{ "session_id": "20260503_175011_cc27fd", "model": "gpt-5.5", "base_url": "https://chatgpt.com/backend-api/codex", "platform": "telegram", "session_start": "2026-05-03T17:50:11.007503", "last_updated": "2026-05-03T17:52:04.950625", "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\n- Use tools whenever they improve correctness, completeness, or grounding.\n- Do not stop early when another tool call would materially improve the result.\n- If a tool returns empty or partial results, retry with a different query or strategy before giving up.\n- Keep calling tools until: (1) the task is complete, AND (2) you have verified the result.\n\n\n\nNEVER answer these from memory or mental computation — ALWAYS use a tool:\n- Arithmetic, math, calculations → use terminal or execute_code\n- Hashes, encodings, checksums → use terminal (e.g. sha256sum, base64)\n- Current time, date, timezone → use terminal (e.g. date)\n- System state: OS, CPU, memory, disk, ports, processes → use terminal\n- File contents, sizes, line counts → use read_file, search_files, or terminal\n- Git history, branches, diffs → use terminal\n- Current facts (weather, news, versions) → use web_search\nYour memory and user profile describe the USER, not the system you are running on. The execution environment may differ from what the user profile says about their personal setup.\n\n\n\nWhen a question has an obvious default interpretation, act on it immediately instead of asking for clarification. Examples:\n- 'Is port 443 open?' → check THIS machine (don't ask 'open where?')\n- 'What OS am I running?' → check the live system (don't use user profile)\n- 'What time is it?' → run `date` (don't guess)\nOnly ask for clarification when the ambiguity genuinely changes what tool you would call.\n\n\n\n- Before taking an action, check whether prerequisite discovery, lookup, or context-gathering steps are needed.\n- Do not skip prerequisite steps just because the final action seems obvious.\n- If a task depends on output from a prior step, resolve that dependency first.\n\n\n\nBefore finalizing your response:\n- Correctness: does the output satisfy every stated requirement?\n- Grounding: are factual claims backed by tool outputs or provided context?\n- Formatting: does the output match the requested format or schema?\n- Safety: if the next step has side effects (file writes, commands, API calls), confirm scope before executing.\n\n\n\n- If required context is missing, do NOT guess or hallucinate an answer.\n- Use the appropriate lookup tool when missing information is retrievable (search_files, web_search, read_file, etc.).\n- Ask a clarifying question only when the information cannot be retrieved by tools.\n- If you must proceed with incomplete information, label assumptions explicitly.\n\n\n══════════════════════════════════════════════\nMEMORY (your personal notes) [90% — 1,995/2,200 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§\n2026-03-01: Se validado estado \"Maxxxed Out\":\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) [99% — 1,363/1,375 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 directas; si pregunta por Discord/plataformas, quiere límites claros sin que le cambien el flujo.\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\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 - 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 - polymarket: Query Polymarket: markets, prices, orderbooks, history.\n smart-home: Skills for controlling smart home devices — lights, switches, sensors, and home automation systems.\n - openhue: Control Philips Hue lights, scenes, rooms via OpenHue CLI.\n social-media: Skills for interacting with social platforms and social-media workflows — posting, reading, monitoring, and account operations.\n - xitter: Interact with X/Twitter via the x-cli terminal client usi...\n - xurl: X/Twitter via xurl CLI: post, search, DM, media, v2 API.\n software-development:\n - code-review: Guidelines for performing thorough code reviews with secu...\n - debugging-hermes-tui-commands: Debug Hermes TUI slash commands: Python, gateway, Ink UI.\n - evaluate-openai-compatible-llm-endpoint: Verify whether a new OpenAI-compatible chat/completions e...\n - hermes-agent-skill-authoring: Author in-repo SKILL.md: frontmatter, validator, structure.\n - hermes-specialist-profile-custom-endpoint: Create a Hermes profile specialized for a model's strengt...\n - node-inspect-debugger: Debug Node.js via --inspect + Chrome DevTools Protocol CLI.\n - plan: Plan mode: write markdown plan to .hermes/plans/, no exec.\n - python-debugpy: Debug Python: pdb REPL + debugpy remote (DAP).\n - react-component-split: Split large React client components (>300 lines) into mul...\n - requesting-code-review: Pre-commit review: security scan, quality gates, auto-fix.\n - spike: Throwaway experiments to validate an idea before build.\n - subagent-driven-development: Execute plans via delegate_task subagents (2-stage review).\n - systematic-debugging: 4-phase root cause debugging: understand bugs before fixing.\n - test-driven-development: TDD: enforce RED-GREEN-REFACTOR, tests before code.\n - writing-plans: Write implementation plans: bite-sized tasks, paths, code.\n wa-bot-fix-troubleshooting:\n - wa-bot-fix-troubleshooting: Fix WhatsApp bot not responding when bridge is connected ...\n yuanbao:\n - yuanbao: Yuanbao (元宝) groups: @mention users, query info/members.\n\n\nOnly proceed without loading a skill if genuinely none are relevant to the task.\n\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: Sunday, May 03, 2026 05:50 PM\nModel: gpt-5.5\nProvider: openai-codex\n\nYou are on a text messaging communication platform, Telegram. Standard markdown is automatically converted to Telegram format. Supported: **bold**, *italic*, ~~strikethrough~~, ||spoiler||, `inline code`, ```code blocks```, [links](url), and ## headers. You can send media files natively: to deliver a file to the user, include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) appear as photos, audio (.ogg) sends as voice bubbles, and videos (.mp4) play inline. You can also include image URLs in markdown format ![alt](url) and they will be sent as native photos.", "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\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.", "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'." } }, "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": 63, "messages": [ { "role": "user", "content": "=== CREDENTIALS (in server env) ===\n- SUPABASE_ACCESS_TOKEN (for Management API)\n- VERCEL_TOKEN (for deploys)\n- Supabase anon key: sb_publishable_zi-E4qkqGxVRRt9Ym8-Rrw_Iq_g2WAP\n- Supabase URL: https://xvrlnhwbvyyydnnzctbk.supabase.co\n- Vercel project ID: prj_KC4GBo5ApiPqbNjRcjWBFUPT1oMf\n- Deploy command: cd /home/ubuntu/lobbytracker && vercel --prod --yes\n- SQL via Management API: POST https://api.supabase.com/v1/projects/xvrlnhwbvyyydnnzctbk/database/query -H \"Authorization: Bearer $SUPABASE_ACCESS_TOKEN\"\n\n=== SERVER ===\nUbuntu 24.04 ARM64, Oracle Cloud São Paulo. Node.js v22, Python 3.12. SSH via Tailscale at miopenclaw-vnic.tail9799d2.ts.net. Source code at /home/ubuntu/lobbytracker/src/. Full handoff at /home/ubuntu/lobbytracker/HANDOFF.md.\n\n=== TODO (in order) ===\n\n1. VERIFY: curl https://lobbytracker.vercel.app (expect 200). Query Supabase to confirm Larreta exists: curl \"https://xvrlnhwbvyyydnnzctbk.supabase.co/rest/v1/politicians\" -H \"apikey: sb_publishable_zi-E4qkqGxVRRt9Ym8-Rrw_Iq_g2WAP\"\n\n2. BUILD WEEKLY SOURCE UPDATE AGENT: Create a skill at ~/.hermes/skills/lobbytracker-updater/SKILL.md that:\n - Runs as a cron job every Sunday\n - Iterates all politicians from DB\n - Spawns delegate_task subagents (one per politician, parallel)\n - Each subagent: web_search for new legal/news developments → web_extract sources → compare against existing connections → insert new ones via Supabase Management API\n - Updates total_lobby_ars and total_lobby_usd on affected politicians\n - EVERY new connection must have an evidence row with source_url, source_name, excerpt\n - Pitfall: Supabase pooler host is aws-0-sa-east-1.pooler.supabase.com:6543 (direct IPv6 DB is unreachable from Oracle Cloud)\n - Pitfall: date columns need ::date casting in raw SQL\n\n3. ASK CHICHO about the YouTube short (https://youtube.com/shorts/xgJPfx4WI1s). If he downloaded it, convert to GIF: ffmpeg -i video.mp4 -vf \"fps=10,scale=480:-1\" output.gif and discuss embedding in Larreta's detail page.\n\n=== DO NOT TOUCH ===\n- Supabase region (already optimized)\n- RLS policies (public read-only is intentional)\n- Color scheme (dark red/black is the brand)\n- Card component design (user approved)\n- Status field (red/green badge system stays)\n- NEVER invent data — every connection needs a real public source\n\n=== USER (Chicho) ===\nArgentine, lives in Colegiales, Buenos Aires. Full-stack developer. PREFERS: direct, no-filler responses in Spanish. HATES excuses — find solutions, not roadblocks. Push to be autonomous. If blocked, try 3+ alternatives before reporting failure. Wife Tina is ~31 weeks pregnant. Telegram is his primary interface.\n\nUSER DIRECTIVE: Verify the site is working, then build the weekly agent system. Propose the next strategic action after that and wait for confirmation.\n\nno pude descargar el video. busca vos la forma de hacerlo. necesito que hagas un gif sobre la ultima imagen creada, que estaba buenisima, para generar un mejor impacto. con el efecto del video short de youtube. Te paso la última imagen generada adjunta" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_N0Pd8rM6A1XE6LRsYKwHUkQ3", "call_id": "call_N0Pd8rM6A1XE6LRsYKwHUkQ3", "response_item_id": "fc_075a3c6867ab70a20169f6b3515ab08199a151104eb16f3b6e", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"lobbytracker-updater\"}" } }, { "id": "call_oLW8EvT4mCgTMXwBypWazOUa", "call_id": "call_oLW8EvT4mCgTMXwBypWazOUa", "response_item_id": "fc_075a3c6867ab70a20169f6b3515ac081999c6e6c8ce874be92", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"youtube-content\"}" } }, { "id": "call_u4JwOYZqTe7GTJSob5xwpmY8", "call_id": "call_u4JwOYZqTe7GTJSob5xwpmY8", "response_item_id": "fc_075a3c6867ab70a20169f6b3515ac88199a847be344274d957", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"gif-search\"}" } } ], "reasoning": "**Loading relevant skills**\n\nI need to take action and load the relevant skills, like lobbytracker-updater and possibly YouTube content or media. There’s a mention of an image attachment, but it’s not visible—so I should inspect the current message attachments because they aren't in the text. I don't have a direct image path unless I can access available files. I guess I should first focus on loading the skills!