoabierto.gob.ar/api/v1/credito\\\", \\\"auth\\\": \\\"X-API-Key\\\", \\\"payload_idx\\\": 0, \\\"status\\\": 401, \\\"ctype\\\": \\\"application/json;charset=ISO-8859-1\\\", \\\"body_start\\\": \\\"{\\\\\\\"statusCode\\\\\\\":401,\\\\\\\"message\\\\\\\":\\\\\\\"Debe indicar el header Authorization en la petición\\\\\\\",\\\\\\\"detail\\\\\\\":\\\\\\\"\\\\\\\"}\\\"}\\n{\\\"probe\\\": \\\"POST\\\", \\\"endpoint\\\": \\\"https://www.presupuestoabierto.gob.ar/api/v1/credito\\\", \\\"auth\\\": \\\"X-API-Key\\\", \\\"payload_idx\\\": 1, \\\"status\\\": 401, \\\"ctype\\\": \\\"application/json;charset=ISO-8859-1\\\", \\\"body_start\\\": \\\"{\\\\\\\"statusCode\\\\\\\":401,\\\\\\\"message\\\\\\\":\\\\\\\"Debe indicar el header Authorization en la petición\\\\\\\",\\\\\\\"detail\\\\\\\":\\\\\\\"\\\\\\\"}\\\"}\\n{\\\"probe\\\": \\\"POST\\\", \\\"endpoint\\\": \\\"https://www.presupuestoabierto.gob.ar/api/v1/credito\\\", \\\"auth\\\": \\\"X-API-Key\\\", \\\"payload_idx\\\": 2, \\\"status\\\": 401, \\\"ctype\\\": \\\"application/json;charset=ISO-8859-1\\\", \\\"body_start\\\": \\\"{\\\\\\\"statusCode\\\\\\\":401,\\\\\\\"message\\\\\\\":\\\\\\\"Debe indicar el header Authorization en la petición\\\\\\\",\\\\\\\"detail\\\\\\\":\\\\\\\"\\\\\\\"}\\\"}\\n{\\\"probe\\\": \\\"POST\\\", \\\"endpoint\\\": \\\"https://www.presupuestoabierto.gob.ar/api/v1/credito\\\", \\\"auth\\\": \\\"X-API-Key\\\", \\\"payload_idx\\\": 3, \\\"status\\\": 401, \\\"ctype\\\": \\\"application/json;charset=ISO-8859-1\\\", \\\"body_start\\\": \\\"{\\\\\\\"statusCode\\\\\\\":401,\\\\\\\"message\\\\\\\":\\\\\\\"Debe indicar el header Authorization en la petición\\\\\\\",\\\\\\\"detail\\\\\\\":\\\\\\\"\\\\\\\"}\\\"}\\n{\\\"probe\\\": \\\"POST\\\", \\\"endpoint\\\": \\\"https://www.presupuestoabierto.gob.ar/api/credito\\\", \\\"auth\\\": \\\"Authorization raw\\\", \\\"payload_idx\\\": 0, \\\"status\\\": 405, \\\"ctype\\\": \\\"application/json\\\", \\\"body_start\\\": \\\"{\\\\\\\"timestamp\\\\\\\":\\\\\\\"2026-05-12T16:03:04.591+00:00\\\\\\\",\\\\\\\"status\\\\\\\":405,\\\\\\\"error\\\\\\\":\\\\\\\"Method Not Allowed\\\\\\\",\\\\\\\"path\\\\\\\":\\\\\\\"/api/credito\\\\\\\"}\\\"}\\n{\\\"probe\\\": \\\"POST\\\", \\\"endpoint\\\": \\\"https://www.presupuestoabierto.gob.ar/api/credito\\\", \\\"auth\\\": \\\"Authorization Bearer\\\", \\\"payload_idx\\\": 0, \\\"status\\\": 405, \\\"ctype\\\": \\\"application/json\\\", \\\"body_start\\\": \\\"{\\\\\\\"timestamp\\\\\\\":\\\\\\\"2026-05-12T16:03:04.754+00:00\\\\\\\",\\\\\\\"status\\\\\\\":405,\\\\\\\"error\\\\\\\":\\\\\\\"Method Not Allowed\\\\\\\",\\\\\\\"path\\\\\\\":\\\\\\\"/api/credito\\\\\\\"}\\\"}\\n{\\\"probe\\\": \\\"POST\\\", \\\"endpoint\\\": \\\"https://www.presupuestoabierto.gob.ar/api/credito\\\", \\\"auth\\\": \\\"X-API-Key\\\", \\\"payload_idx\\\": 0, \\\"status\\\": 405, \\\"ctype\\\": \\\"application/json\\\", \\\"body_start\\\": \\\"{\\\\\\\"timestamp\\\\\\\":\\\\\\\"2026-05-12T16:03:04.910+00:00\\\\\\\",\\\\\\\"status\\\\\\\":405,\\\\\\\"error\\\\\\\":\\\\\\\"Method Not Allowed\\\\\\\",\\\\\\\"path\\\\\\\":\\\\\\\"/api/credito\\\\\\\"}\\\"}\", \"exit_code\": 0, \"error\": null}",
      "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.get('required'))\\nprint('properties', list(schema.get('properties',{}).keys()))\\nfor k,v in schema.get('properties',{}).items():\\n    print('\\\\nPROP', k)\\n    for kk in ['type','description','required','items','properties','enum','oneOf','anyOf','$ref']:\\n        if kk in v:\\n            s=json.dumps(v[kk], ensure_ascii=False)[:1200]\\n            print(kk, s)\\nPY\",\"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": "{\"output\": \"top keys ['$schema', '$id', 'title', 'description', 'definitions', 'type', 'required', 'additionalProperties', 'properties']\\nrequired ['columns']\\nproperties ['title', 'ejercicios', 'columns', 'filters', 'order']\\n\\nPROP title\\ntype \\\"string\\\"\\n\\nPROP ejercicios\\ntype \\\"array\\\"\\nitems {\\\"$ref\\\": \\\"#ejercicioFilterDef\\\", \\\"default\\\": [\\\"vigente\\\"]}\\n\\nPROP columns\\ntype \\\"array\\\"\\nitems {\\\"$ref\\\": \\\"#columnDef\\\"}\\n\\nPROP filters\\n$ref \\\"#arrayConditionDef\\\"\\n\\nPROP order\\ntype \\\"array\\\"\\nitems {\\\"$ref\\\": \\\"#orderDef\\\"}\", \"exit_code\": 0, \"error\": null}",
      "tool_call_id": "call_MUvQGAL0B8DXyRUloWK7bdXK"
    },
    {
      "role": "assistant",
      "content": "",
      "tool_calls": [
        {
          "id": "call_Zv0GCHMmkQVSqfiBdE4XNNel",
          "call_id": "call_Zv0GCHMmkQVSqfiBdE4XNNel",
          "response_item_id": "fc_0a64543e6208048d016a034f48ada081918587e11e8653732f",
          "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()\\ndefs=schema['definitions']\\nprint('definitions', list(defs.keys()))\\nfor name in defs:\\n    print('\\\\n##', name)\\n    obj=defs[name]\\n    print(json.dumps(obj, ensure_ascii=False, indent=2)[:3000])\\nPY\",\"timeout\":60}"
          }
        }
      ],
      "finish_reason": "tool_calls"
    },
    {
      "role": "tool",
      "content": "{\"output\": \"definitions ['columnDef', 'oneValueOperatorDef', 'twoValueOperatorDef', 'oneValueConditionDef', 'twoValueConditionDef', 'finalConditionDef', 'andConditionDef', 'orConditionDef', 'notConditionDef', 'compoundConditionDef', 'conditionDef', 'arrayConditionDef', 'orderDef', 'ejercicioFilterDef']\\n\\n## columnDef\\n{\\n  \\\"$id\\\": \\\"#columnDef\\\",\\n  \\\"enum\\\": [\\n    \\\"impacto_presupuestario_fecha\\\",\\n    \\\"impacto_presupuestario_anio\\\",\\n    \\\"impacto_presupuestario_mes\\\",\\n    \\\"ejercicio_presupuestario\\\",\\n    \\\"sector_id\\\",\\n    \\\"sector_desc\\\",\\n    \\\"subsector_id\\\",\\n    \\\"subsector_desc\\\",\\n    \\\"caracter_id\\\",\\n    \\\"caracter_desc\\\",\\n    \\\"jurisdiccion_id\\\",\\n    \\\"jurisdiccion_desc\\\",\\n    \\\"subjurisdiccion_id\\\",\\n    \\\"subjurisdiccion_desc\\\",\\n    \\\"entidad_id\\\",\\n    \\\"entidad_desc\\\",\\n    \\\"servicio_id\\\",\\n    \\\"servicio_desc\\\",\\n    \\\"programa_id\\\",\\n    \\\"programa_desc\\\",\\n    \\\"subprograma_id\\\",\\n    \\\"subprograma_desc\\\",\\n    \\\"proyecto_id\\\",\\n    \\\"proyecto_desc\\\",\\n    \\\"actividad_id\\\",\\n    \\\"actividad_desc\\\",\\n    \\\"obra_id\\\",\\n    \\\"obra_desc\\\",\\n    \\\"finalidad_id\\\",\\n    \\\"finalidad_desc\\\",\\n    \\\"funcion_id\\\",\\n    \\\"funcion_desc\\\",\\n    \\\"inciso_id\\\",\\n    \\\"inciso_desc\\\",\\n    \\\"principal_id\\\",\\n    \\\"principal_desc\\\",\\n    \\\"parcial_id\\\",\\n    \\\"parcial_desc\\\",\\n    \\\"subparcial_id\\\",\\n    \\\"subparcial_desc\\\",\\n    \\\"clasificador_economico_8_digitos_id\\\",\\n    \\\"clasificador_economico_8_digitos_desc\\\",\\n    \\\"fuente_financiamiento_id\\\",\\n    \\\"fuente_financiamiento_desc\\\",\\n    \\\"ubicacion_geografica_id\\\",\\n    \\\"ubicacion_geografica_desc\\\",\\n    \\\"unidad_ejecutora_id\\\",\\n    \\\"unidad_ejecutora_desc\\\",\\n    \\\"prestamo_externo_id\\\",\\n    \\\"prestamo_externo_desc\\\",\\n    \\\"codigo_bapin_id\\\",\\n    \\\"codigo_bapin_desc\\\",\\n    \\\"credito_presupuestado\\\",\\n    \\\"credito_vigente\\\",\\n    \\\"credito_comprometido\\\",\\n    \\\"credito_devengado\\\",\\n    \\\"credito_pagado\\\",\\n    \\\"ultima_actualizacion_fecha\\\"\\n  ]\\n}\\n\\n## oneValueOperatorDef\\n{\\n  \\\"$id\\\": \\\"#oneValueOperatorDef\\\",\\n  \\\"enum\\\": [\\n    \\\"equal\\\",\\n    \\\"like\\\",\\n    \\\"greater_than\\\",\\n    \\\"greater_equal_than\\\",\\n    \\\"lower_than\\\",\\n    \\\"lower_equal_than\\\"\\n  ]\\n}\\n\\n## twoValueOperatorDef\\n{\\n  \\\"$id\\\": \\\"#twoValueOperatorDef\\\",\\n  \\\"enum\\\": [\\n    \\\"between\\\"\\n  ]\\n}\\n\\n## oneValueConditionDef\\n{\\n  \\\"$id\\\": \\\"#oneValueConditionDef\\\",\\n  \\\"type\\\": \\\"object\\\",\\n  \\\"additionalProperties\\\": false,\\n  \\\"required\\\": [\\n    \\\"column\\\",\\n    \\\"operator\\\",\\n    \\\"value\\\"\\n  ],\\n  \\\"properties\\\": {\\n    \\\"column\\\": {\\n      \\\"$ref\\\": \\\"#columnDef\\\"\\n    },\\n    \\\"operator\\\": {\\n      \\\"$ref\\\": \\\"#oneValueOperatorDef\\\"\\n    },\\n    \\\"value\\\": {\\n      \\\"type\\\": \\\"string\\\"\\n    }\\n  }\\n}\\n\\n## twoValueConditionDef\\n{\\n  \\\"$id\\\": \\\"#twoValueConditionDef\\\",\\n  \\\"type\\\": \\\"object\\\",\\n  \\\"additionalProperties\\\": false,\\n  \\\"required\\\": [\\n    \\\"column\\\",\\n    \\\"operator\\\",\\n    \\\"valueFrom\\\",\\n    \\\"valueTo\\\"\\n  ],\\n  \\\"properties\\\": {\\n    \\\"column\\\": {\\n      \\\"$ref\\\": \\\"#columnDef\\\"\\n    },\\n    \\\"operator\\\": {\\n      \\\"$ref\\\": \\\"#twoValueOperatorDef\\\"\\n    },\\n    \\\"valueFrom\\\": {\\n      \\\"type\\\": \\\"string\\\"\\n    },\\n    \\\"valueTo\\\": {\\n      \\\"type\\\": \\\"string\\\"\\n    }\\n  }\\n}\\n\\n## finalConditionDef\\n{\\n  \\\"$id\\\": \\\"#finalConditionDef\\\",\\n  \\\"oneOf\\\": [\\n    {\\n      \\\"$ref\\\": \\\"#oneValueConditionDef\\\"\\n    },\\n    {\\n      \\\"$ref\\\": \\\"#twoValueConditionDef\\\"\\n    }\\n  ]\\n}\\n\\n## andConditionDef\\n{\\n  \\\"$id\\\": \\\"#andConditionDef\\\",\\n  \\\"type\\\": \\\"object\\\",\\n  \\\"additionalProperties\\\": false,\\n  \\\"required\\\": [\\n    \\\"and\\\"\\n  ],\\n  \\\"properties\\\": {\\n    \\\"and\\\": {\\n      \\\"$ref\\\": \\\"#arrayConditionDef\\\"\\n    }\\n  }\\n}\\n\\n## orConditionDef\\n{\\n  \\\"$id\\\": \\\"#orConditionDef\\\",\\n  \\\"type\\\": \\\"object\\\",\\n  \\\"additionalProperties\\\": false,\\n  \\\"required\\\": [\\n    \\\"or\\\"\\n  ],\\n  \\\"properties\\\": {\\n    \\\"or\\\": {\\n      \\\"$ref\\\": \\\"#arrayConditionDef\\\"\\n    }\\n  }\\n}\\n\\n## notConditionDef\\n{\\n  \\\"$id\\\": \\\"#notConditionDef\\\",\\n  \\\"type\\\": \\\"object\\\",\\n  \\\"additionalProperties\\\": false,\\n  \\\"required\\\": [\\n    \\\"not\\\"\\n  ],\\n  \\\"properties\\\": {\\n    \\\"not\\\": {\\n      \\\"$ref\\\": \\\"#arrayConditionDef\\\"\\n    }\\n  }\\n}\\n\\n## compoundConditionDef\\n{\\n  \\\"$id\\\": \\\"#compoundConditionDef\\\",\\n  \\\"oneOf\\\": [\\n    {\\n      \\\"$ref\\\": \\\"#andConditionDef\\\"\\n    },\\n    {\\n      \\\"$ref\\\": \\\"#orConditionDef\\\"\\n    },\\n    {\\n      \\\"$ref\\\": \\\"#notConditionDef\\\"\\n    }\\n  ]\\n}\\n\\n## conditionDef\\n{\\n  \\\"$id\\\": \\\"#conditionDef\\\",\\n  \\\"oneOf\\\": [\\n    {\\n      \\\"$ref\\\": \\\"#finalConditionDef\\\"\\n    },\\n    {\\n      \\\"$ref\\\": \\\"#compoundConditionDef\\\"\\n    }\\n  ]\\n}\\n\\n## arrayConditionDef\\n{\\n  \\\"$id\\\": \\\"#arrayConditionDef\\\",\\n  \\\"type\\\": \\\"array\\\",\\n  \\\"uniqueItems\\\": true,\\n  \\\"items\\\": {\\n    \\\"$ref\\\": \\\"#conditionDef\\\"\\n  }\\n}\\n\\n## orderDef\\n{\\n  \\\"$id\\\": \\\"#orderDef\\\",\\n  \\\"oneOf\\\": [\\n    {\\n      \\\"$ref\\\": \\\"#columnDef\\\"\\n    },\\n    {\\n      \\\"type\\\": \\\"object\\\",\\n      \\\"additionalProperties\\\": false,\\n      \\\"required\\\": [\\n        \\\"column\\\",\\n        \\\"order\\\"\\n      ],\\n      \\\"properties\\\": {\\n        \\\"column\\\": {\\n          \\\"$ref\\\": \\\"#columnDef\\\"\\n        },\\n        \\\"order\\\": {\\n          \\\"enum\\\": [\\n            \\\"asc\\\",\\n            \\\"desc\\\"\\n          ]\\n        }\\n      }\\n    }\\n  ]\\n}\\n\\n## ejercicioFilterDef\\n{\\n  \\\"$id\\\": \\\"#ejercicioFilterDef\\\",\\n  \\\"oneOf\\\": [\\n    {\\n      \\\"const\\\": \\\"vigente\\\"\\n    },\\n    {\\n      \\\"type\\\": \\\"integer\\\",\\n      \\\"minimum\\\": 1995\\n    }\\n  ]\\n}\", \"exit_code\": 0, \"error\": null}",
      "tool_call_id": "call_Zv0GCHMmkQVSqfiBdE4XNNel"
    },
    {
      "role": "assistant",
      "content": "",
      "tool_calls": [
        {
          "id": "call_N9xHEbbKmRYozDhZQqRS2UrA",
          "call_id": "call_N9xHEbbKmRYozDhZQqRS2UrA",
          "response_item_id": "fc_0ead97e3b85cd2bc016a034f547c448191942d4e8ec0374b7c",
          "type": "function",
          "function": {
            "name": "terminal",
            "arguments": "{\"command\":\"python3 - <<'PY'\\nimport os, re, json, requests\\nfrom pathlib import Path\\n# Re-extract token from recent session files without printing it.\\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()/'.hermes'/'sessions', Path.home()/'.hermes'/'webui'/'sessions']:\\n    if root.exists(): files += [p for p in root.rglob('*') if p.is_file() and p.stat().st_size < 5_000_000]\\nfiles.sort(key=lambda p:p.stat().st_mtime, reverse=True)\\ntoken=None\\nfor p in files[:200]:\\n    txt=p.read_text(errors='ignore')\\n    m=pat.findall(txt)\\n    if m:\\n        token=m[-1]; break\\nif not token: raise SystemExit('token not found')\\n\\nendpoint='https://www.presupuestoabierto.gob.ar/api/v1/credito'\\nheaders={'Authorization': token, 'Content-Type':'application/json', 'Accept':'application/json'}\\nqueries=[]\\nqueries.append({\\n    'name':'minimal_columns_only',\\n    'payload': {'title':'test','ejercicios':[2026], 'columns':['inciso_id','inciso_desc','credito_pagado']}\\n})\\nqueries.append({\\n    'name':'filter_inciso_5',\\n    'payload': {'title':'test','ejercicios':[2026], 'columns':['impacto_presupuestario_fecha','inciso_id','inciso_desc','credito_pagado'], 'filters':[{'column':'inciso_id','operator':'equal','value':'5'}]}\\n})\\nqueries.append({\\n    'name':'uba_2026_05_05',\\n    'payload': {'title':'uba','ejercicios':[2026], 'columns':['impacto_presupuestario_fecha','jurisdiccion_desc','programa_desc','actividad_desc','subparcial_desc','credito_pagado','ultima_actualizacion_fecha'], 'filters':[{'column':'impacto_presupuestario_fecha','operator':'equal','value':'2026-05-05'},{'column':'subparcial_desc','operator':'equal','value':'Universidad de Buenos Aires'},{'column':'inciso_id','operator':'equal','value':'5'}], 'order':[{'column':'credito_pagado','order':'desc'}]}\\n})\\nfor q in queries:\\n    try:\\n        r=requests.post(endpoint,headers=headers,json=q['payload'],timeout=40)\\n        text=r.text.replace(token,'[REDACTED]')\\n        print('\\\\n###', q['name'], 'status', r.status_code, 'ctype', r.headers.get('content-type'))\\n        print(text[:2000])\\n    except Exception as e:\\n        print('ERR', q['name'], repr(e))\\nPY\",\"timeout\":120}"
          }
        }
      ],
      "finish_reason": "tool_calls",
      "reasoning": "**Formulating a valid query**\n\nI need to create a valid query for an API. The payload must include a list of columns, and maybe they should all be non-aggregate. It seems that the API returns results grouped by those columns. I could try a simple setup like: `columns: [\"inciso_id\",\"inciso_desc\",\"credito_pagado\"], ejercicios:[2026], filters[inciso_id equal 5], order ...`. Using token extraction again seems like a good idea, and I definitely want to ensure the output is sanitized.",
      "reasoning_content": "**Formulating a valid query**\n\nI need to create a valid query for an API. The payload must include a list of columns, and maybe they should all be non-aggregate. It seems that the API returns results grouped by those columns. I could try a simple setup like: `columns: [\"inciso_id\",\"inciso_desc\",\"credito_pagado\"], ejercicios:[2026], filters[inciso_id equal 5], order ...`. Using token extraction again seems like a good idea, and I definitely want to ensure the output is sanitized.",
      "codex_reasoning_items": [
        {
          "type": "reasoning",
          "encrypted_content": "gAAAAABqA09UsCLPswpgO6KFXXopUjhXousOWGQ8nOBwCov7l1gmKBZrfSCfPlzF-qQxd2c6oC2GRpyLvmdrfSQpdYYjEdfJJceYStlQ3nyTvQATmMpMRGo2ol8Tnsvg8KkyK0OXp3Mg79mQDB2SrIM9RCrfDzNXFipXOKWGYPDW3Z4Favv8YBaz2HNkaj7JypU9oHBChaz9SY2y87nkr1mPa7WFfQyPgPLmUWUmHbiJjz0jEDiCLRpfuD1DgJMOZyAaQPyQCO2Fcqzm1eWh44HnQMU378AcDaovZ5Zpo-csX5Fw_mML8DNxJDxsCjVmMr5RVjyIg83TAeVuyA5wXeCCC361fAigS09o-r_vE3rzG2y10RGIXOhcB_RzaAmcQpz3ji-_5aYJ-gFQm-R7g4sTROBujjYltNhUySBcURyjjNGZ3GpB9nnHWCzrM2LDa82xpeuOmxb3Kg-2b45kko2mxpnwVKBeRxCZK2KrazwHK-56w6tzqcTQ3L2ywcwlKWnU3o_0tA3_Mo8GObYOdfzXFA9zK1MmXiDpZssnKXZqMzQH5eEOEpZuWD7jvng5vbZTwR2j1T4KLcHJ57H5ax7f9xDhvamCA9SFVFsKsjIQmU0wTXdQG4_n95Lbov2E9bEcz5_9BpWZJ5brUZ9St7h-FPEeyc7J-4gv1hCQUdQ1den8CiJF3Y_BZi5eDF6TZaO79OuqyzrlL4AJ_adYU99KSvGylQ12gEaeR1kp7-pvZuc8MPu1OVOt2VQ8m7qzd5sl15mlVGvu6i_3lgxPMZakVCazoDL4XlXzjyhWZ6zXNmGPVhzU04UvHphT409zcBBhsn2QzyoLuh8KYPPXctqsNK1U6imV5cT_GuH6wgS8miHj3kvej5iTq_PiAvePmSrrBo01BTNAqXx6oRseCC_hR-MWQYzx_h3NpOxnObePHIW6zzo03RivcQGA_O79_QUoKlOQOLR3s8oUnTX9tspG-F30OoR5CGSSZVN2xxeU8n0I_Q2VG9jgA7Xt4Qb4adHKN96QNr5UOcYFXofgRDAheec_TgI-6IWgVOymPG3pGYDlPO71gBN6EyRNbv_WWsTgVp8LN8dhvQhznxDOO0Qse9fN_49dpyB0hsniIGUpCpD35nDowIVdJPKU41EjD4Zb7uFaTk3uEGZIqgvY1etNHxY4nvb-2oDZjKVREwLizpR8YDYP2uNxqu1vnPWvuC4f2PeBbJdUVmQCbNc4BCRHhoKfE5hmC3AuqJJ8BnlgYvQIDVjbP7L05rkjz0-UKRmjRtVHD1UKlQX4PYlu8HnNdpZ7mghtTsXc-wtOZ8j0QPrGLxb0Dm7GQ5ge97kZnjt9GNL0wD30Wvc17p_TUk17_60IH337Rt3HIvxzJIBvwWPGwzqCr8E=",
          "id": "rs_0ead97e3b85cd2bc016a034f4f372081919b711d9433059747",
          "summary": [
            {
              "type": "summary_text",
              "text": "**Formulating a valid query**\n\nI need to create a valid query for an API. The payload must include a list of columns, and maybe they should all be non-aggregate. It seems that the API returns results grouped by those columns. I could try a simple setup like: `columns: [\"inciso_id\",\"inciso_desc\",\"credito_pagado\"], ejercicios:[2026], filters[inciso_id equal 5], order ...`. Using token extraction again seems like a good idea, and I definitely want to ensure the output is sanitized."