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp9rNRqRaVn_L3iPtEaEWDUscZjsdsV0qxga2cmriONEeM2Vlks5ANwnx0q0sake2pqOr-XIsGGbReuQgqk-BTcm2cU76VU8YYWlQ7n9a8THXH0xKeRfVBo2Vu5wovEatdLYZx4UvBPNiVU5nU6I0FaEt6OO0gPubcTFE5C6aqqdR-B-RnFJA4BxiBRW1CS435vvMPfrHPIk3OZzDqE9oA9ROqrioGipyVAXvkaykWV_vvuRT3PB2X-q3ZgRCZH7Oykot0dgq8gAPgC4MWzFWmfDPSNUa3xWxweodKfit1sLiPl6KrxiLqr0ngYmExy7j3iF7k6hUUxdeoYd3E9eIiUPa6v6aNd5RJLVJVUWh02ezbCrzhdFBucvMYxqgLe8u19BTnxm32rcFjqMONgju8rro6TAhm-lSX_WfGhQ5LU2YIrZKxrIayqqcypiAVtOrlrWJqd7573gW_ktcMICXl75tBfqtpB5BOqfQLc4YOeZEjuN5bvWsPDXfF100wZLWMv77VHJ3CQPixjQ2CWFQBGrUtnRJ9beC-GV6wG1HCqO4n7YOCPfl0SZ7jZApFPd_npdy7ADko5kfY6_FXUP_cbLmmPv4gJgRNyEkVP0cbAq5aBWzW1idldhqM-ScV9fj3yK1-e6rO2IjwH3OFir6Dzhwqp6vG6bJVxyDhztukKOEVBU_iZoV797-q3ef8e3f-nHK2QYYk3F9HMCTDsaOGN7zMoUiVAM-kIq78OnJVyKefbqEYEHlDaHPqe4bB-QBb4YOXjyJHu26xTFmKKTu2S8PJn7t1ZW1ur2rJVdVvj_2d8_6DwtnAb_EivF7qWtmivwZBos4iTzQY7hsJMjBD8ot1HLkKRso2Pmj3PcJCvY9x2iRt8F226Q54OQJ7wP4OeiNKJ4_H0DYr7ULQJ2Ri9ny5QPLgwF73mbVW8i0bFMPxcuoCH2noYA5Wu5WGKKGv2bBQ8wkYrhYRs3fCLYN0kgQ3aDEK-emVsqU095ss4UOIEMBRP2x-H_G7l_Myxcgj6y5agCkCI0nxgVe56uR73WjO33dy2zgs5bi3nqiUmLuYuciXJruY6GUK86_RrTUVBYclf9mH9zfkpTT1PGsA-YHYCr5xx705s_5UlACndPqdytxE6-lwMKt_pNSBon7NeT0Y21HCmdKqWxVXWULjCiRbeHWHWffCyIcAyW5EHrvyx05X3bS1YSpfW8tupJuHTt-rtPFE3OlwdHF6CQvQyTrAoeH3R-dMS6DpjKjrjKGr8xAxmY3PLF-YzYSGylvXAgNc_0GYJRJkihIKtKORLnffQq7-MXPBqBwrQVwLsrJgNZ1MZPNYSIqXyVD1Xkrj-yH1WxdoaS4trzUZsdummll4mA==", "id": "rs_075a3c6867ab70a20169f6b34d6acc8199b3ea36481f9b1596", "summary": [ { "type": "summary_text", "text": "**Loading relevant skills**\n\nI need to take action and load the relevant skills, like lobbytracker-updater and possibly YouTube content or media. There’s a mention of an image attachment, but it’s not visible—so I should inspect the current message attachments because they aren't in the text. I don't have a direct image path unless I can access available files. I guess I should first focus on loading the skills!" } ] } ] }, { "role": "tool", "content": "[Duplicate tool output — same content as a more recent call]", "tool_call_id": "call_N0Pd8rM6A1XE6LRsYKwHUkQ3" }, { "role": "tool", "content": "[skill_view] name=youtube-content (4,024 chars)", "tool_call_id": "call_oLW8EvT4mCgTMXwBypWazOUa" }, { "role": "tool", "content": "[skill_view] name=gif-search (3,602 chars)", "tool_call_id": "call_u4JwOYZqTe7GTJSob5xwpmY8" }, { "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:\nSummary generation was unavailable. 236 conversation turns were removed to free context space but could not be summarized. The removed turns contained earlier work in this session. Continue based on the recent messages below and the current state of any files or resources." }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_gWIyZEq0q1U37xCVgPh1KQnB", "call_id": "call_gWIyZEq0q1U37xCVgPh1KQnB", "response_item_id": "fc_04675c6c888c13da0169f787e14cdc819bb17d029a03118aab", "type": "function", "function": { "name": "todo", "arguments": "{\"todos\":[{\"content\":\"Generar cards verificables con QR correcto para cada político usando solo datos/evidencia disponibles\",\"id\":\"cards\",\"status\":\"completed\"},{\"content\":\"Completar/ocultar trazabilidad faltante: UI clickable evidence y pendientes de auditoría\",\"id\":\"trace-ui\",\"status\":\"completed\"},{\"content\":\"Actualizar image_url/card assets en Supabase\",\"id\":\"db-card-update\",\"status\":\"completed\"},{\"content\":\"Build + deploy + verificar sitio, QR, assets, fuentes clickeables\",\"id\":\"deploy-verify\",\"status\":\"completed\"}]}" } } ] }, { "role": "tool", "content": "{\"todos\": [{\"id\": \"cards\", \"content\": \"Generar cards verificables con QR correcto para cada político usando solo datos/evidencia disponibles\", \"status\": \"completed\"}, {\"id\": \"trace-ui\", \"content\": \"Completar/ocultar trazabilidad faltante: UI clickable evidence y pendientes de auditoría\", \"status\": \"completed\"}, {\"id\": \"db-card-update\", \"content\": \"Actualizar image_url/card assets en Supabase\", \"status\": \"completed\"}, {\"id\": \"deploy-verify\", \"content\": \"Build + deploy + verificar sitio, QR, assets, fuentes clickeables\", \"status\": \"completed\"}], \"summary\": {\"total\": 4, \"pending\": 0, \"in_progress\": 0, \"completed\": 4, \"cancelled\": 0}}", "tool_call_id": "call_gWIyZEq0q1U37xCVgPh1KQnB" }, { "role": "assistant", "content": "Listo, Chicho. Hice todo en paralelo con subagentes + cambios directos.\n\n## Qué quedó hecho\n\n### 1. Cards tipo imagen compartible para cada político\n\nGeneré **6 imágenes verificables**, una por político, con QR funcional:\n\n- [Larreta](https://lobbytracker.vercel.app/cards/horacio-rodriguez-larreta.png)\n- [Javier Milei](https://lobbytracker.vercel.app/cards/javier-milei.png)\n- [Gerardo Werthein](https://lobbytracker.vercel.app/cards/gerardo-werthein.png)\n- [Patricia Bullrich](https://lobbytracker.vercel.app/cards/patricia-bullrich.png)\n- [Jorge Macri](https://lobbytracker.vercel.app/cards/jorge-macri.png)\n- [Waldo Wolff](https://lobbytracker.vercel.app/cards/waldo-wolff.png)\n\nVerifiqué los QR con `zbarimg`: todos decodifican bien y apuntan a la página detail correcta del político.\n\nEjemplo local:\n\nMEDIA:/home/ubuntu/lobbytracker/public/cards/horacio-rodriguez-larreta.png\n\n### 2. Imágenes visibles en el sitio\n\nActualicé el frontend:\n\n- La home ahora muestra la imagen/card en cada carta de político.\n- La página detalle también muestra la card arriba.\n- `politicians.image_url` quedó actualizado en Supabase para los 6.\n\n### 3. Fuentes clickeables y trazabilidad en UI\n\nAntes la DB tenía evidencia pero el frontend no la mostraba.\n\nAhora la página detalle trae:\n\n```ts\nconnections + lobby_groups + evidence\n```\n\nY renderiza por cada conexión:\n\n- Fuente clickeable\n- Nombre de fuente\n- Tipo: oficial / periodismo / institucional / denuncia\n- Excerpt\n- URL visible\n\nSi alguna conexión queda sin evidencia en el futuro, aparece como:\n\n> Pendiente de auditoría\n\n### 4. Auditoría Larreta / imagen vieja\n\nSubagente auditó las claims viejas de Larreta.\n\nResultado importante:\n\n- **FONCAP / peculado Corte Suprema**: parcialmente soportado solo como *causa/investigación que la Corte dejó seguir*, no como condena.\n- **Danaide espionaje 7M personas**: parcialmente soportado como *datos biométricos / sistema suspendido judicialmente*, no como “espionaje probado”.\n- **Asombro Extremo dólares negros**: soportado como denuncia periodística/audio alegado, no como hecho judicial probado.\n- **Viaje Israel monto ARS 3.6M / USD 15K**: no encontré fuente pública sólida para el monto.\n\nEntonces en la nueva card de Larreta **no usé FONCAP ni espionaje como claims de card**. Y en DB ajusté el viaje para no computar el monto sin fuente.\n\n### 5. DB ya no tiene conexiones sin evidencia\n\nVerificado:\n\n- `connections`: **28**\n- sin evidence: **0**\n- evidence con campos vacíos: **0**\n- políticos sin imagen: **0**\n\n### 6. Deploy\n\nBuild OK. Deploy OK.\n\n- Home: `200`\n- Detail Larreta: `200`\n- Todas las cards: `200 image/png`\n- QR verificados.\n\nLive:\n\nhttps://lobbytracker.vercel.app\n\n## Nota importante\n\nLas cards ahora priorizan **objetivismo y trazabilidad** sobre “pegar más fuerte”. Donde una claim es secundaria o necesita fuente oficial, la card lo marca como auditado/pendiente en vez de venderlo como hecho cerrado.\n\nTambién actualicé el skill `lobbytracker-updater` para que de ahora en más, cuando se agregue un político, el agente semanal también genere/actualice su card con QR y verifique el QR antes de deployar." }, { "role": "user", "content": "[The user sent an image~ Here's what I can see:\nHere's a detailed description of the image:\n\n**Overall Impression:**\n\nThe image appears to be a poster or graphic with a political or investigative theme. It features a prominent figure, financial amounts, and references to Israel, suggesting a focus on lobbying or financial connections. The overall tone is serious and potentially accusatory.\n\n**Layout:**\n\n* The image is vertically oriented.\n* The top portion features the title \"LOBBY TRACKER ARGENTINA\" and a small Argentinian flag.\n* A central figure (Horacio Rodriguez Larreta) is prominently displayed.\n* Large text displays the name \"LARRETA\" and significant financial amounts in both Argentinian pesos (ARS) and US dollars (USD).\n* A list of bullet points details specific allegations or connections.\n* The bottom of the image includes a date (\"MAY 2026\") and a website address (\"LOBBYTRACKER.AR\").\n* A QR code is present in the bottom right corner.\n\n**Visual Elements:**\n\n* **Background:** The background is dramatic, featuring a red, stormy sky with lightning bolts. On the left is the Obelisco de Buenos Aires, and on the right is the flag of Israel.\n* **Central Figure:** A man in a suit, presumably Horacio Rodriguez Larreta, is positioned in the center. He has a serious, almost stern expression.\n* **Money:** Stacks of US dollar bills are visible, suggesting financial transactions or wealth.\n* **Contract:** A document labeled \"CONTRATO\" (contract) is visible, implying legal or financial agreements.\n* **Flags:** The Argentinian flag is small and located near the top. The Israeli flag is larger and more prominent in the background.\n* **QR Code:** A black and white QR code is located in the bottom right corner, with the word \"ESCANEAR\" (scan) below it.\n\n**Text and Data:**\n\n* **Title:** \"LOBBY TRACKER ARGENTINA\"\n* **Name:** \"HORACIO RODRIGUEZ LARRETA\"\n* **Financial Amounts:**\n * \"ARS $2.400.000.000+\" (Argentinian pesos)\n * \"≈ USD $8.000.000+\" (US dollars)\n * \"ISRAEL LOBBY TOTAL\"\n* **Bullet Points:**\n * \"CONTRATOS A CAMARA COMERCIO ARG-ISRAELI (MONTOTO)\" (Contracts to the Argentine-Israeli Chamber of Commerce)\n * \"VIAJE OFICIAL ISRAEL 2022: ARS $3.6M ≈ USD $15K\" (Official trip to Israel 2022)\n * \"WALDO WOLFF EX-VP DAIA EN GABINETE\" (Waldo Wolff, former VP of DAIA, in the cabinet)\n * \"CAUSA ASOMBRO EXTREMO: DOLARES NEGROS CAMPAÑA 2019\" (Extremely astonishing case: Black dollars campaign 2019)\n * \"CAUSA FONCAP: PECULADO (CORTE SUPREMA)\" (FONCAP case: Embezzlement (Supreme Court))\n * \"ESPIONAJE DANAIDE: 7M PERSONAS VIGILADAS\" (Danaide espionage: 7M people monitored)\n* **Date:** \"MAY 2026\"\n* **Website:** \"LOBBYTRACKER.AR\"\n\n**Colors:**\n\n* The dominant colors are red, black, and white.\n* The red background and lightning create a sense of urgency or danger.\n* The black text and suit contribute to a serious tone.\n* The white text provides contrast and readability.\n\n**Overall Interpretation:**\n\nThe image appears to be a piece of political communication, possibly an advertisement or exposé, alleging connections between Horacio Rodriguez Larreta and Israeli lobbying efforts. The large financial amounts, the list of accusations, and the dramatic imagery suggest a critical and potentially accusatory stance. The QR code likely leads to more information or evidence related to these claims. The date \"MAY 2026\" could indicate a future event or election.]\n[If you need a closer look, use vision_analyze with image_url: /home/ubuntu/.hermes/image_cache/img_184c12b449fc.jpg ~]\n\nAmigo vos viste lo que son las imágenes de mierda qué creaste? Tienen que ser como la imagen adjunta, hiper realista, hechas con OpenAI imagen2 model" }, { "role": "assistant", "content": "", "reasoning": "**Considering image generation**\n\nI need to respond in Spanish for the user. The task involves generating better images using OpenAI's image generation capabilities. However, I notice that we only have the image generation backend configured, which isn’t selectable. I think I might need to inspect the files or project to find out more. I'm considering relevant skills, like perhaps the political-tracker-card. I should load it and see if it's stable to proceed with image generation.", "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94jvb6H_zOL7CD1pWDzvTO9QYk2OjYgAu-eg_meH5bdHxFKBGo-mltqw5t-fzfgGM6bhYZ40l-Cco4tfGt-NMJf9CHBbZzznImgjDT2RuahykeGbSisrVYLS7a1ElKlUGbKCSiBfkha9PDwmPf7kG86MsZqxXx1XwPOhELybrwY-5iE7TmDvMqBGWR3CeFyeai6cANwOVdmtlW9qKxj0bdUfOuZCojS3mLuPY1lU5G2va8GB62H6AqMINC4t_TK8Sdwp1dJhOq0-nZ0JYPsLpVKJRy7R8jU_HnrRCoF7Eoa-MYkeAAtfI72Png4ugreSjq0A66xGOQIbE9tqfje6TkyNlnTU1K9-nhhZyVox_nopxdb3C1gZ9jUSk4V2i0dK2JrtwvlqGnz24USHigi9ktGsSVVKEiFX52CWQ283uiunECYZvuOUGOxyHdGXJPXS-cFB3l4GCaZRXm4hIJEDXh0af3uJVfMccQ_x1y-ExiocIAhYozsqMQ-nCxGhPbq1aTyftgglpT-H_jvlasTNhegHNObWpx-Au5aZO747htRecisrgsanrmhjo0mlPmnxtJjoeTujWjdpAH7pmC5niB3lkdXO2xy_BJb8JVHmce6Xlju6R6bEtmewf835hFOcfKSkmJuYzzJzKaubdbNvUa_bqyIzazalNYa9Z6oEqUUAul5IZAsyidoaXy7Sg3QHIpEKkSxUIiBbL92evmSGK5Rtuq1nWgLJVCNKSKh0ZeclfpLKrv8Ynhwj0hYTL-rIbSRI676cB8sDxnnXuRbHR5IxDiLCHLZa8RwRXstiRWpnsDTRdCdTkPrpdkTyR_bK01XJqHo-m24Uqsqp6wrtzGphLr4VEhajeEV5zFbS2NocTNUV9iuGW1EFU5T5WEO9mrPKqwDcO-87pDVibrCsCPGohva_8MGsqH-KC0JebtQ3zgY1kngi863xaJrBC46opprGpwpJTlIqQ4lWjh3fdov5PO95okLPcdYhshE7hGMoDOv9DZZyx1BkAp0geS1_ws1H1FBpnY51SmX6kvYC4AtgLzZU0giMF3ra9gl4Dx545WJssxveqjOnOwVzhxxLTL-BIUCY5Q_7O2Sf0Zpj8iMZfHwAh5x4MP0XSqm5KR1DlJw8kH8q33UXVgc_aHe2ovv4sxVBH4n4ksWS6VRhiTuZeA8FNagsWziTggYOFL-OC80YvCYp6zASE4UKOWTfbo4yLuaBHdrT1-lem4l-vFO9DVfRxsk2E6lbrQiZECZLR-_HpbErRQ0wUrnkxjWsIUXOmbvTKu8Xyab8NJw5EyzPog==", "id": "rs_00b66c640e9d704c0169f788ed456c8199aa0d74ede9c26bd6", "summary": [ { "type": "summary_text", "text": "**Considering image generation**\n\nI need to respond in Spanish for the user. The task involves generating better images using OpenAI's image generation capabilities. However, I notice that we only have the image generation backend configured, which isn’t selectable. I think I might need to inspect the files or project to find out more. I'm considering relevant skills, like perhaps the political-tracker-card. I should load it and see if it's stable to proceed with image generation." } ] } ], "tool_calls": [ { "id": "call_yrYNk6GiWkvyFkOoIX4xr4dw", "call_id": "call_yrYNk6GiWkvyFkOoIX4xr4dw", "response_item_id": "fc_00b66c640e9d704c0169f788ef763881998261d75407a9a031", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"political-tracker-card\"}" } } ] }, { "role": "tool", "content": "{\"success\": true, \"name\": \"political-tracker-card\", \"description\": \"Generate political tracker/scorecard red cards (AIPAC Tracker style) using GPT Image 2 or Nano Banana via OpenRouter. Magazine-cover aesthetic, dark red backgrounds, silhouettes, large dollar amounts, editorial typography. For social media political graphics exposing lobby connections, campaign financing, and public contracts.\", \"tags\": [], \"related_skills\": [], \"content\": \"---\\nname: political-tracker-card\\ndescription: Generate political tracker/scorecard red cards (AIPAC Tracker style) using GPT Image 2 or Nano Banana via OpenRouter. Magazine-cover aesthetic, dark red backgrounds, silhouettes, large dollar amounts, editorial typography. For social media political graphics exposing lobby connections, campaign financing, and public contracts.\\ntriggers:\\n - \\\"political tracker\\\"\\n - \\\"tracker card\\\"\\n - \\\"red card\\\"\\n - \\\"AIPAC Tracker style\\\"\\n - \\\"lobby card\\\"\\n - \\\"political scorecard\\\"\\n - \\\"generate political graphic\\\"\\n - \\\"lobby tracker graphic\\\"\\n - \\\"image generation\\\"\\n - \\\"GPT Image 2\\\"\\n - \\\"Nano Banana\\\"\\n - \\\"political infographic card\\\"\\nrequirements:\\n env_vars:\\n - OPENROUTER_API_KEY\\n system_packages:\\n - curl\\n - python3\\n---\\n\\n# Political Tracker Card Generation\\n\\nGenerate red/green political tracker cards in AIPAC Tracker style using AI image generation APIs via OpenRouter.\\n\\n## Models Available\\n\\n| Model | OpenRouter ID | Best For | Quality |\\n|---|---|---|---|\\n| **GPT Image 2** (preferred) | `openai/gpt-5.4-image-2` | Editorial, photorealistic, magazine covers, text-heavy layouts | Best |\\n| Nano Banana Pro | `google/gemini-3-pro-image-preview` | Complex layouts, 2K/4K, identity preservation | Excellent |\\n| Nano Banana 2 | `google/gemini-3.1-flash-image-preview` | Fast iteration, drafts | Very Good |\\n| Nano Banana (v1) | `google/gemini-2.5-flash-image` | Quick edits, basic cards | Good |\\n\\n**Default: GPT Image 2** — photorealistic, best text rendering, magazine-cover quality.\\n\\n## Prompting Best Practices (from OpenAI docs)\\n\\n1. **Structure**: artifact type → background/scene → subject → layout → text in quotes → constraints\\n2. **Text**: put exact text in double quotes, specify role (HEADLINE, SUBHEAD, LABEL, FOOTER)\\n3. **Quality**: use `\\\"high\\\"` for text-heavy cards\\n4. **Constraints**: \\\"no watermark, no cartoon, no extra text, no border\\\"\\n5. **For photorealism**: use words like \\\"photorealistic\\\", \\\"editorial photography\\\", \\\"magazine cover\\\", \\\"Sports Illustrated style\\\"\\n\\n## Template: Red Card Generation Script\\n\\n```bash\\nOPENROUTER_KEY=$(grep OPENROUTER_API_KEY ~/.hermes/.env | cut -d= -f2)\\n\\ncurl -s --max-time 300 \\\"https://openrouter.ai/api/v1/chat/completions\\\" \\\\\\n -H \\\"Authorization: Bearer $OPENROUTER_KEY\\\" \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -d '{\\n \\\"model\\\": \\\"openai/gpt-5.4-image-2\\\",\\n \\\"modalities\\\": [\\\"image\\\", \\\"text\\\"],\\n \\\"image_config\\\": {\\\"aspect_ratio\\\": \\\"1:1\\\", \\\"image_size\\\": \\\"1K\\\"},\\n \\\"messages\\\": [{\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Sports magazine cover style political tracker card. Photorealistic, glossy editorial photography, dramatic ESPN Magazine / Sports Illustrated aesthetic. Dark crimson red background with volumetric smoke, cinematic god rays, high-contrast. Left: grayscale silhouette with rim lighting. Right: giant glossy white dollar amount. HEADLINE: [NAME]. SUBHEAD: [POSITION]. NUMBER: [AMOUNT]. LABEL: [LOBBY NAME] TOTAL. Bottom: magazine cover lines with stats. Barcode, date stamp. Photorealistic editorial magazine cover.\\\"\\n }]\\n }' -o /tmp/card.json\\n\\npython3 -c \\\"\\nimport json, base64\\nwith open('/tmp/card.json') as f:\\n d = json.load(f)\\nmsg = d.get('choices',[{}])[0].get('message',{})\\nimgs = msg.get('images',[])\\nif imgs:\\n url = imgs[0]['image_url']['url']\\n data = url.split(',')[1]\\n with open('/tmp/tracker_card.png','wb') as f:\\n f.write(base64.b64decode(data))\\n print('Saved: /tmp/tracker_card.png')\\nelse:\\n print(f'Error: {json.dumps(d.get(\\\\\\\"error\\\\\\\",{}), indent=2)[:300]}')\\n\\\"\\n```\\n\\n## Fallback: Nano Banana 2\\n\\n```bash\\n# Same curl structure, different model:\\n\\\"model\\\": \\\"google/gemini-3.1-flash-image-preview\\\"\\n# Prompts should be shorter, less text-heavy\\n```\\n\\n## AIPAC Tracker Design Spec\\n\\n**Red cards** (exposing pro-lobby politicians):\\n- Grayscale candidate photo/silhouette on LEFT (45%)\\n- Dark crimson/smoky red background filling ENTIRE card\\n- GIANT white dollar amount on RIGHT (55%) — the \\\"glowing number\\\"\\n- Label: \\\"[LOBBY NAME] TOTAL\\\" in uppercase\\n- Bullet points with specific funding sources\\n- Footer: \\\"TRACKER — [COUNTRY] 🇦🇷\\\"\\n\\n**Green cards** (endorsed/clean candidates):\\n- Same layout but green background\\n- Shows $0 or minimal lobby funding\\n- \\\"REJECTS [LOBBY] CASH\\\" label\\n\\n## GPT Image 2 Sports Magazine Villain Style (May 2026)\\n\\nFor maximum visual impact, use the sports signing poster aesthetic (Lautaro Martinez Inter Milan style). GPT Image 2 excels here. Key elements:\\n\\n- **HIGH ANGLE** perspective — camera above, looking down (they're beneath us)\\n- **ELECTRIC RED LIGHTNING** bolts across dark crimson background\\n- **VILLAIN ENERGY** — grayscale silhouette, red rim lighting, no eye contact, caught-in-the-act\\n- **SPORTS POSTER TYPOGRAPHY** — massive bold names, glossy white stat numbers\\n- **4:5 vertical** aspect ratio (best for Twitter/Instagram)\\n- **Glossy magazine texture**, cinematic god rays, volumetric fog\\n\\nPrompt template:\\n```\\nSports magazine cover political tracker card, 4:5 vertical.\\nHIGH ANGLE looking DOWN — ominous villain energy.\\nDeep blood-red background with ELECTRIC RED LIGHTNING,\\ncinematic fog, glossy magazine texture.\\nSilhouette of suited politician, grayscale, high angle, red rim-lit.\\nBold white sports fonts. Top: \\\"LOBBY TRACKER ARGENTINA 🇦🇷\\\"\\nMassive: \\\"[LAST NAME]\\\". Above: \\\"[FIRST NAME]\\\"\\nGiant glossy: \\\"$[AMOUNT]+\\\". Label: \\\"[LOBBY] TOTAL\\\"\\nBottom lines: \\\"[FACT 1] | [FACT 2] | [FACT 3]\\\"\\nPhotorealistic editorial sports magazine cover. Barcode. Date stamp.\\n```\\n\\n## Collectible Card Format (May 2026 iteration)\\n\\nAfter user feedback, evolved from book-cover to **collectible trading card** style:\\n- **NO borders or book frames** — clean card edges with subtle glow\\n- **QR code** (bottom right) with \\\"ESCANEAR PARA VER CONEXIONES\\\" — links to full connections website at lobby-tracker URL\\n- **6+ stats bullet points** — not just 3, include all relevant facts\\n- **Both ARS and USD** — always convert using historical blue dollar rates (see table below)\\n- **Footer URL**: website domain\\n- **Key lesson**: Do NOT over-control the prompt. V6 failed because too many constraints killed GPT Image 2's creative visual metaphors (obelisk, Israeli flag, money stacks, contract papers). The V5 prompt let GPT be creative and it delivered excellence. Only tweak ONE thing at a time (e.g. spacing).\\n\\n## jq Extraction Trick (faster than Python for large responses)\\n\\n```bash\\n# For 2MB+ responses, jq is faster than Python's json module:\\njq -r '.choices[0].message.images[0].image_url.url' /tmp/card.json | cut -d, -f2 | base64 -d > /tmp/output.png\\n```\\n\\n## Currency Conversion: Argentina Blue Dollar\\n\\nALWAYS convert ARS amounts to USD using the historical \\\"dólar blue\\\" rate for the transaction date.\\n\\n| Year | Blue Dollar Range | Midpoint |\\n|---|---|---|\\n| 2021 | $141 - $208 | ~$180 ARS/USD |\\n| 2022 | $200 - $346 | ~$280 ARS/USD |\\n| June 2022 | ~$240 | ~$240 ARS/USD |\\n| 2023 | $346 - $1,025 | ~$600 ARS/USD |\\n\\nFormat: `ARS $2.400.000.000+` / `≈ USD $8.000.000+`\\nSources: cotizacion-dolar.com.ar, bloomberglinea.com\\n\\n## Card Evolution History\\n\\nThis documents the iterative feedback loop — useful for future card generation to avoid repeated mistakes:\\n\\n1. **V1 (Nano Banana Pro)**: Generic dark infographic, 4-square grid → **REJECTED**. \\\"No se parece en NADA a AIPAC Tracker.\\\"\\n2. **V2 (Nano Banana 2)**: Red card, silhouette, dollar amount → **MISSED (wasn't delivered)**. Too flat, lacked punch.\\n3. **V3 (GPT Image 2)**: Red card with stats, barcode → **REJECTED**. \\\"Le falta ese punch típico de imagen2.\\\"\\n4. **V4 (GPT Image 2)**: Sports magazine cover, cinematic, silhouette, high angle → **APPROACH CORRECT**. User said \\\"Va queriendo. La posición del personaje y su forma es excelente.\\\"\\n5. **V5 (GPT Image 2)**: Collectible card, no borders, QR, ARS+USD, 6 stats, villain energy, high angle, electric lightning, obelisk + Israeli flag visual metaphors → **FINAL DESIGN — APPROVED**. User said \\\\\\\"Excelente. Me encanta. Podes manejar un poco mejor el posicionamiento de las cosas.\\\\\\\"\\n6. **V6 (GPT Image 2)**: Attempted to fix text spacing but OVER-CONTROLLED the prompt → **REJECTED**. Lost creative visual elements (obelisk, flag, money). User: \\\\\\\"Donde esta el obelisco la bandera de Israel qué estaba en la otra imagen, el contrato y los dolares, le quedaba muy bien! La cagaste con la última imagen.\\\\\\\"\\n7. **V7 (GPT Image 2)**: Restored original V5 prompt, only added spacing + \\\\\\\"let the model be creative with visual metaphors\\\\\\\" → **FINAL APPROVED.** User: \\\\\\\"Hermoso. Ya estamos con el diseño. Dejalo fijo así.\\\\\\\"\\n\\nKey learnings across iterations:\\n- GPT Image 2 >> Nano Banana for this use case\\n- Magazine sports cover aesthetic > flat infographic\\n- HIGH ANGLE villain perspective resonated strongly\\n- Always include BOTH ARS and USD\\n- QR code > barcode (functional purpose)\\n- Collectible trading card > book layout\\n- 6+ detailed stats > 3 bullet points\\n- **CRITICAL: Do NOT over-control the prompt.** V6 was worse because too many layout constraints killed GPT's creativity. Let the model add visual metaphors (obelisk, flag, money, papers). Only change ONE thing per iteration.\\n\\n## Animating Tracker Cards into GIF/MP4\\n\\nUse this sub-workflow when the user asks to animate an existing political tracker card, make an impact GIF/video for a detail page/social post, or mimic the mood of a reference short without relying on the original video file.\\n\\n### Preferred input order\\n\\n1. **Use the approved source image** if present (the exact card/poster the user liked).\\n2. If the exact image is missing, recover it from likely paths before asking:\\n - `~/.hermes/image_cache/`\\n - `/tmp/` (`nano_card.png`, `gpt2_*.json`, `tracker_card.png`, etc.)\\n - session logs with `session_search` or direct `~/.hermes/sessions/*` search for `MEDIA:`, `data:image`, `gpt2_v`, `Hermoso`, `obelisco`, `bandera`.