            }
          ]
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"output\": \"### minimal_columns_only status 200 ctype application/json\\n[{\\\"inciso_id\\\":1,\\\"inciso_desc\\\":\\\"Gastos en personal\\\",\\\"credito_pagado\\\":4720863.81375389},{\\\"inciso_id\\\":2,\\\"inciso_desc\\\":\\\"Bienes de consumo\\\",\\\"credito_pagado\\\":264896.69179105},{\\\"inciso_id\\\":3,\\\"inciso_desc\\\":\\\"Servicios no personales\\\",\\\"credito_pagado\\\":468945.70878804},{\\\"inciso_id\\\":4,\\\"inciso_desc\\\":\\\"Bienes de uso\\\",\\\"credito_pagado\\\":143688.34099074},{\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":33605900.54247986},{\\\"inciso_id\\\":6,\\\"inciso_desc\\\":\\\"Incremento de activos financieros\\\",\\\"credito_pagado\\\":105895.99489641},{\\\"inciso_id\\\":7,\\\"inciso_desc\\\":\\\"Servicio de la deuda y disminución de otros pasivos\\\",\\\"credito_pagado\\\":5896450.49745572},{\\\"inciso_id\\\":8,\\\"inciso_desc\\\":\\\"Otros gastos\\\",\\\"credito_pagado\\\":0}]\\n\\n### filter_inciso_5 status 200 ctype application/json\\n[{\\\"impacto_presupuestario_fecha\\\":\\\"2026-01-20 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":0},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-01-21 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":0},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-01-22 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":4439.74548793},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-01-23 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":38696.400258},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-01-26 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":18003.57876966},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-01-27 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":71595.09364391},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-01-28 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":391109.49797428},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-01-29 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":918664.08450846},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-01-30 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":5328536.99720556},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-02-02 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":36834.85019905},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-02-03 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":373969.82810208},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-02-04 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":137515.44449291},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-02-05 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":212719.01792982},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-02-06 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":36483.48664289},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-02-09 00:00:00\\\",\\\"inciso_id\\\":5,\\\"inciso_desc\\\":\\\"Transferencias\\\",\\\"credito_pagado\\\":160144.72227061},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-02\\n\\n### uba_2026_05_05 status 200 ctype application/json\\n[{\\\"impacto_presupuestario_fecha\\\":\\\"2026-05-05 00:00:00\\\",\\\"jurisdiccion_desc\\\":\\\"Ministerio de Capital Humano\\\",\\\"programa_desc\\\":\\\"Desarrollo de la Educacion Superior\\\",\\\"actividad_desc\\\":\\\"Asistencia Financiera para el Pago de Salario del Personal no Docente\\\",\\\"subparcial_desc\\\":\\\"Universidad de Buenos Aires\\\",\\\"credito_pagado\\\":32455.015624,\\\"ultima_actualizacion_fecha\\\":\\\"2026-05-11 00:00:00\\\"},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-05-05 00:00:00\\\",\\\"jurisdiccion_desc\\\":\\\"Ministerio de Capital Humano\\\",\\\"programa_desc\\\":\\\"Desarrollo de la Educacion Superior\\\",\\\"actividad_desc\\\":\\\"Asistencia Financiera para el Pago de Salario Docente y Autoridades Superiores\\\",\\\"subparcial_desc\\\":\\\"Universidad de Buenos Aires\\\",\\\"credito_pagado\\\":28449.187754,\\\"ultima_actualizacion_fecha\\\":\\\"2026-05-11 00:00:00\\\"},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-05-05 00:00:00\\\",\\\"jurisdiccion_desc\\\":\\\"Ministerio de Capital Humano\\\",\\\"programa_desc\\\":\\\"Desarrollo de la Educacion Superior\\\",\\\"actividad_desc\\\":\\\"Asistencia Financiera a Hospitales Universitarios\\\",\\\"subparcial_desc\\\":\\\"Universidad de Buenos Aires\\\",\\\"credito_pagado\\\":1664.038468,\\\"ultima_actualizacion_fecha\\\":\\\"2026-05-11 00:00:00\\\"},{\\\"impacto_presupuestario_fecha\\\":\\\"2026-05-05 00:00:00\\\",\\\"jurisdiccion_desc\\\":\\\"Ministerio de Economía\\\",\\\"programa_desc\\\":\\\"Regulacion del Transporte y Distribucion de Gas\\\",\\\"actividad_desc\\\":\\\"Regulacion del Transporte y Distribucion de Gas\\\",\\\"subparcial_desc\\\":\\\"Universidad de Buenos Aires\\\",\\\"credito_pagado\\\":0,\\\"ultima_actualizacion_fecha\\\":\\\"2026-05-11 00:00:00\\\"}]\", \"exit_code\": 0, \"error\": null}",
      "tool_call_id": "call_N9xHEbbKmRYozDhZQqRS2UrA"
    },
    {
      "role": "assistant",
      "content": "",
      "tool_calls": [
        {
          "id": "call_0aaxrI3biHDIMDR0QOKqghzh",
          "call_id": "call_0aaxrI3biHDIMDR0QOKqghzh",
          "response_item_id": "fc_017f86f32ff074e3016a034f921ed08191a2aa2d0dc4f07c87",
          "type": "function",
          "function": {
            "name": "terminal",
            "arguments": "{\"command\":\"python3 - <<'PY'\\nimport re, requests, json\\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()/'.hermes'/'sessions', Path.home()/'.hermes'/'webui'/'sessions']:\\n    if root.exists(): files += [p for p in root.rglob('*') if p.is_file() and p.stat().st_size < 5_000_000]\\nfiles.sort(key=lambda p:p.stat().st_mtime, reverse=True)\\ntoken=None\\nfor p in files[:200]:\\n    m=pat.findall(p.read_text(errors='ignore'))\\n    if m: token=m[-1]; break\\nheaders={'Authorization':token,'Content-Type':'application/json','Accept':'application/json'}\\nendpoint='https://www.presupuestoabierto.gob.ar/api/v1/credito'\\nqueries={\\n 'uba_annual_summary': {\\n   'title':'UBA anual', 'ejercicios':[2026],\\n   'columns':['subparcial_desc','credito_pagado','credito_vigente','ultima_actualizacion_fecha'],\\n   'filters':[{'column':'subparcial_desc','operator':'equal','value':'Universidad de Buenos Aires'},{'column':'inciso_id','operator':'equal','value':'5'}]\\n },\\n 'top_transfer_destinations_paid_gt0': {\\n   'title':'Top transferencias por subparcial', 'ejercicios':[2026],\\n   'columns':['subparcial_desc','credito_pagado','credito_vigente'],\\n   'filters':[{'column':'inciso_id','operator':'equal','value':'5'},{'column':'credito_pagado','operator':'greater_than','value':'0'}],\\n   'order':[{'column':'credito_pagado','order':'desc'}]\\n },\\n 'latest_transfer_days_paid_gt0': {\\n   'title':'dias transferencias', 'ejercicios':[2026],\\n   'columns':['impacto_presupuestario_fecha','inciso_desc','credito_pagado'],\\n   'filters':[{'column':'inciso_id','operator':'equal','value':'5'},{'column':'credito_pagado','operator':'greater_than','value':'0'}],\\n   'order':[{'column':'impacto_presupuestario_fecha','order':'desc'}]\\n }\\n}\\nfor name,payload in queries.items():\\n    r=requests.post(endpoint,headers=headers,json=payload,timeout=40)\\n    print('\\\\n##', name, 'status', r.status_code, 'len', len(r.text))\\n    try:\\n        data=r.json()\\n        print('rows', len(data) if isinstance(data,list) else 'non-list')\\n        print(json.dumps(data[:5] if isinstance(data,list) else data, ensure_ascii=False)[:2500])\\n    except Exception:\\n        print(r.text[:1200].replace(token,'[REDACTED]'))\\nPY\",\"timeout\":120}"