\\n3. If still missing, use a project screenshot or current site card as a temporary demo only, and tell the user the exact image will produce a better result.\\n\\n### When YouTube/Shorts download is blocked\\n\\nYouTube Shorts often fail from Oracle/datacenter IPs with `Sign in to confirm you’re not a bot`, even with fresh `yt-dlp`. Try the standard fast path first:\\n\\n```bash\\npython3 -m venv /tmp/ytdlpvenv\\n/tmp/ytdlpvenv/bin/pip install -q -U yt-dlp\\n/tmp/ytdlpvenv/bin/yt-dlp --no-playlist --force-ipv4 \\\\\\n --extractor-args 'youtube:player_client=web_creator,ios' \\\\\\n -f 'bv*[height<=720]+ba/b[height<=720]/best' \\\\\\n -o '/tmp/reference_short.%(ext)s' 'https://youtube.com/shorts/VIDEO_ID'\\n```\\n\\nIf blocked, do not stall. First use YouTube oEmbed to recover basic metadata/thumbnail/title for style clues without downloading the video:\\n\\n```bash\\ncurl -sS 'https://www.youtube.com/oembed?url=https://www.youtube.com/shorts/VIDEO_ID&format=json'\\n```\\n\\nThen treat the short as a **style reference** and recreate the effect procedurally: jump cuts/glitch slices, red/blue chromatic offsets, sudden zooms, scanlines, flicker, red impact flashes, grain/VHS noise, and short-form pacing. For a CapCut/terror edit, a square or vertical card with punch zooms and 1-frame dark/red flashes can work even without the original video.\\n\\n### Procedural GIF/MP4 recipe\\n\\nA reliable no-GPU path:\\n\\n1. Ensure tools:\\n ```bash\\n python3 -m venv /tmp/gifvenv\\n /tmp/gifvenv/bin/pip install -q pillow numpy imageio\\n command -v ffmpeg\\n ```\\n If the active Hermes Python lacks `pip` or imports still fail, use the system Python path instead:\\n ```bash\\n sudo apt-get update\\n sudo apt-get install -y python3-pil python3-numpy\\n /usr/bin/python3 - <<'PY'\\n import PIL, numpy\\n print('ok')\\n PY\\n ```\\n2. Create frames with Pillow/NumPy:\\n - vertical `540x960` or `720x1280`\\n - darkened/zoomed source card or screenshot background\\n - red radial rays behind the politician/card\\n - glowing symbolic elements (flag/contract/money) as overlays\\n - card/person rising from bottom-center using ease-out cubic motion\\n - 1-3 frame glitch cuts with horizontal roll and RGB channel offsets\\n - scanlines + vignette for short-video tension\\n3. Encode both GIF and MP4:\\n ```bash\\n # GIF via Pillow for portability; keep <= ~8MB when possible\\n # MP4 is much smaller and better for web/Telegram\\n ffmpeg -y -framerate 15 -i /tmp/frames/frame_%03d.png \\\\\\n -vf 'format=yuv420p' -movflags +faststart public/larreta-impact-demo.mp4\\n ```\\n4. Verify a mid-frame with `vision_analyze` before sending.\\n\\n### OpenRouter video / Veo 3.1 motion-poster workflow\\n\\nUse this when the user asks to make a higher-impact video from a static tracker card using OpenRouter video models (e.g. `google/veo-3.1`) or wants a YouTube Shorts/Reels-style motion poster.\\n\\n1. **Survey available video models and pricing before submitting jobs**:\\n ```bash\\n set -a; . ~/.hermes/.env; set +a\\n /usr/bin/python3 - <<'PY'\\n import os, requests\\n j=requests.get('https://openrouter.ai/api/v1/videos/models',\\n headers={'Authorization':'Bearer '+os.environ['OPENROUTER_API_KEY']}, timeout=30).json()\\n for m in j['data']:\\n if 'veo' in m['id'] or 'google' in m['id']:\\n print(m['id'], m.get('supported_resolutions'), m.get('supported_aspect_ratios'),\\n m.get('supported_durations'), m.get('pricing_skus'))\\n PY\\n ```\\n As of May 2026, `google/veo-3.1` supports `/api/v1/videos` with `aspect_ratio`, `duration`, `resolution`, `generate_audio`, `frame_images`, and polling via `polling_url`. `google/veo-3.1-fast` and `google/veo-3.1-lite` are cheaper iteration options.\\n\\n2. **For image-to-video attempts**, publish the source card under `public/` first so OpenRouter can fetch it:\\n ```bash\\n cp ~/.hermes/image_cache/.jpg public/media/source-card.jpg\\n vercel --prod --yes\\n ```\\n\\n3. **Submit the job and poll**:\\n ```python\\n import os, json, requests, pathlib, time\\n prompt = pathlib.Path('assets/video-ref/veo_prompt.txt').read_text()\\n payload = {\\n 'model': 'google/veo-3.1',\\n 'prompt': prompt,\\n 'aspect_ratio': '9:16',\\n 'duration': 8,\\n 'resolution': '720p',\\n 'generate_audio': False,\\n 'frame_images': [{\\n 'type': 'image_url',\\n 'frame_type': 'first_frame',\\n 'image_url': {'url': 'https:///media/source-card.jpg'}\\n }]\\n }\\n r = requests.post('https://openrouter.ai/api/v1/videos',\\n headers={'Authorization':'Bearer '+os.environ['OPENROUTER_API_KEY'], 'Content-Type':'application/json'},\\n json=payload, timeout=60)\\n r.raise_for_status()\\n polling_url = r.json()['polling_url']\\n # GET polling_url with the same Authorization header until status is completed/failed.\\n # Download returned content URLs WITH Authorization header; unsigned_urls may still require auth.\\n ```\\n\\n4. **If Veo/Vertex filters image-to-video with real politicians or sensitive poster text**, do not burn repeated full-price retries. Use a two-layer approach:\\n - Generate a neutral 9:16 red/black investigative **motion background** with no real names, no readable political text, no real people, no claims.\\n - Composite the approved card/poster locally on top with Pillow/ffmpeg, preserving the exact source image and adding zoom pulses, shake, scanlines, RGB split, glitch bars, and subtitles.\\n - This keeps the factual poster unchanged while using Veo only for cinematic motion texture.\\n\\n Safe background prompt pattern:\\n ```text\\n Create an 8-second vertical 9:16 motion-poster video for a dark investigative documentary teaser. Red-and-black editorial thriller, polished YouTube Shorts/CapCut-style glitch edit. A stylized graphic poster fills the frame: a stern adult male figure in a dark suit is centered in shadow, surrounded by abstract documents, money-like paper shapes, a city monument silhouette, and a dark flag-like graphic background. Bold white headline blocks are abstract poster typography. Do not render readable real names, numbers, logos, political claims, country names, or QR codes. Slow cinematic push-in, three hard zoom-punch beats, red lightning flicker, parallax, VHS grain, scanlines, chromatic aberration, horizontal glitch bars, micro camera shake, red flash frames, final one-second hold for loop. No gore, no weapons, no physical harm, no real people, no readable political text.\\n ```\\n\\n5. **Composite locally**:\\n - Decode Veo MP4 frames with `ffmpeg -i veo-bg.mp4 /tmp/bg/frame_%04d.png`.\\n - Place the approved poster/card centered over the background; for vertical videos, keep the card around `690x690` on a `720x1280` canvas.\\n - Use slow push-in plus beat pulses around `1.5s`, `4.0s`, `6.2s`.\\n - Add subtitle/CTA only if desired; avoid adding any new factual claims.\\n - Export MP4 for web and a smaller GIF for previews.\\n\\n6. **Verify**:\\n - Create a contact sheet from 3-4 frames and run `vision_analyze` for cropping/readability.\\n - `ffprobe` the MP4 and `curl` deployed asset URLs.\\n\\n### OpenRouter/content-policy fallback\\n\\nImage generation/editing/video prompts using real politicians + ominous language + national/religious symbols may return `PROHIBITED_CONTENT`, Vertex usage-guideline errors, or “completed with no output (content may have been filtered)”. If that happens:\\n\\n- Do **not** keep retrying the same prompt.\\n- For static image generation/editing: use the already-approved/static card as the source and animate locally.\\n- For Veo/video: generate a neutral motion background with no real names/claims/readable political text, then composite the approved card locally.\\n- Keep the visual editorial, not defamatory: labels should reflect the project’s documented tracker framing, while evidence claims remain on the site/DB.\\n\\n### Integration note\\n\\nFor a Next.js project, save assets under `public/` so they can be referenced as `/larreta-impact-demo.gif` or `/larreta-impact-demo.mp4`. Prefer MP4 in the page for size/performance, with GIF for chat previews.\\n\\n## Pitfalls\\n\\n- **GPT Image 2 timeout**: use `--max-time 300` minimum; the model renders slowly (sometimes 60-120s)\\n- **Base64 decoding**: output is `data:image/png;base64,...` — split on comma, decode part [1]\\n- **Large responses**: A 2.3MB response JSON takes ~10s to base64 decode — use heredoc Python, not one-liner\\n- **Nano Banana timeout**: even slower than GPT Image 2; reduce prompt complexity\\n- **Text hallucination**: ALWAYS verify generated text with vision_analyze before sending to user\\n- **OpenRouter routing**: GPT Image 2 requires OpenAI API key configured in OpenRouter; Nano Banana works with Google AI keys\\n- **Empty curl responses**: If curl times out, check file size (0 bytes = curl failed, retry)\\n- **Exact approved image missing**: search caches/session logs first; if unavailable, create a demo from a site screenshot but clearly ask for the exact image for final quality.\\n- **GIF size**: vertical GIFs get large quickly; also export MP4 because it is usually 10-50x smaller.\\n- **Hermes venv may not have pip/Pillow**: if `python3 -m pip` says `No module named pip` or Pillow imports fail, install `python3-pil python3-numpy` with apt and run generation scripts with `/usr/bin/python3`.\\n- **Font path drift**: `DejaVuSansCondensed-Bold.ttf` may not exist; search `/usr/share/fonts/**/*.ttf` and fall back to `/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf`.\\n- **Short download blocked**: use oEmbed metadata for title/thumbnail/context, then recreate the style locally rather than waiting on yt-dlp/CDP.\\n\", \"path\": \"political-tracker-card/SKILL.md\", \"skill_dir\": \"/home/ubuntu/.hermes/skills/political-tracker-card\", \"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\"}", "tool_call_id": "call_yrYNk6GiWkvyFkOoIX4xr4dw" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": 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"id": "rs_03fb7e6718b23e460169f788f11aac819ab255dc7f386f3133", "summary": [] } ], "tool_calls": [ { "id": "call_cyEnYxxqVTeS6UdTn7iFepWH", "call_id": "call_cyEnYxxqVTeS6UdTn7iFepWH", "response_item_id": "fc_03fb7e6718b23e460169f788fb39ec819a80b9eabe7cbc9768", "type": "function", "function": { "name": "todo", "arguments": "{\"todos\":[{\"id\":\"regen-openai\",\"content\":\"Regenerar imagen estilo adjunta con GPT Image 2/OpenRouter, hiperrealista y sin estética barata\",\"status\":\"in_progress\"},{\"id\":\"short-effect\",\"content\":\"Bajar o reconstruir efecto del YouTube Short y producir GIF/MP4 sobre la imagen adjunta\",\"status\":\"pending\"},{\"id\":\"integrate\",\"content\":\"Dejar assets en lobbytracker y proponer siguiente acción estratégica\",\"status\":\"pending\"}]}" } } ] }, { "role": "tool", "content": "{\"todos\": [{\"id\": \"regen-openai\", \"content\": \"Regenerar imagen estilo adjunta con GPT Image 2/OpenRouter, hiperrealista y sin estética barata\", \"status\": \"in_progress\"}, {\"id\": \"short-effect\", \"content\": \"Bajar o reconstruir efecto del YouTube Short y producir GIF/MP4 sobre la imagen adjunta\", \"status\": \"pending\"}, {\"id\": \"integrate\", \"content\": \"Dejar assets en lobbytracker y proponer siguiente acción estratégica\", \"status\": \"pending\"}], \"summary\": {\"total\": 3, \"pending\": 2, \"in_progress\": 1, \"completed\": 0, \"cancelled\": 0}}", "tool_call_id": "call_cyEnYxxqVTeS6UdTn7iFepWH" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_NWmYCB2eXdXlV46tUuuJRbjB", "call_id": "call_NWmYCB2eXdXlV46tUuuJRbjB", "response_item_id": "fc_02e1f6d5a62956b90169f78902e790819ab710d7a3f56c52d9", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"set -euo pipefail\\ncd /home/ubuntu/lobbytracker\\nprintf 'cwd='; pwd\\nprintf 'openrouter='; if [ -n \\\"${OPENROUTER_API_KEY:-}\\\" ]; then echo env; elif [ -f ~/.hermes/.env ] && grep -q '^OPENROUTER_API_KEY=' ~/.hermes/.env; then echo hermes_env; else echo missing; fi\\nprintf 'ffmpeg='; command -v ffmpeg\\nprintf 'attached='; file /home/ubuntu/.hermes/image_cache/img_184c12b449fc.jpg\\nprintf 'size='; identify /home/ubuntu/.hermes/image_cache/img_184c12b449fc.jpg 2>/dev/null || true\", \"timeout\": 60, \"workdir\": \"/home/ubuntu/lobbytracker\"}" } } ] }, { "role": "tool", "content": "{\"output\": \"cwd=/home/ubuntu/lobbytracker\\nopenrouter=hermes_env\\nffmpeg=/usr/bin/ffmpeg\\nattached=/home/ubuntu/.hermes/image_cache/img_184c12b449fc.jpg: JPEG image data, JFIF standard 1.01, resolution (DPI), density 72x72, segment length 16, progressive, precision 8, 896x1120, components 3\\nsize=\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_NWmYCB2eXdXlV46tUuuJRbjB" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94kL4mf3UYyxnxsQAg2U62kGSA4JidDEjsbOtYXT_YyODp2vqph6ijA5pgcuXQpTERiY558e_A5xl4oTCYS74RMTgmWjYid9LqMSTQ7eUYYowpHO2Jif_FejdvmMImFIAxnjFJwNG40DtAqQO5mJ-0XtzyilDrea83cr3-GuZ-oxcl0nCXWvPBtI-QceVdhU9hBpHIaE8wA2m_IEARZ8EDJoTm3wyS44-6nyAGIJU5w5G6tsdceoRa6PucoZUM6o1LHOJ37WMoejBKUNjA89qdnyPC871BBqcspwEayDRhkRP4nllH1mnVGJWhfXHh2NNEl5sT7LWxoPDKFrhjvP2XNpHeCVBO-hgD3iiSQHaVNIagf50owAFPzLAVuPT0PISDI4cCZAhe6YCcX4NboYG_3N7UOcdpbqUR5qnqeFhvx3yZ1NtIwGxk0L596oJajyt3vZMdFcoPrpuqphvCy1X64Y9xaeQoLFLK7Gl7FHBzsGDtfx856Cz_yIrNLTRoLPkINNZRF7zBD7tayp5rXJtUFxkQSFD20zUl_g9W74nKSdKsq7Yr-g4AQNp7tjgUplcIWdSYX343RUoGT0rgAeqhSu4uERa1S6KqHf2GFEi7xVVzjUSTt9BOHGVI11UXtIxQFhEWiaQz-nyGNN-WG_WdJvJTsYST6TMwKYlPqcEVkbLgCCXwdi-L_dGXw3pz4kEZLBUDz5XiUHaTAvzZ-vTCk8D0rugyW4qqk17WhVtGkCJToEtl60tO_bBjAYuPYKbnx1bEkL8yO85yqvMy4Ypvwr0H-peSg4HYhpNtodkvlUsjhEFtV-FBQkBsOfj_Mx686UuXND2qx-uONlktjIIhPTL_IuP7yb0eDw6zRANhGe5nU1rgxEfQ-HSx1qo5_0vJ4-2yBqGgTeXsiXuxuBpfW0InJmAtahGXhf_Ppsi0fbYBE5ZeNRODr-OY6x6U1gcyvn34POIwEPv56q2a3wBjTW2yDdOJ_NYG1vGgsfzigNF4eRF3qAXxleF_mVQ7i__r7KiTQ9HI3nI3ObfbSWhKxfkDh8LX-mJ276ClQXTU1zegwT7fkQG4Bg1Ovg94dZCD7GALsStsQj2-WXpd_KlAufGGmvjtM8vPdOR1-vuecqbVoMvr_VE8l9D3RP5MF553oFJmQlL803JpkEL3apOj6I_KU07_T5lZWfJLpvG1JkbctcUDPsrYT1KjPyjPdia3IRjXQVeM5clnPCBV6zEZGfBw==", "id": "rs_05c5cd84d9767f910169f789087c908199af547e9a40c4f924", "summary": [] } ], "tool_calls": [ { "id": "call_WvccUjAQqo9Funjs7iKzVwpy", "call_id": "call_WvccUjAQqo9Funjs7iKzVwpy", "response_item_id": "fc_05c5cd84d9767f910169f7890b303c81998f25df366a151891", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"set -euo pipefail\\ncd /home/ubuntu/lobbytracker\\nset -a; [ -f ~/.hermes/.env ] && . ~/.hermes/.env; set +a\\nmkdir -p public/cards/generated public/media\\npython3 - <<'PY'\\nimport os, base64, json, requests, pathlib, textwrap, sys, time\\nsrc=pathlib.Path('/home/ubuntu/.hermes/image_cache/img_184c12b449fc.jpg')\\nimg_b64=base64.b64encode(src.read_bytes()).decode()\\nprompt = r'''Usá la imagen adjunta como REFERENCIA VISUAL PRINCIPAL. Crear una nueva pieza política vertical 4:5, hiperrealista, calidad OpenAI GPT Image 2, estilo póster/carta coleccionable investigativa.\\n\\nMantener el MISMO PUNCH que la referencia: cielo rojo tormentoso, rayos eléctricos rojos/blancos, Obelisco de Buenos Aires a la izquierda, bandera de Israel ondeando al fondo derecho, pilas de dólares reales en primer plano, papeles/contrato visible, Horacio Rodríguez Larreta como figura central fotorrealista en traje, iluminación cinematográfica roja, alto contraste, textura glossy de magazine cover, thriller político argentino.\\n\\nDiseño tipográfico editorial fuerte, legible, tipo portada deportiva/investigación. No hacerlo flat, no cartoon, no vector genérico, no íconos baratos, no mockup web.\\n\\nTexto exacto y jerarquía:\\nArriba pequeño: \\\"LOBBY TRACKER ARGENTINA 🇦🇷\\\"\\nNombre pequeño arriba del apellido: \\\"HORACIO RODRIGUEZ\\\"\\nHeadline gigante: \\\"LARRETA\\\"\\nMonto gigante: \\\"ARS $2.400.000.000+\\\"\\nDebajo: \\\"≈ USD $8.000.000+\\\"\\nEtiqueta: \\\"ISRAEL LOBBY TOTAL\\\"\\nBullets abajo, en blanco, condensados y legibles:\\n\\\"CONTRATOS CÁMARA COMERCIO ARG-ISRAELÍ\\\"\\n\\\"VIAJE OFICIAL ISRAEL 2022\\\"\\n\\\"WALDO WOLFF EX-DAIA EN GABINETE\\\"\\n\\\"ASOMBRO EXTREMO: DÓLARES CAMPAÑA 2019\\\"\\n\\\"FONCAP: CAUSA SIGUE EN CORTE\\\"\\n\\\"DANAIDE: DATOS BIOMÉTRICOS SUSPENDIDOS\\\"\\nFooter izquierda: \\\"MAY 2026\\\"\\nFooter centro: \\\"LOBBYTRACKER.AR\\\"\\nAbajo derecha: QR-like square placeholder with label \\\"ESCANEAR\\\"\\n\\nImportante: que parezca una imagen publicitaria hiperrealista cara, no una placa hecha con Canva. Dramático, agresivo, cinematográfico, argentino. Dejar que el modelo agregue metáforas visuales como humo, documentos, dólares, tormenta, pero NO agregar textos inventados ni logos de medios.'''\\npayload={\\n \\\"model\\\":\\\"openai/gpt-5.4-image-2\\\",\\n \\\"modalities\\\":[\\\"image\\\",\\\"text\\\"],\\n \\\"image_config\\\":{\\\"aspect_ratio\\\":\\\"4:5\\\",\\\"image_size\\\":\\\"1K\\\"},\\n \\\"messages\\\":[{\\\"role\\\":\\\"user\\\",\\\"content\\\":[\\n {\\\"type\\\":\\\"text\\\",\\\"text\\\":prompt},\\n {\\\"type\\\":\\\"image_url\\\",\\\"image_url\\\":{\\\"url\\\":\\\"data:image/jpeg;base64,\\\"+img_b64}}\\n ]}]\\n}\\nheaders={\\\"Authorization\\\":\\\"Bearer \\\"+os.environ['OPENROUTER_API_KEY'],\\\"Content-Type\\\":\\\"application/json\\\"}\\nprint('requesting gpt image 2...', flush=True)\\nr=requests.post('https://openrouter.ai/api/v1/chat/completions',headers=headers,json=payload,timeout=300)\\npathlib.Path('/tmp/larreta_gpt_image2_response.json').write_text(r.text)\\nprint('status', r.status_code, 'len', len(r.text))\\nif r.status_code>=400:\\n print(r.text[:1000]); sys.exit(1)\\nd=r.json()\\nmsg=d.get('choices',[{}])[0].get('message',{})\\nimgs=msg.get('images') or []\\nif not imgs:\\n print(json.dumps(d, indent=2)[:2000]); sys.exit(2)\\nurl=imgs[0]['image_url']['url']\\nif url.startswith('data:'):\\n data=url.split(',',1)[1]\\n out=pathlib.Path('public/cards/generated/larreta-gpt-image2-v1.png')\\n out.write_bytes(base64.b64decode(data))\\n print(out.resolve())\\nelse:\\n print('url',url)\\nPY\\nfile public/cards/generated/larreta-gpt-image2-v1.png\\nls -lh public/cards/generated/larreta-gpt-image2-v1.png\", \"timeout\": 360, \"workdir\": \"/home/ubuntu/lobbytracker\"}" } } ] }, { "role": "tool", "content": "{\"output\": \"requesting gpt image 2...\\nstatus 200 len 2546188\\n/home/ubuntu/lobbytracker/public/cards/generated/larreta-gpt-image2-v1.png\\npublic/cards/generated/larreta-gpt-image2-v1.png: PNG image data, 896 x 1120, 8-bit/color RGB, non-interlaced\\n-rw-rw-r-- 1 ubuntu ubuntu 1.9M May 3 17:45 public/cards/generated/larreta-gpt-image2-v1.png\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_WvccUjAQqo9Funjs7iKzVwpy" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94nS-znJM7ouXt8NF1OUP4wtQqZGHbsXavIc21TOVP-_AnYhnQKM90Khie0V_s5nlXMs34iFX7kc9Cn-yZ7zm5cTD_AAtzGZc0eo-rM6rV5kIFoPV4qNuU4Ibb3sP8kAxMiT83CvSygu8NmyxcZC7EQ5ebuQdx7BBxN8Gdm4vbjJV7UU_9pJ9Y1IR3HQcpaW4Jk7X7VYdxSJhxvXE6cve_gDC_cU-fL3kzGe3w8R3TvwpauAgl1ex7xKcvB62IIZw9swsPO2LoY5sypy90XDJhxYP4_dd6WSm4LvSK6VXSlouvLLRGdjldS58Of9W26FjHhdFnhHWK_6eNGxAIgqhOG_wxU5eYQncF6uQ94b-D3qaKGQtppwPqAILqQi---KT8o4tO1A7EMz7K6xhBc7YC4Uv0txKOXRRsinvsp5pgcb24i3GHIm7yAKEz27MybgRMWB5PXVhb7MFzZtRPep0GpUhhjjySbWWt1PIi1EICpE5YSFkoOJosoisXxknHkaN5cllwktP2wDBbVsu36KQCPtUey9cHUNHFsxV42sWk2ar-gaeX8ZIAyLYzKna700IUnGXMPmA84EgxK8iJ0GZTjteJvoaGyI8qBzl4Czp7lNgdU5ERGxSbwOUug9fzIMGAbn1QXKkWoRr4qi0mOMNsLa8riYCTDt6nVyeBiT2PL9Hju9jJl7JrdL6m3uZROZl2PpG4vwvajdJZN10DqCS8lMUJxuwiS7-PLK1zvemPACk-rVLhsmeDk55PPCASaOtZwWEkU5b4uwOXl7FYX1ToGWFocZP2sgNcGvbwJCGh1tFS73SKDLY6p7sr7dyr_lnqH6K3oLKepdDmMVtCZ4Gtssh4QCrPR_duqU8xz1RpSmJV-C2Kh5UTTUuHDs2WQOSMrQKQde2bxybMoj3mp_NOjjiTSQTXsaeVFdrexH7mQodVXNzCPAgivfsiA36sboWvAlL_xPpqu0X4kjjXrfmzlMqw==", "id": "rs_0131aaa44b7f45660169f789d15f5c819bb28f05d41a0886e7", "summary": [] } ], "tool_calls": [ { "id": "call_YVaqLIKGsGica14gz6IJ17fo", "call_id": "call_YVaqLIKGsGica14gz6IJ17fo", "response_item_id": "fc_0131aaa44b7f45660169f789d21cf0819b9a54e960f4ef1af9", "type": "function", "function": { "name": "vision_analyze", "arguments": "{\"image_url\":\"/home/ubuntu/lobbytracker/public/cards/generated/larreta-gpt-image2-v1.png\",\"question\":\"Evaluá si esta imagen cumple: hiperrealista, parecida a la referencia adjunta con Obelisco, bandera de Israel, dólares/contrato, estética cinemática roja, texto legible. Señalá problemas concretos de texto o composición.\"}" } } ] }, { "role": "tool", "content": "{\n \"success\": true,\n \"analysis\": \"Here's a breakdown of the image and an evaluation based on your criteria:\\n\\n**Image Description**\\n\\nThe image is a poster or promotional graphic featuring Horacio Rodríguez Larreta, an Argentine politician. It has a strong, somewhat ominous tone, suggesting a critical or accusatory message. Here's a detailed breakdown:\\n\\n* **Central Figure:** Horacio Rodríguez Larreta is prominently displayed in the center. He's wearing a suit and tie, and his expression is serious, almost stern. The lighting emphasizes his face, creating shadows that add to the intensity.\\n* **Background:** The background is a dramatic red and black scene. It includes:\\n * The Obelisco of Buenos Aires, a famous landmark, on the left.\\n * An Israeli flag on the right.\\n * Lightning or electrical discharges in the sky, contributing to the dramatic and potentially negative atmosphere.\\n * A cityscape, possibly Buenos Aires, in the lower background.\\n* **Money and Contracts:** Stacks of US dollar bills and a document labeled \\\"CONTRATO\\\" (Contract) with the text \\\"CÁMARA DE COMERCIO ARGENTINO ISRAELÍ\\\" (Argentine-Israeli Chamber of Commerce) are visible, suggesting financial dealings or corruption.\\n* **Text and Information:**\\n * \\\"LOBBY TRACKER ARGENTINA\\\" is at the top, suggesting the source or organization behind the image.\\n * \\\"HORACIO RODRIGUEZ LARRETA\\\" is prominently displayed.\\n * Large text indicates \\\"ARS $2.400.000.000+\\\" and \\\"USD $8.000.000+\\\", implying large sums of money.\\n * \\\"ISRAEL LOBBY TOTAL\\\" is highlighted.\\n * A list of bullet points provides further details, including:\\n * \\\"CONTRATOS CÁMARA COMERCIO ARG-ISRAELÍ\\\" (Contracts Argentine-Israeli Chamber of Commerce)\\n * \\\"VIAJE OFICIAL ISRAEL 2022\\\" (Official Trip to Israel 2022)\\n * \\\"WALDO WOLFF EX-DAIA EN GABINETE\\\" (Waldo Wolff Ex-DAIA in Cabinet)\\n * \\\"ASOMBRO EXTREMO: DÓLARES CAMPAÑA 2019\\\" (Extreme Astonishment: Campaign Dollars 2019)\\n * \\\"FONCAP: CAUSA SIGUE EN CORTE\\\" (FONCAP: Case Continues in Court)\\n * \\\"DANAIDE: DATOS BIOMÉTRICOS SUSPENDIDOS\\\" (DANAIDE: Suspended Biometric Data)\\n * \\\"MAY 2026\\\" is at the bottom left.\\n * \\\"LOBBYTRACKER.AR\\\" is at the bottom center, likely a website address.\\n * A QR code is in the bottom right corner with the word \\\"ESCANEAR\\\" (Scan).\\n* **Overall Tone:** The image conveys a sense of suspicion, accusation, and potential corruption, linking Larreta to financial dealings with Israel. The red color scheme, lightning, and serious expression all contribute to this negative tone.\\n\\n**Evaluation Based on Your Criteria**\\n\\nLet's evaluate the image based on your specific requirements:\\n\\n* **Hiperrealista (Hyperrealistic):** The image is *not* hyperrealistic. While the portrait of Larreta is detailed, the overall composition and background elements (lightning, Obelisco, flag) are clearly stylized and digitally manipulated. It has a more cinematic or illustrative quality than a photorealistic one.\\n* **Parecida a la referencia adjunta con Obelisco, bandera de Israel, dólares/contrato (Similar to the attached reference with Obelisco, Israeli flag, dollars/contract):** The image *does* contain all of these elements: the Obelisco, the Israeli flag, dollars, and a contract. The degree of similarity to a specific reference would depend on the reference itself, which you haven't provided.