          }
        }
      ],
      "finish_reason": "tool_calls",
      "codex_reasoning_items": [
        {
          "type": "reasoning",
          "encrypted_content": "gAAAAABqA0-SHvNTeasi-7kiqnjz40qhGnMv67gjdu1qIIvklJ31xo_25p6dLv1pIiOChjOuLthuKI0gmLDPA8LoZZUXD_Ed_a6bGA8z7WKIbm3rRLDi-3clxlf7FYrTAkWg6hfBx9rli1pePFCkJ371fCupfacnuQSNZEPwEHPlejJC8wJniTl7eFwVOPrONboWVDwh9FN0s0W48sRWAtKBQjYus8QYDWX0dYvqcQ37nyP3PZKXhPSVmU18NRv3Ju7cAz7mpldjv6_er-F4fgIfJjWapLjBFvKQ990aEOjad72EUO9ByJq5hDCK6D63RjiYdDPd3UoYAoQMqZ8ChizpDigKuN-2daAXNEri1JEIdSLzMsXAfHG_LFdrlTqKmb0fzkEKQh-vMM3tTjk6ZeytruAeae81weNNlYGfozvqKEKxDAY1c0NpS5gn7AlXyyWjqMWCQyQLjXQo5hEhUTA98pepdgD8QNY5TaSWsq0MJj0lJzsg4Zn6qw6cjaszqxZpG5obE0OBsD4fRaYJ9bv4Ju6Y1nsQQ3cShPyf4Yd2RpBpQbXpDnFR_BzfIM1wrLW7sfQKzXzDtQYmMf7tHEh5i1eqnIPN3kx8W3EXq5B5188GMpjENnMWhxLvp2GKUGG7mZ-_QD02xOM4teQT9oe5KhqtSNnCbfEjw3NcCNqr1PGVjgBgoz2gdMHW5pzhNzyj2d-bvqkKIBX562WfJnDBoMtYyxEethC6Lc8CN6WIdsq-hwwgwr9I9yFMJ8HAE74o4Ylw90aCMpXr0flO57OBlHBN7jPQSx9HbqoyW7d-wkKvuUSZWS3SrdZPPLakqyEL65XvIFBaFEDhw6MnUWbsYIF4AWr0AqtfR1VQPZGmKdyQ6Ly9k1D2ojdrstVg-dOJnOwfoqTTuzvLTuPm2X-aRwPgVIhylxwkPaufPGfC49N7gJDu1ERQjboXoXTin88_aN9PQCSRB5sZLbG96Hb8lMCqbLWpIK3ajcghTGonJaQD8U4bgBdKqIIlQ9LB_rBWDAHJuFMB4XWLUuHrUa2layrvruIgTh8nuTuVmFvt_K7fPK1BGAAD4c9eHg-4a8INP44PcvzFeHYaT4N-ujGodJIWLE_ZVy7ev0QT7W7fw73XS1DJjOx8DXzMbT0cGoyOMLIGNFgriVdNpHfJGIsj6IKcb0LA7_AtskTIMlz6ozAVEOWFLnvJPPDbL92YG5fldh64tDDDG1_eU97BVMWYbtPoyxV-AZuFaAveR_lvS7Agh1GStZsM_Uu_O9cAA6Xxsf5lZkPnufJAKryD5yX_8ZqmzsQznkIJQeTQhCQWu0J_RBwGO7RmcHUGH4ehzJ8t1unneb9kzFlKjEfG3yGFmKPVnT1A5bXB_VbTRn8h2eD5Oc2zuNo4NDuneWG2VA-0-ICJGkRXFuKIo3Bljt8k5FzK9B4kp53AYN_b07AQRanFQ1mSp6pzp6W_JNkPzpV0Zge1nfwn6a0VgGB-8g-YxhJ0o7RcngNaoQRvw-PYiCn1zCCHwtByl19jeP-hr8p87iSfb9VVjK72a8tsFhXSgPHtysrLN8Hwo0w2uWnCkgmogVOSlGxh5oejbYIvZLAop7EDh-otVxR-BmBdI71g1AtzYaZdWTMwmgOVCsJgNNd7B_cm9p0ark-DJEbPFSLvZ9mzdb-FCj7iPXeErZYZY04Ozf0L-6povByF1U12T6vhtMCEOsbaigFfOFw-rQFvGiVT6UhcopSTJLaxPJL9d1mQnV0bc7zg4TYLrJsNeaqPmRsRkaZernc_MLvzVLln8K2-knLn76SEagaiTANDzOAFPm9sDD1kbQYjCnw85etZi_HmhC7b2K353I-IeqDhhjaMAZId06sCB9Vywg1tNRL2SzgDcQvZqhHaqlyhjhxiDPtAZcelzJWKiwjmAQNT5e40hh3hu949VBpY6DAL20txKWHbHx6_bmEf0KvL0T4lyi2LA5wlx1z2D3M6yvoTwVyprXnrn12qHyssJP-wEt-2Hzzm0Ay_iEj7TQte2NNg-nIFIGHYRUwH0AmfYqm7Z0mZAbpFRrT0oIZlE-Tv--0ymQiTnkkBdU90OzuKai8RtLL6yJJiGOlEdrRMvIzRiaU_5rIekKRlsqsmGzbqwD6RkAL0yIhF3h_HSEWPxg4gXdoXl51cK0JNSnky4jJYcWBg2ooLDupH-tELrB7k3BVVOaIrjEezDkUOd7WRISaLA5SDVsN7jcfsNEN2jCWA-JbPDVOC",
          "id": "rs_017f86f32ff074e3016a034f88babc8191813a9576b973996e",
          "summary": []
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    },
    {
      "role": "tool",
      "content": "{\"output\": \"## uba_annual_summary status 200 len 165\\nrows 1\\n[{\\\"subparcial_desc\\\": \\\"Universidad de Buenos Aires\\\", \\\"credito_pagado\\\": 262403.287296, \\\"credito_vigente\\\": 799460.392572, \\\"ultima_actualizacion_fecha\\\": \\\"2026-05-11 00:00:00\\\"}]\\n\\n## top_transfer_destinations_paid_gt0 status 200 len 19836\\nrows 161\\n[{\\\"subparcial_desc\\\": \\\"Jubilaciones y/o retiros\\\", \\\"credito_pagado\\\": 15254073.05687253, \\\"credito_vigente\\\": 48232463.072245}, {\\\"subparcial_desc\\\": \\\"Ayudas sociales a personas y asignaciones familiares\\\", \\\"credito_pagado\\\": 6701220.28902992, \\\"credito_vigente\\\": 20460867.699379}, {\\\"subparcial_desc\\\": \\\"Pensiones\\\", \\\"credito_pagado\\\": 5781465.77866464, \\\"credito_vigente\\\": 18946392.993808}, {\\\"subparcial_desc\\\": \\\"Compania Administradora del Mercado Mayorista Electrico\\\", \\\"credito_pagado\\\": 1287673.440784, \\\"credito_vigente\\\": 2642272}, {\\\"subparcial_desc\\\": \\\"Instituto Nacional de Servicios Sociales para Jubilados y Pensionados\\\", \\\"credito_pagado\\\": 1002799.10780584, \\\"credito_vigente\\\": 3603216.315554}]\\n\\n## latest_transfer_days_paid_gt0 status 200 len 8394\\nrows 71\\n[{\\\"impacto_presupuestario_fecha\\\": \\\"2026-05-08 00:00:00\\\", \\\"inciso_desc\\\": \\\"Transferencias\\\", \\\"credito_pagado\\\": 337087.69062}, {\\\"impacto_presupuestario_fecha\\\": \\\"2026-05-07 00:00:00\\\", \\\"inciso_desc\\\": \\\"Transferencias\\\", \\\"credito_pagado\\\": 9077.07531753}, {\\\"impacto_presupuestario_fecha\\\": \\\"2026-05-06 00:00:00\\\", \\\"inciso_desc\\\": \\\"Transferencias\\\", \\\"credito_pagado\\\": 398868.99889851}, {\\\"impacto_presupuestario_fecha\\\": \\\"2026-05-05 00:00:00\\\", \\\"inciso_desc\\\": \\\"Transferencias\\\", \\\"credito_pagado\\\": 493531.92825909}, {\\\"impacto_presupuestario_fecha\\\": \\\"2026-05-04 00:00:00\\\", \\\"inciso_desc\\\": \\\"Transferencias\\\", \\\"credito_pagado\\\": 114110.96369068}]\", \"exit_code\": 0, \"error\": null}",
      "tool_call_id": "call_0aaxrI3biHDIMDR0QOKqghzh"
    },
    {
      "role": "assistant",
      "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: <token>\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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    },
    {
      "role": "user",
      "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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      "content": "",
      "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.",
      "finish_reason": "tool_calls",
      "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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          "id": "rs_01cab3dd05d8e5e9016a0350c723348191865f42a5a4ea1143",
          "summary": [
            {
              "type": "summary_text",
              "text": "**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."
            }
          ]
        }
      ],
      "tool_calls": [
        {
          "id": "call_1NL1VMZo2MCGjonVimopa6vl",
          "call_id": "call_1NL1VMZo2MCGjonVimopa6vl",
          "response_item_id": "fc_01cab3dd05d8e5e9016a0350d0f6288191b726b729c20f2b24",
          "type": "function",
          "function": {
            "name": "web_extract",
            "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\"]}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\n  \"results\": [\n    {\n      \"url\": \"https://presupuesto-abierto.argentina.apidocs.ar/\",\n      \"title\": \"Presupuesto Abierto\",\n      \"content\": \"Presupuesto Abierto\\n\\nv1.0.0\\n\\n# API de Presupuesto Abierto​\\n\\nDescargar Documento OpenAPI\\n\\nJSON\\n\\nDescargar Documento OpenAPI\\n\\nYAML\\n\\nAPI para acceder a datos de recursos, gastos y programación y ejecución física del presupuesto nacional de Argentina.\\n\\n## Solicitud de Token de Acceso\\n\\nPara obtener un token de acceso, dirigete a https://www.presupuestoabierto.gob.ar/sici/api-pac\\n\\n## Contacto​\\n\\nContacto\\n\\n## Servidores​\\n\\nhttps://www.presupuestoabierto.gob.ar/api/v1Servidor de producción\",\n      \"error\": null\n    },\n    {\n      \"url\": \"https://presupuesto-abierto.argentina.apidocs.ar/operations/post-credito\",\n      \"title\": \"vitepress-openapi | Presupuesto Abierto\",\n      \"content\": \"vitepress-openapi | Presupuesto Abierto\\n\\n# Consulta de crédito del presupuesto​\\n\\nPOST\\n\\n/credito\\n\\nPermite acceder a datos de crédito del presupuesto nacional en sus diferentes etapas\\n\\n## Autorizaciones​\\n\\nbearerAuth\\n\\nToken de acceso para autenticación\\n\\nTipoHTTP (bearer)\\n\\n## Parámetros​\\n\\n### Query Parameters\\n\\nformat*\\n\\nFormato de respuesta\\n\\nTipostring\\n\\nRequerido\\n\\nEnum\\n\\n`json``csv``zip`\\n\\nEjemplo`json`\\n\\ndefault`csv`\\n\\n## Cuerpo de la petición​\\n\\napplication/json\\n\\nSchemaCrédito vigente por finalidad funciónCrédito vigente para 2024 y 2025 por programaJSON\\n\\nobject\\n\\ntitle\\n\\nstring\\n\\ncolumns\\n\\nstring[]\\n\\nfilters\\n\\nobject\\n\\n## Respuestas​\\n\\n200400401\\n\\nRespuesta exitosa\\n\\nContent-Type\\n\\napplication/json\\n\\nSchemaJSON\\n\\nobject\\n\\nadditionalProperties\\n\\nstring\\n\\nPOST\\n\\n/credito\\n\\n## Playground​\\n\\nAutorización\\n\\nbearerAuth\\n\\nVariables\\n\\nKey\\n\\nValue\\n\\nformat*\\n\\njson\\n\\nCuerpo\\n\\nProbar\\n\\n## Ejemplos​\\n\\ncURLJavaScriptPHPPython\\n\\ncURL\\n\\nJavaScript\\n\\nPHP\\n\\nPython\\n\\nPowered by VitePress OpenAPI\",\n      \"error\": null\n    }\n  ]\n}",
      "tool_call_id": "call_1NL1VMZo2MCGjonVimopa6vl"
    },
    {
      "role": "assistant",
      "content": "",
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          "function": {
            "name": "terminal",
            "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()/'.hermes'/'sessions', Path.home()/'.hermes'/'webui'/'sessions']:\\n    if root.exists():\\n        files += [p for p in root.rglob('*') if p.is_file() and p.stat().st_size < 5_000_000]\\nfiles.sort(key=lambda p:p.stat().st_mtime, reverse=True)\\ntoken=None\\nfor p in files[:200]:\\n    m=pat.findall(p.read_text(errors='ignore'))\\n    if m:\\n        token=m[-1]\\n        break\\nif not token:\\n    print('token not found'); raise SystemExit(1)\\nendpoint='https://www.presupuestoabierto.gob.ar/api/v1/credito?format=json'\\npayload={\\n  'title':'Crédito vigente por finalidad función',\\n  'ejercicios':[2026],\\n  'columns':['finalidad_id','finalidad_desc','funcion_id','funcion_desc','credito_vigente'],\\n  'order':[{'column':'credito_vigente','order':'desc'}]\\n}\\nheaders={'Authorization':f'Bearer {token}','Content-Type':'application/json','Accept':'application/json'}\\nr=requests.post(endpoint,headers=headers,json=payload,timeout=40)\\nprint(json.dumps({'status':r.status_code,'ctype':r.headers.get('content-type'),'bytes':len(r.content)}, ensure_ascii=False))\\ndata=r.json()\\nprint(json.dumps({'rows':len(data),'first3':data[:3]}, ensure_ascii=False, indent=2))\\n# test csv docs-compliant too, limit naturally aggregate columns; don't dump CSV fully\\nr2=requests.post('https://www.presupuestoabierto.gob.ar/api/v1/credito?format=csv',headers=headers,json=payload,timeout=40)\\nprint(json.dumps({'csv_status':r2.status_code,'csv_ctype':r2.headers.get('content-type'),'csv_start':r2.text[:180]}, ensure_ascii=False))\\nPY\",\"timeout\":120}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"output\": \"{\\\"status\\\": 200, \\\"ctype\\\": \\\"application/json\\\", \\\"bytes\\\": 4284}\\n{\\n  \\\"rows\\\": 29,\\n  \\\"first3\\\": [\\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      \\\"finalidad_id\\\": 3,\\n      \\\"finalidad_desc\\\": \\\"SERVICIOS SOCIALES\\\",\\n      \\\"funcion_id\\\": 1,\\n      \\\"funcion_desc\\\": \\\"Salud\\\",\\n      \\\"credito_vigente\\\": 8820320.483397\\n    }\\n  ]\\n}\\n{\\\"csv_status\\\": 200, \\\"csv_ctype\\\": \\\"text/csv;charset=UTF-8\\\", \\\"csv_start\\\": \\\"finalidad_id,finalidad_desc,funcion_id,funcion_desc,credito_vigente\\\\n3,SERVICIOS SOCIALES,3,Seguridad Social,83445292.926303\\\\n5,DEUDA PUBLICA,1,Servicio de la Deuda Pública,14119847\\\"}\", \"exit_code\": 0, \"error\": null}",
      "tool_call_id": "call_exiFApx94buOTXBpJetcE7qs"
    },
    {
      "role": "assistant",
      "content": "",
      "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!",
      "finish_reason": "tool_calls",
      "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!",
      "codex_reasoning_items": [
        {
          "type": "reasoning",
          "encrypted_content": "gAAAAABqA1GI81uIVsvawGYzt6YcQFNJksTBk2oHSrdNHv_PBAns2Up_Db9ddADJ06GePsBlupRdAdSJRIM3bSMqBVIwwwcCIs42e--jFHNwyO5vDpOjzmrqqnZwDLAP6xx53BAo_qT8aSdpvmkdWdpKZgEA7-WHaka5nbNJ6uaI-Feh1u6GmNuox2v56ldk5uDpEOm1GUMx6DMfm3RGf2kvEEpQA818PxoHKo8PMlPOSqu8oXM1Sm6uWP4gZIKvViqB-AsRTecHOSJgINFkbEz2_KS2tiRlsc5au6gPMsjfVJtcFpjarVqu_YDKkTs3ddpmO1UedXCcYF1hWv2Gj0xRhx_3ILa8aXLP6kSV2nxcWuNg2I_ThmX8gFLIX3MMAKxG9ZG2lFSml3Y8U1Qa3XLx_v-I8_czwPiqXQRAFQE0Rx8E-xUmvL8igRkgUAurWUW7qGq-xL7N7QAwh61CyXUdvKnFLSfvzR-BRDaNOKp4Axe0ya0ZhRawvFnF5C5rZRnYcVzyNEWKe0VljfHuR5PTx63WTghX4tmivLiwcGtH5Eons5wuDTE6aLY4tx1dXowJx6IfSc6Ne1fvSKM5nLGxK5E4i2i9AQM8Mj5zvEk3A2r9HwsjuwdNz3ZpMz7gjkcHzhCbEhVdHZgGAAsQpBfadR0AAm0Fjhh3iM4cSoz7fYbxqZvItrDAgYvYDT3_kmvzOQQa5Mo-HtkZpphl8Z4Z5fE9vlITLnPL0EDIBKDi0R9gQwkyyAtsSH3fEcf-RZLrZCG9MymrcCQNJwH2qpZLLQbm-Hhj7hcyBWjwSlrxrfDSf0eM9g0FtXawzCBPkomQJRXJp92PVyFSsc6dhwNhcA_i3llvckgcaNXfiklFhJ17uE0wqbOzE2f9PHNEMCRDtDL69WphHVBcoR6D7j1ZbSd9zjPM49g93-6tTsIUW5DfX19Bom7ohQCqCWpkmG9JmNqKjZNsG90VkoZLkPtrZCl6ONj8WMibbLrxTwBtsD1X4i0U12_cPrc4AzCD21d4cz9aOy5VOBthT53U1_HGjJT5e3B42L3eX6-cLVroauA0A-dlcj0EhDqc-L7Xpl_TjmFiSlbsOn9-KM0sdsIR_Z6sctVSDFgVIfW0AmNfOXf-AbhzZVgW1D1GUQMqVTnbdxSM3AomK8osR097FO5ClS22-OGHT_vJBHGVtyQu0M1hevPyrGjllEzkYAJD6WAasiugSihJ4-y7gvaGhmOU-JKixGFrpHLbbnxeYUtfdisnRaZWF6B9TUs8o9PnULFcKaMv3UKlBWgAtRTLd8WHfr-dAoP0poDka6_jH2F_h7uV7yVpGs8NzwCekWcMaER_uH4l8JovvepHDV3Gt-bRHD9qqo9U5CuOt_mYFIWz478JfFTxZGSq-E7T11qa1KdCFyj16WUDXCsk6g9UvC5EvKmpergMz991AhE7Tg8GaomOKZSbg4eGSqPo_0FMhvA8md80AyjZZYSqkoj2uoLxCcPKN06gazQgAFNxWk1Ql31d8mJ_0U88MN94nbhwXgqyUTZ4ZcjUCj5NjlrbyAZ2PdSjaz1tSj3nRAWDr0f4-yq9WzmHHTcQUR6iJi4B7KDXaQelhhGpuyDGskCbLnixmkF6_GxVKjevaIg7enuCtoJJ3xmfxdpjAcehYNICWuYLlHKFK4NooTAqwhU4AbWgrt9xWeALjokRDlYHudk3i9AsKK7Yokpurr2E52oeoI4O8oztDhgbbw76YFE97QfWaExCFNNFOQW4sgejGdyntHRJb2XQFnoTws4kmhbI4hpVHTUF7weC3qCGBsmwlb8xRKZ-8zky5f__yWJQdcoL4Gwx6qWIaRqQLkhPjoDYq8zYLDjWwBRj0hwRmAy0KPq9R4NXMOsU3ufWAKiwdfQxq9sZRKOXKs1W6Nxm-aMsKzzKqJcMBzCsmwYUiAdJ0iua8UCaHKs4opiThEcufOR62HEOo7jVuulKL24GEfL98Nr2u6hcZvP1YSdt1tUgGYs2wmPd-HwHGj3nSOCzqZxDw4QyLOnIeOBg3xVdHYUoAkLp2tR1OieJjdaLdBpxKFJuc3WFuvfrKOAuK4KW2Zzae6Wy6hwDb7amR-rYAqYFxO4mYC1CZQeD-93fc4IiW-YYNZuK5AUnUBLBTJpCuDgv-UHtmF0ROVaf-wkNpkN8VXY1zt_1CsmtogKbBNa13TxLSs2ud_aPcOQRNW9DtO4Nct8IzYbWQeJlin0rIPgAW1vdYMuSg0T0o3bA57P8l1btU1T9Dl-pB-hP44NR22tMXd_ZZjlLT4gr8DiKAw-WU760eOACqoCnNBaqPB9FrtnHFll7LliWmBGsS6cCL9UwQOJqj2y5BQXQqPxw9-4cFoXlCtE0bflZGm5UsEXfIABy1aYGUkmwJu0PmINKxTSfNVD_pAg8sEE2VVIXYzhyJBevIWwRT0XDh83Scw0jNmfuSoryS_VPRbXua-hMz4GLgg2mR5plAxTvt4nXkbSL2T5baqcfh3NPhLeMGzPb2--AuSn89XgAM6xmZlP8oO-N5l_j06GxPfAbK8DeycHPmiExxVfTJIZYyOuBBgXHpQErxv6dTJ3sc3n1gkKTQRcGBy70_RdUA2ntG2zYJgsddGw5uWXTeyvS4cQ3yCbUHXgFp_oN7PI3xODBBWfIkDBi-CHjZCGf7qGf2VAejgdrpF44SMWmWOxoiYhby4EFU-nYyrZapY4rEqT9l70oVru4p1BJlFyi9LOJ5T8eYmzRh8vLZhtQ7dFmzF239adTzGnU_L_yKyztSKHC6TapZKYHWCDrE-zaD1h2UhKVT5nWolAmsrN3BQRA1YoNvTxcEZ1nhrLBlFzLGumTRZ-LSyaaTyE8-5XtUscdLCHvrELkJHgjsHLwUTPS_FYbTIqRUl7jGeyJc7X1JUbC-9QoqGbyNGvajLxcLjpCbG9XncqZMpCFpT3Hetk-wrxjRdiyn82MFCjhuV0ZrH1rNqlSaq3f61B8toCzaIj-_OufRsO4lpbyiI7QtTbasmx37isuAwDV5BF6zP_b_2W0o6yvhhtk93crZTon8ShZmC4ezBjBm_DA6ztRIQ5NOtXe6Z0JWe101ExEtTKF8pXRHg-mmduUFlt-WihaQIHqtIdd2RgaOIU6UVRXeeJbt7uYH1wCiNyYBzyv9QOM-Q==",
          "id": "rs_07508900d512ef38016a035179f9788191a864df88d5ef2423",
          "summary": [
            {
              "type": "summary_text",
              "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!"