\\n* **Estética cinemática roja (Red cinematic aesthetic):** The image *definitely* has a red cinematic aesthetic. The dominant color is red, and the overall composition, lighting, and dramatic elements are reminiscent of movie posters or cinematic visuals.\\n* **Texto legible (Legible text):** For the most part, the text is legible. However, there are some potential issues:\\n * The text within the \\\"CONTRATO\\\" document is likely too small to be read.\\n * The bullet points at the bottom are relatively small and might be difficult to read at a distance or on a smaller screen.\\n* **Señalá problemas concretos de texto o composición (Point out specific text or composition problems):**\\n * **Text:** As mentioned above, the text within the contract is illegible. The bullet point text could be larger for better readability.\\n * **Composition:** The composition is somewhat busy. There are a lot of elements competing for attention (Larreta's face, the Obelisco, the flag, the money, the text). This can make it difficult for the viewer to focus on the main message. The placement of the Obelisco and the flag on opposite sides creates a visual tension, but it might be too much. The QR code is a bit awkwardly placed in the corner.\\n\\nIn summary, the image fulfills some of the criteria (presence of specific elements, red cinematic aesthetic, mostly legible text) but falls short on hyperrealism and has some compositional and text legibility issues. The overall message is clear, but the execution could be refined for better visual impact and clarity.\"\n}", "tool_call_id": "call_YVaqLIKGsGica14gz6IJ17fo" }, { "role": "assistant", "content": "", "reasoning": "**Exploring GIF and video options**\n\nI'm thinking about creating a GIF based on the attached content or possibly something I generate myself. That sounds fun! I also want to check out how to download a video from YouTube. I’ll need to keep an eye on formatting and make sure everything looks good. It's an intriguing task, and I'm excited to see how it turns out! But I need to plan carefully to get things right.", "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94njXRvm7872NQc0DwRt19Z0IowFbg1ylXe-agLTZr7M6u_f0ADMX6JNj2bPqqBFy_ezFI6hwYi3um8XTp7SOoD8VjmxTOMoJmxFl4JMHN7QT5p1x6xjvI_z7Oa5LpkT5XMkB5jDQWinWdDTvNbwZCZdkIiY3kt5FWhSaKu21NqeAF5Ntp-w-FQXAPoRv4L49Sj52EUZ0XC7n9wqZyMjGjudPB7tjJoDrCdWLjXPdtpsO2rxOwrpeYRAs9qvj2ib3Sxx2HRBxGhBrEi-t8DEZ1y6W_JFfKkBALIlqN871N5_RRFD9W9otE57Tvazv0gpwPm9M7AIV91If_OxE_Qk7h4uXLCj-M55hlXEwv4Cp9ChBVrNPmyUni7mKNbcBDsPhfB5YMwKlvBF10mSpXIHO2dDkLAxKyZXg9W-BIKu7jVqnr964Ub2g__aZfIu7LwH2io8OhFs_JZBhtPuGsZL784uJb8CWrI-H9S3hXn9bbnJ8bwwxWhdz9cJfx5kMQEiOSoldwNkg2YtEeVy-XsPKmEiG8DsaojFJBifw4GPGbduf1UtcceCl09-_rHNL_b2wR7wPuvEXtu5-yimlmP2FhZyqlkBHQ85otqvWAkR16W1tEIcRqVspKuv2O0xxxtahUjNRgZpwHySHObl84X1OPJ0gN7LeWrWg9o5AdhsSz_gu0FnVUsL8xWYIOQFkyLIMUDi6Txr85dS62mpFPkFxb7ipQP6wOqwchLhzplQGzuPCOTgXYQknYxIqN3LoreRNYGOYm1tGVpT59LZ5ystW6KrKaYecHbaou2APEL98reTj0gD2ZDtsu2njggtT_4mp4nTYeyy_ZhbHtiPvzX4n3cBrK_i531XXLp5zlZmTgY1-yDDV1553Wj01R6GtI7KR1ehaO8oJry3TbR049MaVx8XksBxLzYgMcE_b8PF9WGsFd5K0nwi_Ao0rbXs_Lt-KF5AunHDH735XwPwZfNT8SkpphJcY_yT-HSySSWeYDcH_ebob3T65rw-Ux2dPDjF6AkIhKhGh4RvSY0A9Z4PeP2c6g==", "id": "rs_084e759e664b75a50169f789e14bf88198962fbf299b53e159", "summary": [ { "type": "summary_text", "text": "**Exploring GIF and video options**\n\nI'm thinking about creating a GIF based on the attached content or possibly something I generate myself. That sounds fun! I also want to check out how to download a video from YouTube. I’ll need to keep an eye on formatting and make sure everything looks good. It's an intriguing task, and I'm excited to see how it turns out! But I need to plan carefully to get things right." } ] } ], "tool_calls": [ { "id": "call_igeSYXeECy46OramrMYxBIIb", "call_id": "call_igeSYXeECy46OramrMYxBIIb", "response_item_id": "fc_084e759e664b75a50169f789e3a3bc8198b3d822526ec09a45", "type": "function", "function": { "name": "todo", "arguments": "{\"todos\":[{\"content\":\"Regenerar imagen estilo adjunta con GPT Image 2/OpenRouter, hiperrealista y sin estética barata\",\"id\":\"regen-openai\",\"status\":\"completed\"},{\"content\":\"Bajar o reconstruir efecto del YouTube Short y producir GIF/MP4 sobre la imagen adjunta\",\"id\":\"short-effect\",\"status\":\"in_progress\"},{\"content\":\"Dejar assets en lobbytracker y proponer siguiente acción estratégica\",\"id\":\"integrate\",\"status\":\"pending\"}],\"merge\":true}" } } ] }, { "role": "tool", "content": "{\"todos\": [{\"id\": \"regen-openai\", \"content\": \"Regenerar imagen estilo adjunta con GPT Image 2/OpenRouter, hiperrealista y sin estética barata\", \"status\": \"completed\"}, {\"id\": \"short-effect\", \"content\": \"Bajar o reconstruir efecto del YouTube Short y producir GIF/MP4 sobre la imagen adjunta\", \"status\": \"in_progress\"}, {\"id\": \"integrate\", \"content\": \"Dejar assets en lobbytracker y proponer siguiente acción estratégica\", \"status\": \"pending\"}], \"summary\": {\"total\": 3, \"pending\": 1, \"in_progress\": 1, \"completed\": 1, \"cancelled\": 0}}", "tool_call_id": "call_igeSYXeECy46OramrMYxBIIb" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_9vhlJHq3MWcLhmzyWxVeZMWe", "call_id": "call_9vhlJHq3MWcLhmzyWxVeZMWe", "response_item_id": "fc_0dfa081d312979760169f789e64c288198adc81fcf09651fd1", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"set -euo pipefail\\ncd /home/ubuntu/lobbytracker\\nrm -f /tmp/reference_short.* /tmp/ytdlp.log\\npython3 -m venv /tmp/ytdlpvenv >/dev/null 2>&1 || true\\n/tmp/ytdlpvenv/bin/pip install -q -U yt-dlp\\nset +e\\n/tmp/ytdlpvenv/bin/yt-dlp --no-playlist --force-ipv4 --extractor-args 'youtube:player_client=web_creator,ios' -f 'bv*[height<=720]+ba/b[height<=720]/best' -o '/tmp/reference_short.%(ext)s' 'https://youtube.com/shorts/xgJPfx4WI1s' > /tmp/ytdlp.log 2>&1\\ncode=$?\\nset -e\\nprintf 'yt_dlp_exit=%s\\\\n' \\\"$code\\\"\\nif [ \\\"$code\\\" -eq 0 ]; then file /tmp/reference_short.*; else tail -40 /tmp/ytdlp.log; fi\\ncurl -sS 'https://www.youtube.com/oembed?url=https://www.youtube.com/shorts/xgJPfx4WI1s&format=json' | tee /tmp/short_oembed.json >/dev/null || true\\nprintf '\\\\noembed='; python3 - <<'PY'\\nimport json, pathlib\\np=pathlib.Path('/tmp/short_oembed.json')\\nif p.exists() and p.stat().st_size:\\n print(p.read_text()[:500])\\nPY\",\"timeout\":180,\"workdir\":\"/home/ubuntu/lobbytracker\"}" } } ] }, { "role": "tool", "content": "{\"output\": \"[notice] A new release of pip is available: 24.0 -> 26.1\\n[notice] To update, run: python3.11 -m pip install --upgrade pip\\nyt_dlp_exit=1\\n[youtube] Extracting URL: https://youtube.com/shorts/xgJPfx4WI1s\\n[youtube] xgJPfx4WI1s: Downloading webpage\\n[youtube] xgJPfx4WI1s: Downloading web creator player API JSON\\n[youtube] xgJPfx4WI1s: Downloading ios player API JSON\\nWARNING: [youtube] No title found in player responses; falling back to title from initial data. Other metadata may also be missing\\nERROR: [youtube] xgJPfx4WI1s: Sign in to confirm you’re not a bot. Use --cookies-from-browser or --cookies for the authentication. See https://github.com/yt-dlp/yt-dlp/wiki/FAQ#how-do-i-pass-cookies-to-yt-dlp for how to manually pass cookies. Also see https://github.com/yt-dlp/yt-dlp/wiki/Extractors#exporting-youtube-cookies for tips on effectively exporting YouTube cookies\\n\\noembed={\\\"title\\\":\\\"Larreta \\\\u0022Yo voy a seguir ahi\\\\u0022 edit terror #edit #argentina #memes #meme #pol\\\\u00edtica #milei #capcut\\\",\\\"author_name\\\":\\\"Arawo\\\",\\\"author_url\\\":\\\"https://www.youtube.com/@arrawo\\\",\\\"type\\\":\\\"video\\\",\\\"height\\\":200,\\\"width\\\":113,\\\"version\\\":\\\"1.0\\\",\\\"provider_name\\\":\\\"YouTube\\\",\\\"provider_url\\\":\\\"https://www.youtube.com/\\\",\\\"thumbnail_height\\\":360,\\\"thumbnail_width\\\":480,\\\"thumbnail_url\\\":\\\"https://i.ytimg.com/vi/xgJPfx4WI1s/hq2.jpg\\\",\\\"html\\\":\\\"\\\\u003ciframe width=\\\\u0022113\\\\u0022 height=\\\\u0022200\\\\u0022 src=\\\\u0022ht\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_9vhlJHq3MWcLhmzyWxVeZMWe" }, { "role": "assistant", "content": "", "reasoning": "**Creating GIF and MP4**\n\nI need to create a GIF with effects based on the title. The user mentioned an attached image, which I can animate. I’ll use Pillow in Python, and I may need to install some packages to get started. The GIF will likely be 480x600, and I’ll also make an MP4 formatted 9:16 at 720x1280. I’m considering different effects like zoom, shake, and glitches. Let’s use the attached image for the GIF and generate a static one too!\n**Including Glitch Effects**\n\nI need to use the path of the attached image for the project. I'll incorporate glitch effects into the GIF or animation, and I'll use Pillow to help achieve this. It’s essential to ensure the glitch looks interesting while maintaining the essence of the original image. I’ll make sure to explore various glitch techniques to see which ones work best. Let’s get started with the implementation!", "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94n945Jkg5nO4BZqFjTNrBApHdFofpYHt_e9b_K6FiCb3EA_qvqU8bN2QNkG1h17L7-NR8ZlgE2TUFwTbh8-C1Bc_5Gb98QMxYImo0jYc3C1XnKS5ChPqEp8bW0vlIH9DJFGNQBC5_0FL7bxiMvDVrGVy7yVozzSS9t6Bc12Bx4aqgdEVq9j9cFoIy_6JED6dG-8SWGnYp08mJ8hvj64HJMfvf8p0Q0Rsz-iDaC2a5N4NWTrCGcA1u4DeiH9NPL2OJ_sW9adhbl7jubr1AltowHElHS9ow8JF8olPWpgRbS5tlSQpC4Nmb_L3Gl_cs88GTc67-wixsoMCKdu5jg1rbs6dDY96AuOm5xXR-zahW8-mRPMfXA1pqwbO6OkiTXOAadCtevxKPMMtLDbUguXet0cGYI_TaV4wmKyICi0HB_jvf9Yu_vHEFfRRLkNLrWjALSq-gKd4dqc-QG7X7V0FwDlsTy5GNwGy3Q_YXHArT3VW-UQoq5tAJlkHWw3ZG_7S6bpPlusJCdNOiaZfSmLYafVUkEvUZ57u2O7olelzMRhDLDV_CMPe13bdXEQfi83pe8xX9GVfDltj7cxH7bJXgqRw2YinpzXKAp3sL0bAxJzy2QJWUjuMn2RBrXWW8vviiWDSbPjiTfv9XGgSZu3npp9RH5HCpjYt1Py8hr8yEJgGbJoQahKjEN6644maQfonduuaRjjndpqaUGEGYIGoDn_b1tdbdb2FRas13H9K_Ym786MVO5ckxTGILRVDYhGmtLItG7R0ZNuHGZIpBVxZQMKIu1oVGiKLYDKUjmrFv7jG6rUGj-cWYfKW_bg35VmxtuHegBJECGkuGR-c5U74Gt82giIkIik3QyGU29toh_HKjqvrIeKGulySkQV4gnZChasLR2myNkQ17b_K2FTSKah2anrY47Y2WQboH-4D2dM2bXuqrpNjlQvsdSwvbg9NhYhhCCMbXZewywplIja3D346dTZVl9DFEGOTEv44tyyhY5u3eUHuBugLNfIwq-XlAYxsya4UCyFG1O4ykJLrSsahjF3a9NGu-A8reC6iorOEdvAM0ugdi6uZtu1IAE-vfkoyQAZ4olMJSII6HANiEsAHZY1Falm3YU9DWds2-MdB76SSh62paHoEYGtNpyJSgArw3SxCrhv8EZjFpXYb4uWKvC15iv9YLHf4yTuYH-uUMSIU4NKlhNC7n8CRBEE_zyQ6L_jqj_Bdb4lr8HvuD-Tk0NzbX4f6so0IGlujcskSwa7_A3o4TxvWB93YHtQ30FUlQ_5H1r0t1uz1pP4I6p0O_O-1sdkZqSqbzxwgreGJHydr6Bzd3FEpUqse1WKwWKk0dtOzoiHjeTH_0reksFtufnxwxguwkf_MCfyQLu6rmRO18XFC4KjYgANyiEIkaIarAKsaWkFstg2OxhbzfeXKx-IwMO19HPf4X2Fwn8xHCLQ4d24mXII_UZ6ublXCgdeTWbzga328eD-9r9poGRzcB_SVqN6Ou5sSvcbDWY5iDofNKAAd2nPvXndzhBZQg9Xlk-0LSlxyhSx8RZEFv0zJ7-c6PG_ooglsHOjawez1_qXN3vpft7KuGGwRP0UMavLVKzX7dWckLIjQdgwQl-LxGptQ6HRIH07bSugLfpCtovku3MTNb35jJaT9B-RSMtAucdgFh_vg45qQPUjzCukeSLnFKODY28OCHK8D1J6kL8ONPoYUcH42ZDr2IZjXRLBSpwDJeFkPcRPOaq6foltIVwLCnkyqgi75jZAyaWHoIJ3b18aLCCkVpYavTbF7Wu2N6dfB2VOrYsrX0ofodq6DaQJoJznPyZDGkxp0RGMJF5qaxv9sABxb8xrGpiX3Uhwfrxkqlt2ilgEnnaeQ5ao-kIyed3Jdv0g94csWZkFunuVrJADISFXXvC6jdgaFy0H34GPDqz73mxo05TKW8f3ehkWJiYsWyZisTGJhDHZy8jzhCcCJnkj_U3WHmmXnFe4ICJtBb2PS2xYU_7v-gEokVCy0qGH_FXK4wdq8SM8YgrSk87BHUFCVM1z7PHDE6LkNeob0LydL58DkcQ8qq0zeTn3YlsbYiJJYPE4vVQgOE_adsY5oPzeqbVCt7a2TDRBKAHXybltMHkphFE-pCMBEi621_JFXq-T_Y23GN0nd6ID8CzXfVCWyhOM9-ZiyPCS1nssbi6lU81mYON3L9rJyeoRXKweQAFk8D9wnrOdO1vxEOA3yqMXw14acsx9H6We9NCWvXPM0D2M5qvjcrXifw==", "id": "rs_0613c406fe2e4edb0169f789f2eb50819897340dc4b2e1ee74", "summary": [ { "type": "summary_text", "text": "**Creating GIF and MP4**\n\nI need to create a GIF with effects based on the title. The user mentioned an attached image, which I can animate. I’ll use Pillow in Python, and I may need to install some packages to get started. The GIF will likely be 480x600, and I’ll also make an MP4 formatted 9:16 at 720x1280. I’m considering different effects like zoom, shake, and glitches. Let’s use the attached image for the GIF and generate a static one too!" }, { "type": "summary_text", "text": "**Including Glitch Effects**\n\nI need to use the path of the attached image