            }
          ]
        }
      ],
      "tool_calls": [
        {
          "id": "call_UglDOxl2rXlgbFE03ZQYpxBW",
          "call_id": "call_UglDOxl2rXlgbFE03ZQYpxBW",
          "response_item_id": "fc_07508900d512ef38016a035188b07c81918bb053860b27b786",
          "type": "function",
          "function": {
            "name": "memory",
            "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.\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"success\": false, \"error\": \"Memory at 1,325/1,375 chars. Adding this entry (144 chars) would exceed the limit. Replace or remove existing entries first.\", \"current_entries\": [\"_Learn about the person you're helping. Update this as you go._\", \"**Name:** Ignacio (Igna, also goes by Chicho)\", \"**What to call them:** Igna or Chicho\", \"**Pronouns:** _(not specified)_\", \"**Timezone:** UTC-3 (Buenos Aires, Argentina)\", \"**Notes:**\", \"No usa dispositivos Apple\", \"Prefiere YouTube Music (no Spotify)\", \"Prefiere Asana sobre Trello\", \"Prefiere respuestas en texto por defecto (para ahorrar tokens de ElevenLabs)\", \"Audio solo cuando él lo pida explícitamente\", \"Prefiere respuestas muy breves/directas; límites claros en Discord/plataformas.\", \"Cuando usa audio: prefiere acento argentino y TTS de calidad (ElevenLabs/OpenAI).\", \"Tiene Tailscale en su computadora personal — se puede usar para acceso cross-device\", \"Gmail: ignaciolagosruiz@gmail.com (gog configurado, read-only)\", \"No quiere que Pipo interactúe con otras personas vía WhatsApp/mensajería (por ahora)\", \"Vive en Argentina — scraping de sitios locales puede necesitar exit node argentino (Pixel 6a via Tailscale)\", \"Context: ---\", \"APIs 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.\", \"Dog name is Chivi (with v), not Chibi. Likes Palermo parks and local Colegiales parks near Parque Ferroviario.\"], \"usage\": \"1,325/1,375\"}",
      "tool_call_id": "call_UglDOxl2rXlgbFE03ZQYpxBW"
    },
    {
      "role": "assistant",
      "content": "",
      "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.",
      "finish_reason": "tool_calls",
      "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.",
      "codex_reasoning_items": [
        {
          "type": "reasoning",
          "encrypted_content": "gAAAAABqA1GVPKUqZmNtLBJZ27yOxapFo_utRW_WfGEF4UiVOnOK_PZAyVX2oFd5PtW8l7cks3KzMrQHkAfvpgSH_7eB87JIH_vWFHHfBdI28m6hJzH11qsaArp0kURvRRcedC28YWRfBbRorHPJVAlxCh9fEhHPRyFxmgtl56VZk0zg0Tem0Y8sjZBdqOoyK-LE8FJeE4ACqNiP3F3C3bMFx8KjDCOWtqKC9f_G6lpJUziRS1LYAi6uXCj_RoprGCBnjwU8hzkOyXLGrW1Cgmn4gDSPZwtPSwbADUE7RwjDqkE1vj4CL2CArahjmFQd8TRAXXo7XgWMyyo-mH0091UmKYkpbG9AMJIdcOhmUxUflBPnDfLrO96id0jH8KWnQbni0m8_jrnCvgH6WEPeb8qI6aJNvPLfB1iunMNoVF4wEhL2gK9GiYGKwEEJ8qMhAcOlNZXd4kpCY01idg7XnkTFNOvwoBAHsKPTDxCh2m5ra7U90Irqsg2_wQLmoo3UjeKy7LjRt_FUChu32C3-6UF7LI34fV8YZpQg1rUPrvoSXSQznFM4jUwCnXfG7faRTthtnqQMOVBBrI85pxqRtzGtci_J9GbjIx-DM-D6mYn-HGFK6r7RwAf7BOUzfB5AY3atR5RaExbSVaeZ_JrxMxwDnJ-pATPCdrbLg7RKMjeQm-Di0MynX3Eh6gXi5crDqC8ESYGzIJAXrNJWs-Miq70Dy3oQ5DGkxeBnQOWKEg1BO1G1s89OhDdr0BOGK9QZX0-YaAAKUpiE_MsxnN3V0HbW2YRvHcm2AfyeL29jYo1fMUsuZ-M6xa-Pyrad8dU9DJXCeFiU6nNJ6apHkv5Olk_8RJRW0aVAQ1_T1BxlX-0Lq36lJnOYKju_0TXC7TQ2XTSS0_glPcE0WrKyJGzdWPbnMuyYzAxT1dsbR_rR-uQVcc9GWizAB3A3B5SjIB0-MoG5515XoZD8_zf2LSJbf6dnMJFtDC9kwt31upzskfs4V4dJzISKV8ACOf3bmhmIc6Lxmcts9JElXKmrvm-pt2hNJhxWUxiYp0t8IxSbfrdBsB3SBHAlnmZLmKa5fzVjj8FvYIV0qtWJDCkwAvYniW4on97ylqC0PBJnmw1pMlrO-xj0TfJZW7eB35jyYsZcDjE0fcKtGUZ25BC2hqQidrw-gdxyyziFUjRhfXLV0fjJlrpvheBrHhXUZx5WrU8qlAy1nlpm41mPB0CM_IwZWZnmz2-oaDULLP3E41wq1xg0upW12R8ts7XmnZZnOGhcWOjMQ7Vbppz-_KAiBGOr-wx3V_Mruw7Q6ADPOoqMpOHZvsjnKU9Yj6gZUzcg4jWZe4mQXHeWnUwHXrosCBJa4I8YLFM-K2GqdI_YRh6MurIOvmCefHnH15JbinOGGgjC6zXeXoVIUgCrNfkItNqgdkutrJxW-jJqbXL7u8YNN2JdWW62wQubCTiSlXQ4e-0SKh6ZuejfV68AWuNfSw5f09mhebIt32lkhg==",
          "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."
            }
          ]
        }
      ],
      "tool_calls": [
        {
          "id": "call_GGfeklcIXniBZiA3zFXgeGHn",
          "call_id": "call_GGfeklcIXniBZiA3zFXgeGHn",
          "response_item_id": "fc_0180c40ce14e5fe0016a035195ccec81918f6b77bca2caecc2",
          "type": "function",
          "function": {
            "name": "memory",
            "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\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "content": "{\"success\": true, \"target\": \"user\", \"entries\": [\"_Learn about the person you're helping. Update this as you go._\", \"**Name:** Ignacio (Igna, also goes by Chicho)\", \"**What to call them:** Igna or Chicho\", \"**Pronouns:** _(not specified)_\", \"**Timezone:** UTC-3 (Buenos Aires, Argentina)\", \"**Notes:**\", \"No usa dispositivos Apple\", \"Prefiere YouTube Music (no Spotify)\", \"Prefiere Asana sobre Trello\", \"Prefiere respuestas en texto por defecto (para ahorrar tokens de ElevenLabs)\", \"Audio solo cuando él lo pida explícitamente\", \"Prefiere respuestas muy breves/directas; en integraciones/API espera leer docs/OpenAPI y usar ejemplos conocidos antes de probar.\", \"Cuando usa audio: prefiere acento argentino y TTS de calidad (ElevenLabs/OpenAI).\", \"Tiene Tailscale en su computadora personal — se puede usar para acceso cross-device\", \"Gmail: ignaciolagosruiz@gmail.com (gog configurado, read-only)\", \"No quiere que Pipo interactúe con otras personas vía WhatsApp/mensajería (por ahora)\", \"Vive en Argentina — scraping de sitios locales puede necesitar exit node argentino (Pixel 6a via Tailscale)\", \"Context: ---\", \"APIs 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.\", \"Dog name is Chivi (with v), not Chibi. Likes Palermo parks and local Colegiales parks near Parque Ferroviario.\"], \"usage\": \"100% — 1,375/1,375 chars\", \"entry_count\": 20, \"message\": \"Entry replaced.\"}",
      "tool_call_id": "call_GGfeklcIXniBZiA3zFXgeGHn"
    },
    {
      "role": "assistant",
      "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 <TOKEN>\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 <token>\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 <token>\", 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.",
      "finish_reason": "stop",
      "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 <token>\", 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.",
      "codex_reasoning_items": [
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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 <token>\", 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."
            }
          ]
        }
      ],
      "codex_message_items": [
        {
          "type": "message",
          "role": "assistant",
          "status": "completed",
          "content": [
            {
              "type": "output_text",
              "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 <TOKEN>\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 <token>\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."
            }
          ],
          "id": "msg_08b048433b5d220e016a0351ada69c819181d956c963fbcad9",
          "phase": "final_answer"
        }
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      "content": "Review the conversation above and update the skill library. Be ACTIVE — most sessions produce at least one skill update, even if small. A pass that does nothing is a missed learning opportunity, not a neutral outcome.\n\nTarget shape of the library: CLASS-LEVEL skills, each with a rich SKILL.md and a `references/` directory for session-specific detail. Not a long flat list of narrow one-session-one-skill entries. This shapes HOW you update, not WHETHER you update.\n\nSignals to look for (any one of these warrants action):\n  • User corrected your style, tone, format, legibility, or verbosity. Frustration signals like 'stop doing X', 'this is too verbose', 'don't format like this', 'why are you explaining', 'just give me the answer', 'you always do Y and I hate it', or an explicit 'remember this' are FIRST-CLASS skill signals, not just memory signals. Update the relevant skill(s) to embed the preference so the next session starts already knowing.\n  • User corrected your workflow, approach, or sequence of steps. Encode the correction as a pitfall or explicit step in the skill that governs that class of task.\n  • Non-trivial technique, fix, workaround, debugging path, or tool-usage pattern emerged that a future session would benefit from. Capture it.\n  • A skill that got loaded or consulted this session turned out to be wrong, missing a step, or outdated. Patch it NOW.\n\nPreference order — prefer the earliest action that fits, but do pick one when a signal above fired:\n  1. UPDATE A CURRENTLY-LOADED SKILL. Look back through the conversation for skills the user loaded via /skill-name or you read via skill_view. If any of them covers the territory of the new learning, PATCH that one first. It is the skill that was in play, so it's the right one to extend.\n  2. UPDATE AN EXISTING UMBRELLA (via skills_list + skill_view). If no loaded skill fits but an existing class-level skill does, patch it. Add a subsection, a pitfall, or broaden a trigger.\n  3. ADD A SUPPORT FILE under an existing umbrella. Skills can be packaged with three kinds of support files — use the right directory per kind:\n     • `references/<topic>.md` — session-specific detail (error transcripts, reproduction recipes, provider quirks) AND condensed knowledge banks: quoted research, API docs, external authoritative excerpts, or domain notes you found while working on the problem. Write it concise and for the value of the task, not as a full mirror of upstream docs.\n     • `templates/<name>.<ext>` — starter files meant to be copied and modified (boilerplate configs, scaffolding, a known-good example the agent can `reproduce with modifications`).\n     • `scripts/<name>.<ext>` — statically re-runnable actions the skill can invoke directly (verification scripts, fixture generators, deterministic probes, anything the agent should run rather than hand-type each time).\n     Add support files via skill_manage action=write_file with file_path starting 'references/', 'templates/', or 'scripts/'. The umbrella's SKILL.md should gain a one-line pointer to any new support file so future agents know it exists.\n  4. CREATE A NEW CLASS-LEVEL UMBRELLA SKILL when no existing skill covers the class. The name MUST be at the class level. The name MUST NOT be a specific PR number, error string, feature codename, library-alone name, or 'fix-X / debug-Y / audit-Z-today' session artifact. If the proposed name only makes sense for today's task, it's wrong — fall back to (1), (2), or (3).\n\nUser-preference embedding (important): when the user expressed a style/format/workflow preference, the update belongs in the SKILL.md body, not just in memory. Memory captures 'who the user is and what the current situation and state of your operations are'; skills capture 'how to do this class of task for this user'. When they complain about how you handled a task, the skill that governs that task needs to carry the lesson.\n\nIf you notice two existing skills that overlap, note it in your reply — the background curator handles consolidation at scale.\n\n'Nothing to save.' is a real option but should NOT be the default. If the session ran smoothly with no corrections and produced no new technique, just say 'Nothing to save.' and stop. Otherwise, act."
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      "reasoning": "**Updating skills for open data**\n\nI need to update my skills, specifically around open data monitoring. First, I should inspect the existing skills list, which suggests that open-data-monitoring was likely created previously. I'll consider using tools like skill_view for open-data-monitoring or maybe xurl. The session also involves checking the Presupuesto Abierto API docs and correcting the workflow based on the user’s input. I've loaded the hermes-agent, but it might not be suitable. So, I need to update the open-data-monitoring skills.",
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      "reasoning_content": "**Updating skills for open data**\n\nI need to update my skills, specifically around open data monitoring. First, I should inspect the existing skills list, which suggests that open-data-monitoring was likely created previously. I'll consider using tools like skill_view for open-data-monitoring or maybe xurl. The session also involves checking the Presupuesto Abierto API docs and correcting the workflow based on the user’s input. I've loaded the hermes-agent, but it might not be suitable. So, I need to update the open-data-monitoring skills.",
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              "text": "**Updating skills for open data**\n\nI need to update my skills, specifically around open data monitoring. First, I should inspect the existing skills list, which suggests that open-data-monitoring was likely created previously. I'll consider using tools like skill_view for open-data-monitoring or maybe xurl. The session also involves checking the Presupuesto Abierto API docs and correcting the workflow based on the user’s input. I've loaded the hermes-agent, but it might not be suitable. So, I need to update the open-data-monitoring skills."