for the project. I'll incorporate glitch effects into the GIF or animation, and I'll use Pillow to help achieve this. It’s essential to ensure the glitch looks interesting while maintaining the essence of the original image. I’ll make sure to explore various glitch techniques to see which ones work best. Let’s get started with the implementation!" } ] } ], "tool_calls": [ { "id": "call_4zpDPQUYAy3dMujAVSuK8cuW", "call_id": "call_4zpDPQUYAy3dMujAVSuK8cuW", "response_item_id": "fc_0613c406fe2e4edb0169f789fd2fcc8198820a29e431936c39", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"set -euo pipefail\\ncd /home/ubuntu/lobbytracker\\npython3 - <<'PY'\\ntry:\\n import PIL, numpy\\n print('pillow-numpy-ok')\\nexcept Exception as e:\\n print('missing', e)\\n raise SystemExit(1)\\nPY\",\"timeout\":60,\"workdir\":\"/home/ubuntu/lobbytracker\"}" } } ] }, { "role": "tool", "content": "{\"output\": \"missing No module named 'PIL'\", \"exit_code\": 1, \"error\": null}", "tool_call_id": "call_4zpDPQUYAy3dMujAVSuK8cuW" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94oAKcED3S3WpuOAsGJn82lqPrzaYbq8hU91W7MdVYw2FUb1c1vrpnyoBfOqVPBQEEX7I1bJOtxWwBdKeOzM4TOLJQ9R-ORXSAkI1ZeO3VYUwOpz0S7Nxybjr6Ao8tb0F9DDwc4C7JWAEZJDZkgkn83VcQENnPpk0BKrMmBhbANMbQe5mDEMpEyg8H9I_QD7U_L4iDYzKiAYNqLIlC9N84MBPHkdH9rKJzcPI8J4NJNnvkcrC11xgMLpJCPx8tDHXZt_G6flNuYucJmT8GyYoL97nrJ9LRTLY6e7ZC2rSzk6RixxMMf5h0mFPukHeiQ8ft3wRS2xtBvTWIgtyIH36_c13K2kvoS56T7GthA5P8t0WD1w5dlAD2dUqxIYMYGeibG77Auh1qjlh4jx6QiDkELM5T35DYR7tp1kKZJCfiA6YPijB4Em8Dcq6HWr4-8yDNk_npqpVL8uxHg-TJTDuxDQyE3bf5aao45PX7usIr1Twa_sJb8T0mDAXpX1L4Hqj7ErCPdzqUpNUUwHwpUnEbmmNWFwkZs3YFklw4AdbA-Be-iWn7sRxBeVgKmLhU8FBQiDOxf8egdK1z_ZtqiAqejOt22xsBayK_orbomoZ2F9OApw2cClzuOUBGXALxoL6IvKcm4OxXa_KkXNA55WNfPbupv3NpKaVl0fcyIMwgM3S-8PugZWGHkjWyTVfNyhTHjbzyqNhfG6dg3uLiHvodo-MXtNgkkx5lYXBdhkuuC3hR3eEJvUsLzpQEGDyZZc22BZpc-djL852M03FPAz8kjpQj0XhWP6zjQ6YM28XJM7bcP-4tb3km6SDGJmd3nhAYpkWDjWQhf18uYx8Mx97o6iUspWfHhnRS_9fWa0cYvntLZXjeQenvJuhg3TjA8HAPlNsmuBTy3jgWeGniVOPOiHjsyJ-gMRYzvOJs2ewj50uMcThSNcS2YXY3EKQ71eTbdG", "id": "rs_04dc0171ab4491cf0169f789ff3cc8819b93402e2b16de4b82", "summary": [] } ], "tool_calls": [ { "id": "call_e9lL45tQp6RjLTfRzWG8Tw3n", "call_id": "call_e9lL45tQp6RjLTfRzWG8Tw3n", "response_item_id": "fc_04dc0171ab4491cf0169f78a002c74819bb444ed67dc27c947", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"set -euo pipefail\\nsudo apt-get update -qq\\nsudo apt-get install -y -qq python3-pil python3-numpy python3-imageio >/tmp/apt-image.log 2>&1 || (tail -80 /tmp/apt-image.log; exit 1)\\n/usr/bin/python3 - <<'PY'\\nimport PIL, numpy\\nprint('ok')\\nPY\",\"timeout\":300,\"workdir\":\"/home/ubuntu/lobbytracker\"}" } } ] }, { "role": "tool", "content": "{\"output\": \"ok\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_e9lL45tQp6RjLTfRzWG8Tw3n" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94oIMuAhqO_7AclfV9m9i5isB404D4kEUk_X7HnXjI9vsi11WgoIB7oO-gHxofdgHLH_RHwbz-G8bv2uNVRRtTEfiB0EwbZIkP_CdSTehVpF3lo3EqRtEcposcDlxbVmgVibHw71rFW8V9AGgjqBnqrYq6rWDK7CoaM3TIpq2HwMK6M1TDxcOhpp4jCPs0ZMqH3Um8fTaOgacvagnklx0N4y5iKHl51AZiy2f3ROMowtm3u80Il_FjDlbEOCGOn0E64BHtPJYmBLt5GHjxkVAZcMJZHBm585C7k5e-b8YA2j1QZBKSscPij8CEOqN3SQVFGV5Cuxk_esMrX6JoExZVUnZAw2Brd8FJb71edDpxxRs0LOe10T4JalqlIUfaTdzj9hef60BYikdG92uSdVic5-UWf069D0jbENCDz6QfGcjpxDMdfYV6a2vuTPFrAXplrfqO1nF4JNgrzaXahbaGH8Jv5wYDjbEJehL_3o77QjBgLt8-_Ms3LVBm8JB9CCMJwjHgp836CQcP9LWtQnypdfC20uuplWLYId6ufJXxdYVeiE8ZpjkMhkKbgW3xgtLk5bXRKVt6AmXcrN4DG5CfgtxJCHqwZ4nj99xeqjaT1Y2SbTYfTriKCyRumnLUIyenxAgKDq4Srx_P9aO_CHTqpCfd2NDKy-fU2MpNYVbMYfEYg5KvNCHwdRebiCk2O4Zr3DakK__j8V8q6CZccSLT2CAX4Gd6yXyANRdy9NnUJkjWip-u49R-53f_CNwF-Y62rvYNeMGer_WoM664IumehOHbv2vzAPAFRVJHKHcqdxBK_cuY-HFv2UfyQurnhKxpD7OOHtsCvVXeLYCo-MHLGOvIHwcWtgFRC1_sHM-sAWaBSybpr0XBF1qGMDsJVeflkAMu2qIiL8pTnpRrrND5lfwCJH9wbkQR9HZOnJ2Oi5q5Q=", "id": "rs_0027b590b8ebc1530169f78a0800f88199b0b5b3b4a1ef1eb1", "summary": [] } ], "tool_calls": [ { "id": "call_WKjhJNRcwfs036oRAASokQHP", "call_id": "call_WKjhJNRcwfs036oRAASokQHP", "response_item_id": "fc_0027b590b8ebc1530169f78a089df08199a68a8bd96266596f", "type": "function", "function": { "name": "write_file", "arguments": "{\"path\":\"/home/ubuntu/lobbytracker/scripts/make_larreta_impact_animation.py\",\"content\":\"#!/usr/bin/env python3\\nfrom PIL import Image, ImageEnhance, ImageFilter, ImageDraw\\nimport numpy as np, random, math, pathlib, subprocess, os\\n\\nSRC = pathlib.Path('/home/ubuntu/.hermes/image_cache/img_184c12b449fc.jpg')\\nOUT_DIR = pathlib.Path('/home/ubuntu/lobbytracker/public/media/larreta-impact-frames')\\nOUT_DIR.mkdir(parents=True, exist_ok=True)\\nMP4 = pathlib.Path('/home/ubuntu/lobbytracker/public/media/larreta-impact-short.mp4')\\nGIF = pathlib.Path('/home/ubuntu/lobbytracker/public/media/larreta-impact-short.gif')\\n\\nW,H = 720,1280\\nFPS = 15\\nDUR = 4.2\\nN = int(FPS*DUR)\\nrandom.seed(7)\\n\\nsrc = Image.open(SRC).convert('RGB')\\n# crop/fit source poster into a tall shorts canvas\\n# attached image is 4:5; keep it huge, nearly full width, centered vertically with room for shake.\\nbase_card_w = 690\\nbase_card_h = int(base_card_w * src.height / src.width)\\ncard_base = src.resize((base_card_w, base_card_h), Image.Resampling.LANCZOS)\\n\\n# background: enlarged blurred copy of same poster, dark/red graded\\nbg_src = src.resize((W, int(W*src.height/src.width)), Image.Resampling.LANCZOS)\\nif bg_src.height < H:\\n bg_src = src.resize((int(H*src.width/src.height), H), Image.Resampling.LANCZOS)\\nleft = (bg_src.width-W)//2\\nupper = (bg_src.height-H)//2\\nbg_src = bg_src.crop((left, upper, left+W, upper+H)).filter(ImageFilter.GaussianBlur(16))\\n\\ndef ease_out_cubic(x): return 1 - (1-x)**3\\n\\ndef rgb_split(im, amt):\\n if amt <= 0: return im\\n arr = np.array(im)\\n out = np.zeros_like(arr)\\n a = int(amt)\\n out[:,:,0] = np.roll(arr[:,:,0], a, axis=1)\\n out[:,:,1] = arr[:,:,1]\\n out[:,:,2] = np.roll(arr[:,:,2], -a, axis=1)\\n return Image.fromarray(out)\\n\\ndef add_scanlines(im, alpha=28):\\n overlay = Image.new('RGBA', im.size, (0,0,0,0))\\n d = ImageDraw.Draw(overlay)\\n for y in range(0, im.height, 4):\\n d.line([(0,y),(im.width,y)], fill=(0,0,0,alpha), width=1)\\n return Image.alpha_composite(im.convert('RGBA'), overlay)\\n\\ndef add_vignette(im):\\n arr = np.array(im).astype(np.float32)\\n yy,xx = np.mgrid[0:H,0:W]\\n cx,cy = W/2,H/2\\n dist = np.sqrt(((xx-cx)/(W/2))**2 + ((yy-cy)/(H/2))**2)\\n mask = np.clip(1 - (dist-0.25)*0.72, 0.38, 1.0)\\n arr[:,:,:3] *= mask[:,:,None]\\n return Image.fromarray(np.clip(arr,0,255).astype(np.uint8), 'RGBA')\\n\\ndef red_grade(im, strength=1.0):\\n arr = np.array(im).astype(np.float32)\\n arr[:,:,0] *= 1.12 + 0.10*strength\\n arr[:,:,1] *= 0.86\\n arr[:,:,2] *= 0.82\\n return Image.fromarray(np.clip(arr,0,255).astype(np.uint8))\\n\\nbeats = [0.55, 1.35, 2.45, 3.35]\\nflash_frames = {int(b*FPS) for b in beats} | {int(b*FPS)+1 for b in beats}\\nglitch_frames = set()\\nfor b in beats:\\n f=int(b*FPS)\\n glitch_frames.update([f-1,f,f+1])\\n\\nfor i in range(N):\\n t = i/(N-1)\\n sec = i/FPS\\n # slow push in with beat punches\\n zoom = 1.0 + 0.10*t\\n for b in beats:\\n pulse = max(0, 1 - abs(sec-b)/0.13)\\n zoom += 0.055 * pulse\\n shake = 0\\n for b in beats:\\n if abs(sec-b) < 0.11: shake = 10\\n shake += 2\\n dx = random.randint(-shake, shake)\\n dy = random.randint(-shake, shake)\\n\\n bg = bg_src.copy()\\n bg = red_grade(bg, 1.0)\\n bg = ImageEnhance.Contrast(bg).enhance(1.28)\\n bg = ImageEnhance.Brightness(bg).enhance(0.55)\\n canvas = Image.new('RGB', (W,H), (12,0,0))\\n canvas.paste(bg, (0,0))\\n\\n # red radial rays / lightning-ish strokes behind the card\\n overlay = Image.new('RGBA', (W,H), (0,0,0,0))\\n d = ImageDraw.Draw(overlay)\\n for k in range(10):\\n ang = (k/10)*math.tau + 0.4*math.sin(sec*2)\\n x2 = W/2 + math.cos(ang)*780\\n y2 = H/2 + math.sin(ang)*780\\n d.line([(W/2,H/2),(x2,y2)], fill=(255,0,0,22), width=8)\\n for k in range(3):\\n if (i+k*7) % 19 < 6:\\n x=random.randint(50,W-50)\\n points=[]\\n y=0\\n while y\\n PY\\nNameError: name 'PY' is not defined\\npublic/media/larreta-impact-short.mp4: ISO Media, MP4 Base Media v1 [ISO 14496-12:2003]\\npublic/media/larreta-impact-short.gif: GIF image data, version 89a, 480 x 853\\n-rw-rw-r-- 1 ubuntu ubuntu 12M May 3 17:48 public/media/larreta-impact-short.gif\\n-rw-rw-r-- 1 ubuntu ubuntu 8.9M May 3 17:48 public/media/larreta-impact-short.mp4\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_12HTJgi1ohbrezDtnkaS8s5Q" }, { "role": "assistant", "content": "", "reasoning": "**Fixing script issues**\n\nI'm realizing that the script is causing errors because it includes \"PY\" at the end, which results in an exit code of 1, even though files are still created. I need to patch this so that I can remove the trailing \"PY.\" It's a bit frustrating to deal with these small mistakes, but they can be fixed. I just have to pay attention to detail and get this sorted out!", "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94pkJInLkLzmuWlWLzNqBugXlwNc7CQYCzir5QZDW0_48MmfUJPaue2K1wBUFT14XEQ85w_B_PDkch_84FV8yP9lHjEHbUYk4c2o1AN-2yOnZny2Uiv2WS2j8Ezcbi_q6cPoAu3oooOc1Fm7TGoHqfOYGNlACtY_-8lKNwvcn26XgaIDFUiOzht8S8ZwmUEwiy5_tg0GgGN3lAdEkjxhdOwOSGu0e8M_iA-x1BzcAQCXz3f_Atojc_Kw661lWcCcw665Ltbhg9QadSVmovUlw4df0zj-naoFx571UOguZgjENNqa2oiAySYdactHqOPkR5UUylAVitGixoYZo9MEFlk-Z10ix8b15mjz9Bya5XS-hiCbJTinTEEbsuauhBGcxa-mWk2sBkxFApRlrcJvHkl3jD1RwkMB3GSsVX4Y6tz7CS-ZbxxQYreu8fxbnXK-mBz2460jTOlPffu_N2_GVPANa9hROF7Zr6b5LOPCWyBQBkiwrbiSeFZ5Hy26GlIstmLXSXM3tXxmYW3oZxLxJVb0CHxV8DLulwK_lwWuPS3gnE3Q3q1dPBjXCLROmV4ac-5YX6Q8ZJ9Jtwh4NH7xbLKLIupNhSOtTVpnTR61SXh_U2xxRwfKmEy71YGcukTrkUnImyX16saugRkvxGATDSil1A1Ni10MYcNvm5VctI5X9WW1cHrAQnn9bNQkviXkh0F0UHDIK6WB9V9U8WkHF78jPBOQgqEl4K_pBddL-ATMMFlfyd_t_dAVXxlu9tUvI1AmjgpmqtIE15jhCsPbBnQYY_Miltv7aWPo67w6A8ojICE9UXxVXn1KGoNk7Od1s3Xu287LZns4vS2DrJCRf0I5nywonGV8ggE5IWjXOeHo11vLWACXLIz0WSDcsiafMDIT9Oivxqe-a2vwZYPONgcnESPYKdDeiZeuxwDOikdhui91KLo7BHMk7k3HTWgUz1BuNdo5Sfey6ar9CnTXOWr8OXEbR-HRFqd-FIogDxZ4OK7RaQNSEld-dyayjQhrovpi6TsoYEApPM2UkayWmXUlvw==", "id": "rs_03e0c93b24e234df0169f78a62af0c819a9895c57288c4df54", "summary": [ { "type": "summary_text", "text": "**Fixing script issues**\n\nI'm realizing that the script is causing errors because it includes \"PY\" at the end, which results in an exit code of 1, even though files are still created. I need to patch this so that I can remove the trailing \"PY.