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      "content": "{\"success\": true, \"name\": \"open-data-monitoring\", \"description\": \"Monitor public/open-data portals and turn changing datasets into alerts, summaries, or social posts. Use for feasibility checks, watchdog bots, civic transparency monitors, scheduled scrapers, and dataset-diff workflows.\", \"tags\": [\"open-data\", \"monitoring\", \"civic-tech\", \"datasets\", \"alerts\", \"bots\"], \"related_skills\": [], \"content\": \"---\\nname: open-data-monitoring\\ndescription: Monitor public/open-data portals and turn changing datasets into alerts, summaries, or social posts. Use for feasibility checks, watchdog bots, civic transparency monitors, scheduled scrapers, and dataset-diff workflows.\\nversion: 1.0.0\\nauthor: Hermes Agent\\nlicense: MIT\\nmetadata:\\n  hermes:\\n    tags: [open-data, monitoring, civic-tech, datasets, alerts, bots]\\n---\\n\\n# Open Data Monitoring\\n\\nUse this skill when the user asks whether an alert bot, transparency tracker, dataset watcher, or public-data automation is feasible.\\n\\nCore pattern:\\n1. **Identify the authoritative source.** Prefer official APIs, CKAN/package metadata, static CSV/ZIP repositories, RSS feeds, and documented downloads over screenshots or UI scraping.\\n2. **Verify with a live probe.** Fetch the API/schema or a small sample of the dataset. Do not just trust a search result.\\n3. **Inspect schema and freshness.** Record fields, date columns, update cadence, license, auth requirements, pagination, and whether values are raw events or aggregates.\\n4. **Define event semantics.** Decide what counts as a new event: new row, changed metric, difference since previous snapshot, state transition, or threshold-crossing.\\n5. **Store state.** Use SQLite/Postgres/Supabase with a deterministic key/hash over stable identifying columns. Keep raw snapshots when auditability matters.\\n6. **Generate concise output.** For alerts/social posts include source, timestamp, amount/status, entity, category, and caveats. Avoid overclaiming real-time or beneficiary-level precision if the dataset is aggregated.\\n7. **Schedule and backoff.** Cron polling is usually enough; add retry/backoff and a last-success marker. Use webhooks only if the source provides them.\\n\\n## Feasibility response checklist\\n\\nAnswer in practical terms:\\n- **Verdict:** feasible / partially feasible / not feasible.\\n- **Source:** exact official endpoint or dataset URL.\\n- **Fields available:** the fields that satisfy the requested output.\\n- **Limitations:** aggregation, latency, auth, rate limits, missing beneficiary identifiers, licensing.\\n- **MVP design:** polling interval, filters, state store, dedupe key, publishing channel.\\n- **Example output:** one realistic alert/post from sampled data.\\n\\n## Implementation sketch\\n\\n```python\\nimport csv, hashlib, io, json, sqlite3, zipfile\\nfrom datetime import datetime\\nimport requests\\n\\nurl = \\\"https://example.gov/dataset.zip\\\"\\nr = requests.get(url, timeout=60)\\nr.raise_for_status()\\nz = zipfile.ZipFile(io.BytesIO(r.content))\\nname = z.namelist()[0]\\n\\nconn = sqlite3.connect(\\\"open_data_monitor.db\\\")\\nconn.execute(\\\"\\\"\\\"\\nCREATE TABLE IF NOT EXISTS seen (\\n  key TEXT PRIMARY KEY,\\n  first_seen_at TEXT NOT NULL,\\n  payload TEXT NOT NULL\\n)\\n\\\"\\\"\\\")\\n\\nwith z.open(name) as f:\\n    reader = csv.DictReader(io.TextIOWrapper(f, encoding=\\\"utf-8-sig\\\"))\\n    for row in reader:\\n        # Customize these fields per dataset.\\n        if row.get(\\\"amount\\\", \\\"0\\\") in (\\\"\\\", \\\"0\\\"):\\n            continue\\n        stable = \\\"|\\\".join(str(row.get(c, \\\"\\\")) for c in [\\\"date\\\", \\\"entity\\\", \\\"category\\\", \\\"amount\\\"])\\n        key = hashlib.sha256(stable.encode()).hexdigest()\\n        try:\\n            conn.execute(\\n                \\\"INSERT INTO seen(key, first_seen_at, payload) VALUES (?, ?, ?)\\\",\\n                (key, datetime.utcnow().isoformat(), json.dumps(row, ensure_ascii=False)),\\n            )\\n            # emit alert here\\n        except sqlite3.IntegrityError:\\n            pass\\nconn.commit()\\n```\\n\\n## Pitfalls\\n\\n- **Aggregate vs transaction:** many budget datasets are aggregated execution records, not individual bank transfers. Phrase alerts accordingly.\\n- **Units and decimals:** verify currency scale and decimal separator before publishing amounts.\\n- **Late revisions:** old rows may change after initial publication; if revisions matter, diff the full row payload, not just new IDs.\\n- **Auth/documented API mismatch:** a web UI may advertise an API that requires auth while static data downloads are public.\\n- **Spam control:** for social media, filter by materiality (thresholds/categories) or publish daily summaries instead of every row.\\n\\n## References\\n\\n- `references/argentina-presupuesto-abierto.md` — Presupuesto Abierto datasets, API quirks, and transfer-monitoring fields.\\n\", \"path\": \"research/open-data-monitoring/SKILL.md\", \"skill_dir\": \"/home/ubuntu/.hermes/skills/research/open-data-monitoring\", \"linked_files\": {\"references\": [\"references/argentina-presupuesto-abierto.md\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\", \"metadata\": {\"hermes\": {\"tags\": [\"open-data\", \"monitoring\", \"civic-tech\", \"datasets\", \"alerts\", \"bots\"]}}}",
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      "content": "{\"success\": true, \"name\": \"open-data-monitoring\", \"file\": \"references/argentina-presupuesto-abierto.md\", \"content\": \"# Argentina Presupuesto Abierto — monitoring notes\\n\\nUse for questions like: “can we build a bot that posts national government transfers to provinces/universities/etc.?”\\n\\n## Official sources\\n\\n- API docs/UI: `https://www.presupuestoabierto.gob.ar/api/`\\n- Public data portal package search: `https://datos.gob.ar/api/3/action/package_search?q=presupuesto%20abierto%20credito%20gasto`\\n- Current-year static downloads are often available even before the CKAN package is listed, e.g.:\\n  - `https://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/credito-diario-2026.zip`\\n  - `https://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/credito-mensual-2026.zip`\\n  - `https://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/credito-anual-2026.zip`\\n  - `https://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/resumen-presupuesto-gastos-ejercicio-vigente-2026.zip`\\n  - Pattern: `https://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/{YEAR}/credito-diario-{YEAR}.zip`\\n- Complementary source for **automatic transfers / coparticipación / Recursos de Origen Nacional**: `https://www.argentina.gob.ar/economia/sechacienda/asuntosprovinciales/ron`\\n  - 2026 daily XLS examples observed: `/sites/default/files/internet_diario26_4_2.xls`, `/sites/default/files/internet_diario_abril26_19_1.xls`.\\n  - Consolidated/historical examples: `/sites/default/files/informacion_consolidada_2026_1.xlsx`, `/sites/default/files/serie_ron_2003_2025.csv` (`ano;provincia;impuesto;regimen;monto`).\\n\\n## API quirks\\n\\n- `GET https://www.presupuestoabierto.gob.ar/api/v1/credito` returns 405; the endpoint expects POST.\\n- POSTing a query may return `401 {\\\"message\\\":\\\"Debe indicar el header Authorization en la petición\\\"}`.\\n- The schema endpoints are public and useful:\\n  - `https://www.presupuestoabierto.gob.ar/api/jsonCredito`\\n  - `https://www.presupuestoabierto.gob.ar/api/jsonRecurso`\\n  - `https://www.presupuestoabierto.gob.ar/api/jsonPef`\\n  - `https://www.presupuestoabierto.gob.ar/api/jsonTransversalFinanciero`\\n- Column descriptions are available as UTF-16-ish text files under `/api/json/itemCredito.txt`, etc.\\n\\n## Transfer monitoring fields\\n\\nThe `credito-diario-{YEAR}.csv` inside the ZIP has useful fields:\\n\\n- `impacto_presupuestario_fecha`\\n- `impacto_presupuestario_anio`, `impacto_presupuestario_mes`\\n- `ejercicio_presupuestario`\\n- `jurisdiccion_desc`, `entidad_desc`, `servicio_desc`\\n- `programa_desc`, `subprograma_desc`, `proyecto_desc`, `actividad_desc`, `obra_desc`\\n- `inciso_id`, `inciso_desc`\\n- `principal_desc`, `parcial_desc`, `subparcial_desc`\\n- `ubicacion_geografica_desc`\\n- `fuente_financiamiento_desc`\\n- `credito_presupuestado`, `credito_vigente`, `credito_comprometido`, `credito_devengado`, `credito_pagado`\\n- `ultima_actualizacion_fecha`\\n\\nFor transfer-like rows, filter:\\n\\n- `inciso_id == \\\"5\\\"` → Transferencias\\n- then usually `credito_pagado > 0` for paid execution, or `credito_devengado > 0` for accrued/recognized spending.\\n\\nUse `credito-diario-{YEAR}` for event detection, but use `credito-anual-{YEAR}` or `credito-mensual-{YEAR}` for annual context/denominators when possible. Daily rows can show paid amounts while `credito_vigente` is zero at that exact grain.\\n\\nRecommended metrics for a public bot:\\n\\n- Event amount: sum `credito_pagado` for the grouped day/event.\\n- Year-to-date amount: sum annual `credito_pagado` at the same human grouping.\\n- Budget denominator: `credito_vigente` (not original `credito_presupuestado`) because it reflects budget modifications.\\n- Execution percentage: `credito_pagado_acumulado / credito_vigente * 100`.\\n- If `credito_vigente == 0`, publish `N/A` / “sin crédito vigente informado” and flag for review; do not divide or imply over-execution.\\n\\nCurrency handling: official dictionary says credit amounts are **in millions of pesos**. Convert before posting (`62568.241846` ⇒ `$62.568 millones` / `$62,6 mil millones`). Validate scale against docs before production.\\n\\n## Examples and feasibility facts from May 2026 probe\\n\\nWhen evaluating an Argentina budget-transfer bot, these concrete facts are useful grounding:\\n\\n- `credito-diario-2026.zip` downloaded successfully from `dgsiaf-repo.mecon.gob.ar` as a public ZIP.\\n- In a 2026 probe through `2026-05-10`, the daily CSV had ~363k rows; `inciso_id=5` yielded ~28k transfer rows and ~10k rows with `credito_pagado > 0`.\\n- Top-level 2026 categories observed for paid transfers included: sector privado gastos corrientes, other SPN entities, universities, provinces/municipalities current spending, provinces/municipalities capital spending, and exterior.\\n- Real UBA example, `2026-05-05`: three paid rows under Ministerio de Capital Humano / Secretaría de Educación / Desarrollo de la Educación Superior totaling `62568.241846` million pesos (≈ `$62.6 mil millones`), annual paid `262403.287296` million, vigente `799460.3925720002` million, execution `32.82%`.\\n- Real denominator caveat: Chubut/ATN showed a paid event around `$4.0 mil millones`, annual paid around `$6.5 mil millones`, but `credito_vigente = 0`; publish percent as N/A and explain.\\n\\n## Examples of transfer categories seen in 2026 data\\n\\n- `Transferencias a instituciones provinciales y municipales para financiar gastos corrientes`\\n- `Transferencias a la Administración Pública Provincial para financiar gastos corrientes`\\n- `Transferencias a fondos fiduciarios y otros entes del Sector Público Nacional no Financiero para financiar gastos corrientes`\\n- `Transferencias al sector privado para financiar gastos corrientes`\\n\\n## Caveats to say out loud\\n\\n- This is budget execution data, not necessarily each bank transfer as a discrete payment order.\\n- Use conservative wording: “Presupuesto Abierto registró un pago presupuestario” / “ejecución presupuestaria registrada”, not “wire transfer in real time”.\\n- It is commonly aggregated by day + budget classifiers + geography, so avoid claims like “the government sent a wire to beneficiary X” unless another source provides beneficiary-level data.\\n- `ubicacion_geografica_desc` is geography; `subparcial_desc` may be a clearer institutional destination for universities, but for provinces it can be a broad classifier like “Administración Central Provincial”.\\n- Automatic transfers/coparticipación are a separate data product from discretionary/budgetary transfers; use the DNAP/RON source, not only Presupuesto Abierto, for “todo lo que Nación manda a provincias”.\\n- Verify currency/decimal handling before posting amounts. Values use comma decimal separators in the CSV (e.g. `18,68193597`) and are in millions of pesos.\\n- Freshness depends on the dataset update cadence. In the May 12, 2026 probe, the file reported: `Última actualización del ejercicio 2026: 10 Mayo 2026.`\\n- Avoid posting every raw row. Group by date + human destination + program/category and publish only material events or summaries.\\n\\n## Minimal probe\\n\\n```bash\\npython3 - <<'PY'\\nimport csv, io, requests, zipfile\\nurl='https://dgsiaf-repo.mecon.gob.ar/repository/pa/datasets/2026/credito-diario-2026.zip'\\nz=zipfile.ZipFile(io.BytesIO(requests.get(url, timeout=60).content))\\nwith z.open(z.namelist()[0]) as f:\\n    reader=csv.DictReader(io.TextIOWrapper(f, encoding='utf-8-sig'))\\n    rows=[]\\n    for r in reader:\\n        if r.get('inciso_id') == '5':\\n            paid=float((r.get('credito_pagado') or '0').replace(',','.'))\\n            if paid > 0:\\n                rows.append((r, paid))\\n    rows.sort(key=lambda x: x[0]['impacto_presupuestario_fecha'], reverse=True)\\n    print('paid transfer rows', len(rows))\\n    if rows:\\n        print(rows[0][0].get('ultima_actualizacion_fecha'))\\n    for r, paid in rows[:5]:\\n        print(r['impacto_presupuestario_fecha'], paid, r['jurisdiccion_desc'], r['entidad_desc'], r['programa_desc'], r['principal_desc'], r['ubicacion_geografica_desc'])\\nPY\\n```\\n\\n## Suggested social-post phrasing\\n\\nPrefer:\\n\\n> 2026-05-08 — Ejecución presupuestaria registrada  \\n> Jurisdicción: Ministerio de Economía  \\n> Destino geográfico: Provincia de Jujuy  \\n> Partida: Transferencias a instituciones provinciales y municipales para gastos corrientes  \\n> Pagado: $X  \\n> Fuente: Presupuesto Abierto\\n\\nFor richer posts, include accumulated context:\\n\\n> 🏛️ Transferencia registrada — 05/05/2026  \\n> Ministerio de Capital Humano → Universidad de Buenos Aires  \\n> Programa: Desarrollo de la Educación Superior  \\n> Pagado del día: **$62,6 mil millones**  \\n> 2026 acumulado: **$262,4 mil millones / $799,5 mil millones**  \\n> Ejecución: **32,8%**  \\n> Fuente: Presupuesto Abierto, corte 10/05/2026.\\n\\nAvoid unless independently verified:\\n\\n> El gobierno transfirió exactamente $X a [beneficiario final] en tiempo real.\\n\", \"file_type\": \".md\"}",
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            "arguments": "{\"action\":\"patch\",\"name\":\"open-data-monitoring\",\"new_string\":\"## Pitfalls\\n\\n- **Skipping available docs:** if OpenAPI/API docs exist, read them before coding or probing. The user expects a documented, known-good request path, not ad-hoc “vemos si sale” endpoint guessing.\\n- **Aggregate vs transaction:** many budget datasets are aggregated execution records, not individual bank transfers. Phrase alerts accordingly.\",\"old_string\":\"## Pitfalls\\n\\n- **Aggregate vs transaction:** many budget datasets are aggregated execution records, not individual bank transfers. Phrase alerts accordingly.\",\"replace_all\":false}"
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          "call_id": "call_mCryutrfXBPIOlPbRIdyqYUP",
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            "arguments": "{\"action\":\"patch\",\"name\":\"open-data-monitoring\",\"new_string\":\"## API docs / OpenAPI\\n\\n- Documentation site: `https://presupuesto-abierto.argentina.apidocs.ar/`\\n- Production server from OpenAPI: `https://www.presupuestoabierto.gob.ar/api/v1`\\n- Documented endpoints:\\n  - `POST /credito`\\n  - `POST /recurso`\\n  - `POST /pef`\\n  - `POST /transversal_financiero`\\n- Required query parameter: `format=json|csv|zip` (default shown as `csv`, but pass explicitly).\\n- Auth scheme in docs: HTTP bearer. Use:\\n  - `Authorization: Bearer $PRESUPUESTO_ABIERTO_TOKEN`\\n  - In May 2026, raw `Authorization: <token>` also passed auth, but prefer the documented Bearer form.\\n- `GET /api/v1/credito` returns 405; use POST.\\n- Docs page embeds a known-good JS example for crédito:\\n  - `POST https://www.presupuestoabierto.gob.ar/api/v1/credito?format=json`\\n  - headers `Content-Type: application/json`, `Authorization: <token>`\\n  - body `{\\\"title\\\":\\\"Crédito vigente por finalidad función\\\",\\\"columns\\\":[\\\"finalidad_id\\\",\\\"finalidad_desc\\\",\\\"funcion_id\\\",\\\"funcion_desc\\\",\\\"credito_vigente\\\"]}`\\n- Schema endpoints are public and useful:\\n  - `https://www.presupuestoabierto.gob.ar/api/jsonCredito`\\n  - `https://www.presupuestoabierto.gob.ar/api/jsonRecurso`\\n  - `https://www.presupuestoabierto.gob.ar/api/jsonPef`\\n  - `https://www.presupuestoabierto.gob.ar/api/jsonTransversalFinanciero`\\n- `jsonCredito` confirms request shape:\\n  - required: `columns`\\n  - optional: `title`, `ejercicios`, `filters`, `order`\\n  - condition operators: `equal`, `like`, `greater_than`, `greater_equal_than`, `lower_than`, `lower_equal_than`, `between`\\n  - `ejercicios`: array of integer years or `\\\"vigente\\\"`\\n\\nDocs-compliant crédito probe:\\n\\n```bash\\ncurl -sS 'https://www.presupuestoabierto.gob.ar/api/v1/credito?format=json' \\\\\\n  -H \\\"Authorization: Bearer $PRESUPUESTO_ABIERTO_TOKEN\\\" \\\\\\n  -H 'Content-Type: application/json' \\\\\\n  --data '{\\n    \\\"title\\\":\\\"Crédito vigente por finalidad función\\\",\\n    \\\"ejercicios\\\":[2026],\\n    \\\"columns\\\":[\\\"finalidad_id\\\",\\\"finalidad_desc\\\",\\\"funcion_id\\\",\\\"funcion_desc\\\",\\\"credito_vigente\\\"],\\n    \\\"order\\\":[{\\\"column\\\":\\\"credito_vigente\\\",\\\"order\\\":\\\"desc\\\"}]\\n  }'\\n```\\n\\nObserved May 2026: returned `200 application/json`, 29 rows; `format=csv` returned `200 text/csv;charset=UTF-8`.\\n\\n## API quirks\\n\\n- `GET https://www.presupuestoabierto.gob.ar/api/v1/credito` returns 405; the endpoint expects POST.\",\"old_string\":\"## API quirks\\n\\n- `GET https://www.presupuestoabierto.gob.ar/api/v1/credito` returns 405; the endpoint expects POST.\",\"replace_all\":false,\"file_path\":\"references/argentina-presupuesto-abierto.md\"}"
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            "arguments": "{\"action\":\"patch\",\"file_path\":\"references/argentina-presupuesto-abierto.md\",\"name\":\"open-data-monitoring\",\"new_string\":\"## API quirks\\n\\n- `GET https://www.presupuestoabierto.gob.ar/api/v1/credito` returns 405; the endpoint expects POST.\\n- When probing with an invalid payload but valid Authorization, `POST /credito?format=json` returns a 400 schema/payload error instead of 401; this is a quick auth sanity check but should not replace a docs-compliant probe.\\n- `X-API-Key` is not the documented auth mechanism and returned 401 in May 2026; use `Authorization: Bearer ...`.\",\"old_string\":\"## API quirks\\n\\n- `GET https://www.presupuestoabierto.gob.ar/api/v1/credito` returns 405; the endpoint expects POST.\",\"replace_all\":false}"
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            "arguments": "{\"action\":\"write_file\",\"file_content\":\"{\\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\",\"file_path\":\"templates/presupuesto-abierto-credito-transferencias.json\",\"name\":\"open-data-monitoring\"}"
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          "type": "function",
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            "name": "skill_manage",
            "arguments": "{\"action\":\"patch\",\"name\":\"open-data-monitoring\",\"new_string\":\"## References\\n\\n- `references/argentina-presupuesto-abierto.md` — Presupuesto Abierto datasets, API/OpenAPI quirks, and transfer-monitoring fields.\\n- `templates/presupuesto-abierto-credito-transferencias.json` — known-good `/credito?format=json` request body for paid transfer rows (`inciso_id=5`, `credito_pagado>0`).\\n\",\"old_string\":\"## References\\n\\n- `references/argentina-presupuesto-abierto.md` — Presupuesto Abierto datasets, API quirks, and transfer-monitoring fields.\\n\",\"replace_all\":false}"
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    {
      "role": "assistant",
      "content": "Actualicé la skill library.\n\nCambios hechos en `open-data-monitoring`:\n\n1. **SKILL.md**\n   - Agregué una regla explícita: si hay docs/OpenAPI oficiales, primero leerlos y extraer base URL, método, auth, params, body, ejemplos y operadores.\n   - Agregué pitfall:\n     > no hacer “vemos si sale” / endpoint guessing cuando hay documentación disponible.\n   - Actualicé referencias para incluir API/OpenAPI quirks y template de request.\n\n2. **Referencia actualizada**\n   - Archivo:\n     ```text\n     references/argentina-presupuesto-abierto.md\n     ```\n   - Agregué:\n     - docs oficiales: `https://presupuesto-abierto.argentina.apidocs.ar/`\n     - server correcto: `https://www.presupuestoabierto.gob.ar/api/v1`\n     - endpoints documentados:\n       ```text\n       POST /credito\n       POST /recurso\n       POST /pef\n       POST /transversal_financiero\n       ```\n     - auth correcta:\n       ```text\n       Authorization: Bearer $PRESUPUESTO_ABIERTO_TOKEN\n       ```\n     - query param requerido:\n       ```text\n       ?format=json|csv|zip\n       ```\n     - schema público:\n       ```text\n       /api/jsonCredito\n       ```\n     - operadores soportados:\n       ```text\n       equal, like, greater_than, greater_equal_than,\n       lower_than, lower_equal_than, between\n       ```\n     - nota: `X-API-Key` no sirve; `GET /credito` da 405; usar POST.\n\n3. **Template agregado**\n   - Archivo:\n     ```text\n     templates/presupuesto-abierto-credito-transferencias.json\n     ```\n   - Contiene request body conocido-bueno para:\n     - `inciso_id = 5`\n     - `credito_pagado > 0`\n     - ordenado por fecha y monto\n     - columnas útiles para bot de transferencias.\n\nTambién guardé la preferencia operativa en memoria del usuario: para integraciones/API espera que parta de docs/OpenAPI y ejemplos conocidos antes de probar."
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}