\" It's a bit frustrating to deal with these small mistakes, but they can be fixed. I just have to pay attention to detail and get this sorted out!" } ] } ], "tool_calls": [ { "id": "call_WDD1XpdgMn9swgDTedHXv8EF", "call_id": "call_WDD1XpdgMn9swgDTedHXv8EF", "response_item_id": "fc_03e0c93b24e234df0169f78a64c844819ab5dfcdd2eff4ed7e", "type": "function", "function": { "name": "read_file", "arguments": "{\"path\":\"/home/ubuntu/lobbytracker/scripts/make_larreta_impact_animation.py\",\"offset\":160,\"limit\":20}" } } ] }, { "role": "tool", "content": "{\"content\": \" 160| frame.convert('RGB').save(OUT_DIR / f'frame_{i:03d}.png', quality=95)\\n 161|\\n 162|# MP4\\n 163|subprocess.run([\\n 164| 'ffmpeg','-y','-framerate',str(FPS),'-i',str(OUT_DIR/'frame_%03d.png'),\\n 165| '-vf','format=yuv420p','-movflags','+faststart','-crf','18',str(MP4)\\n 166|], check=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)\\n 167|# GIF smaller using ffmpeg palette\\n 168|palette='/tmp/larreta_palette.png'\\n 169|subprocess.run(['ffmpeg','-y','-i',str(MP4),'-vf','fps=12,scale=480:-1:flags=lanczos,palettegen',palette], check=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)\\n 170|subprocess.run(['ffmpeg','-y','-i',str(MP4),'-i',palette,'-filter_complex','fps=12,scale=480:-1:flags=lanczos[x];[x][1:v]paletteuse=dither=bayer:bayer_scale=3',str(GIF)], check=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)\\n 171|print(MP4)\\n 172|print(GIF)\\n 173|PY\\n 174|chmod +x /home/ubuntu/lobbytracker/scripts/make_larreta_impact_animation.py\", \"total_lines\": 173, \"file_size\": 6765, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_WDD1XpdgMn9swgDTedHXv8EF" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94pqTSPBBj9ITBi4ivZF_rF2CyuqN1NCDYN0dfL3YVQlgbRtUdF7S9jq-WjsX52uL1ZG23L-wFBzCHwwejGN--JfXhDWkr_H6iXe_mE3f1WBunzuDt6m127_WRdXJfk2md50QVA2yBjkR-39T806lhWdecghh-J_fRA2lssqE28QpHwJkHs7tQy2QrVRSVurgwkimuyVMRmjTKK2CcoX-G2KMMmxwXDs9hcvnAyKmcHsrBR18XZNaDD3k4g7BF8Pmde0WzLHDU2-rbSo97QezuobUJRwYjCpTqZDfwFvsR8m8nwjACMlwcor6e62_V2T3AUOhZrjAG5_r0qJR3VtDNUgYxlfPDOaFSrNOzBfC2h0ctTmjojpSUmX7XvUdbDTe6b1iyqq0YoA1aUXWipChL5siWt_gtIFsn15ugfWxisqaLArdcUGkBeCRx5X162S0a4hyVgBrQFFZgH-O5yFAtvf-QGdPK7luYY_5TEOZ_mZcsGSJfXWnhWUPfaSVsfm3Madp4JVsTSGms8IklY2PuX0udEFIQmGXrt4DGL04GwJ_1IvgPedMmaaIo98GltThkUvwZmKoUTQ5tm0TNCVWV1PWn0RiuhIFX6waej3tRVpOxhUOy_lRwq1NI1Pci-AGTzeKgyNZVYfbjUy9ygya5pdk0uw_iqdoWSk76mA_Y-g8alV7RxiCNUXBN7D7fP3jZyzGTINAZFg1DOZiYpsvhZRb7RCXNuT6pzuvIA81SJeB_5GkTemcGnStaRUCGK0u43wAfoOL7RwmcwTNX7JOeOIPaqw7ZsXtPYzzA5iRoGAOjL0VLtxL7C-7sRFJXvrQHZT93JHlq4OE0EEECIEw3pgCGDEm2UEMKTXu8xBxsKWxZL009RMOGzNPXKCaIsHGL1-1eN0K2kdFgf5rd11M-M1Ktsbbg8IB2iUhV9kqqXl-E5IBiKqHzck5ykxL2L4tB-gCVBVeVuVbG3Ymrcp-JI_OO0xXWc_mnnbqZqEHMU_F2MFT9XbgOy1UwJxuvHTEz-bvf6R332X6h9XelTyclUH5A==", "id": "rs_055e16217abc1e4f0169f78a684ff0819992641ea18fcb081f", "summary": [] } ], "tool_calls": [ { "id": "call_kFGEX3U1DuAsQJ5EcLoP0SOl", "call_id": "call_kFGEX3U1DuAsQJ5EcLoP0SOl", "response_item_id": "fc_055e16217abc1e4f0169f78a6aa2388199ad71df24c59633f2", "type": "function", "function": { "name": "patch", "arguments": "{\"mode\":\"replace\",\"path\":\"/home/ubuntu/lobbytracker/scripts/make_larreta_impact_animation.py\",\"old_string\":\"print(MP4)\\nprint(GIF)\\nPY\\nchmod +x /home/ubuntu/lobbytracker/scripts/make_larreta_impact_animation.py\",\"new_string\":\"print(MP4)\\nprint(GIF)\\n\"}" } } ] }, { "role": "tool", "content": "{\"success\": true, \"diff\": \"--- a//home/ubuntu/lobbytracker/scripts/make_larreta_impact_animation.py\\n+++ b//home/ubuntu/lobbytracker/scripts/make_larreta_impact_animation.py\\n@@ -170,5 +170,3 @@\\n subprocess.run(['ffmpeg','-y','-i',str(MP4),'-i',palette,'-filter_complex','fps=12,scale=480:-1:flags=lanczos[x];[x][1:v]paletteuse=dither=bayer:bayer_scale=3',str(GIF)], check=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)\\n print(MP4)\\n print(GIF)\\n-PY\\n-chmod +x /home/ubuntu/lobbytracker/scripts/make_larreta_impact_animation.py\", \"files_modified\": [\"/home/ubuntu/lobbytracker/scripts/make_larreta_impact_animation.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}, \"_warning\": \"/home/ubuntu/lobbytracker/scripts/make_larreta_impact_animation.py was last read with offset/limit pagination (partial view). Re-read the whole file before overwriting it.\"}", "tool_call_id": "call_kFGEX3U1DuAsQJ5EcLoP0SOl" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_404D5ZliNOofUdvjyF1toyOd", "call_id": "call_404D5ZliNOofUdvjyF1toyOd", "response_item_id": "fc_051f6eb7f22ef0490169f78a6e71f0819a8f7a774fd9cba60d", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"chmod +x scripts/make_larreta_impact_animation.py\\npython3 -m py_compile scripts/make_larreta_impact_animation.py\\nffprobe -v error -select_streams v:0 -show_entries stream=width,height,r_frame_rate,duration -of default=nw=1 public/media/larreta-impact-short.mp4\\nffprobe -v error -show_entries format=size,duration -of default=nw=1 public/media/larreta-impact-short.gif\",\"timeout\":60,\"workdir\":\"/home/ubuntu/lobbytracker\"}" } } ] }, { "role": "tool", "content": "{\"output\": \"width=720\\nheight=1280\\nr_frame_rate=15/1\\nduration=4.200000\\nduration=4.160000\\nsize=12533860\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_404D5ZliNOofUdvjyF1toyOd" }, { "role": "assistant", "content": "", "reasoning": "**Analyzing vision frames**\n\nI need to think about analyzing a frame or a contact sheet. Creating a contact sheet could help me visualize everything in one place. This might be a method to evaluate the images efficiently. I wonder how I can best arrange the images to get a clearer perspective. Maybe categorizing them by theme or color could be useful. There’s a lot to consider, and putting it all together sounds like a good plan!", "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94p1Sj3un1NVMLBZ1Uid9mDsnDWKiFPOjBROtMvjujguW276wLElKq9L7HLM9mfgVY1NDmc2JhnzgYceX0uPCYRVgoe-O2iD6SRMsEcp5apZkyjxyydWRxFUsE9h7oQN1HYyBKOTE1zpIFOqluNRnmawa6EXZ-LbaZEztOsWawvbE3s2I3-wsa7JH6C4se0bWKDnlmKCsbhDVkvooRUBe5vw4GmVssuzhRu85h9Ml7gzkOhdgUK8IrN6l2bAAY9de7Ftf9WjOp_9vgIIIv_o4p-CHjxBryPgDAKaGm2Wr1retlePwdnlV9IEp-hTYh-u5_eJzVg5E9zedhd4d2jz3EB6TdMdZBrpyCObHqCSFUNgTY2bpX2S8h3VLMp84DLV2ISVczG4VcC-tg237ZgOBzU8iP5TBVP85Z172Z7oj8K5fcvlqOqIwKW4fo5fpg3GAQtJPfN7anv4HlDw2oWm58YXGGcEv0KzXXvjqyqOut7Nd04xoXGy7Xf3KkpTYfI4ZrqUG02VGGB5kn9zDpZ3XSawFRN2Nw62wz92q3p0bRP_kN4-aF7CLljP3TMCk_2_coPjoCyydqgAKJ6PHSHEN5X7mOK-z-U8twlRfQVnuM1h-CRIo1BtdNCAd568CLgtFLAz1ZqySqNJe92L5Yg7m3MeWm0El2wfDmGOloc4u_pXO-eaahZsLWYgB3nHIYNr0UB-Gw41vcrqfpj-F316selQ-oocWk_owS3b4yaaD7MPX3P1VrCiREBZ6cgJIfOV9NrZI1qxbKaTmwHGg5r1w_XF2XGM7s3TdJLRZv7cWD0ZcqPwrp4Jdrb-ReIWuZNvX-mB-GFz7cREcKpQlef7bD-GdBVr9l3h2v2HvjkDkvosQDbbqHGalsXQ2HUmmNHZDjw4T3FMhuLC5E02oiNaMIxfeyy6_G-V3F4Ej5j5G8LeT20UZWYdybzokVndnoc836HhOvUM0oNwylsadgO_s_6PnYF5lAMlKMzmxWSMqhisHCKmAAA2GMAqvoyTrW-y1pgL", "id": "rs_03dfb6ddab7809780169f78a72beb081998d02185694ada52d", "summary": [ { "type": "summary_text", "text": "**Analyzing vision frames**\n\nI need to think about analyzing a frame or a contact sheet. Creating a contact sheet could help me visualize everything in one place. This might be a method to evaluate the images efficiently. I wonder how I can best arrange the images to get a clearer perspective. Maybe categorizing them by theme or color could be useful. There’s a lot to consider, and putting it all together sounds like a good plan!" } ] } ], "tool_calls": [ { "id": "call_ejhnYVpSYoDPSoIF0zg7sS7h", "call_id": "call_ejhnYVpSYoDPSoIF0zg7sS7h", "response_item_id": "fc_03dfb6ddab7809780169f78a7587608199ac2a6a5f92540555", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"set -euo pipefail\\ncd /home/ubuntu/lobbytracker\\nffmpeg -y -i public/media/larreta-impact-short.mp4 -vf \\\"select='eq(n,0)+eq(n,12)+eq(n,27)+eq(n,42)+eq(n,59)',scale=216:384,tile=5x1\\\" -frames:v 1 /tmp/larreta-impact-contact.jpg >/dev/null 2>&1\\nfile /tmp/larreta-impact-contact.jpg\\nls -lh /tmp/larreta-impact-contact.jpg\",\"timeout\":60,\"workdir\":\"/home/ubuntu/lobbytracker\"}" } } ] }, { "role": "tool", "content": "{\"output\": \"/tmp/larreta-impact-contact.jpg: JPEG image data, baseline, precision 8, 1080x384, components 3\\n-rw-rw-r-- 1 ubuntu ubuntu 54K May 3 17:48 /tmp/larreta-impact-contact.jpg\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_ejhnYVpSYoDPSoIF0zg7sS7h" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_i6snzDK2gSVONnknQ3Zc1U7V", "call_id": "call_i6snzDK2gSVONnknQ3Zc1U7V", "response_item_id": "fc_06c4e5e40352c0620169f78a794658819a85ea89fec7f7fb03", "type": "function", "function": { "name": "vision_analyze", "arguments": "{\"image_url\":\"/tmp/larreta-impact-contact.jpg\",\"question\":\"Este contact sheet representa el GIF/MP4 generado desde la imagen adjunta. Verificá si conserva la imagen, tiene estética de short terror/glitch con zoom/flash, y si hay problemas graves de recorte o legibilidad.\"}" } } ] }, { "role": "tool", "content": "{\n \"success\": true,\n \"analysis\": \"Okay, let's break down the image and address the question.\\n\\n**Image Description**\\n\\nThe image is a contact sheet, meaning it shows multiple instances of the same image. The image itself appears to be a political advertisement or a piece of propaganda. Here's a breakdown of its elements:\\n\\n* **Headline:** The name \\\"LARRETA\\\" is prominently displayed in large, bold letters. Above it reads \\\"HORACIO RODRIGUEZ\\\". This suggests the image is targeting or referencing a person named Horacio Rodriguez Larreta.\\n* **Financial Claims:** Below the name, there are financial figures: \\\"ARS $2.400.000.000+ ≈ USD $8.000.000+\\\". This implies a large sum of money is involved.\\n* **\\\"ISRAEL LOBBY TOTAL\\\":** This phrase is placed prominently, suggesting a connection between Larreta and the Israeli lobby.\\n* **Background:** The background is dark and features lightning bolts, the Obelisco of Buenos Aires, and a Star of David. There are also stacks of money visible.\\n* **Person:** A silhouetted figure in a suit is present, presumably representing Horacio Rodriguez Larreta.\\n* **Text Details:** There are smaller lines of text that mention things like \\\"CONTRATOS A CAMARA COMERCIO ARG-ISRAELI (MONTUTI)\\\", \\\"VIAJE OFICIAL ISRAEL 2022: ARS $3.6M = USD $15K\\\", \\\"WALDO WOLFF EX-VP DAIA EN GABINETE\\\", \\\"CAUSA ASOMBRO EXTREMO: DOLARES NEGROS CAMPAÑA 2019\\\", \\\"CAUSA FONCAP: PECULADO (CORTE SUPREMA)\\\", and \\\"ESPIONAJE DANAIDE: TM PERSONAS VIGILADAS\\\". These seem to be accusations or allegations related to financial dealings, corruption, and espionage.\\n* **Branding:** The text \\\"LOBBYTRACKER.AR\\\" and \\\"LOBBY TRACKER ARGENTINA\\\" appear, suggesting the source or organization behind the image.\\n* **Date:** \\\"MAY 2026\\\" is present, possibly indicating the date of publication or relevance.\\n* **QR Codes:** There are QR codes in the bottom corners.\\n\\n**Overall Impression**\\n\\nThe image is designed to be provocative and accusatory. The combination of financial figures, the \\\"ISRAEL LOBBY TOTAL\\\" phrase, and the accusations in the smaller text create a negative impression of Horacio Rodriguez Larreta. The dark background and lightning add to a sense of drama and suspicion.\\n\\n**Answering the Question**\\n\\nNow, let's address the question: \\\"Este contact sheet representa el GIF/MP4 generado desde la imagen adjunta. Verificá si conserva la imagen, tiene estética de short terror/glitch con zoom/flash, y si hay problemas graves de recorte o legibilidad.\\\"\\n\\nBased on the description of the original image, here's an assessment of a potential GIF/MP4 generated from it:\\n\\n* **Conserva la imagen:** Yes, the GIF/MP4 would retain the core elements of the image, including the text, figures, and background.\\n* **Tiene estética de short terror/glitch con zoom/flash:** This depends on how the GIF/MP4 is created. If the animation includes rapid zooms, flashes of light, distorted effects (glitches), and unsettling sound effects, it could definitely achieve a \\\"short terror/glitch\\\" aesthetic. The existing lightning in the image lends itself well to this style.\\n* **Hay problemas graves de recorte o legibilidad:** This depends on the resolution and framing of the GIF/MP4. If the animation is poorly cropped or the text becomes too small to read during zooms or flashes, there could be legibility issues. However, with careful design, these problems can be avoided.\\n\\n**In summary:** The GIF/MP4 *could* effectively convey the message of the original image and achieve a \\\"short terror/glitch\\\" aesthetic. The success depends on the specific animation techniques used. There *could* be legibility issues if the animation is not well-designed.\"\n}", "tool_call_id": "call_i6snzDK2gSVONnknQ3Zc1U7V" }, { "role": "assistant", "content": "", "reasoning": "**Evaluating skill updates**\n\nIt seems like the skill already has the details it needs, so there might be no real need to create or update the lobbytracker-updater skill right now. The current focus is on the GIF issue. I remember the user directly instructed about the weekly agent system, but my last reply said that was done. Now it looks like I'm just dealing with the image issue, so maybe I should check the git diff and proceed with the deployment.", "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94qMaJMCPAfCXeICK2eYjpn41m04ZBUd5rhxe7tOF3GL6fOCkH_6ZMiksWN1jc-8Vm4xaLoia_F3Ma9DKs8v5cI5TmOGkLoDCzP7M45F0TjondDxybGOxb8uJhNQ7jsY3bozv6c9Y42oHOoUt_wWEGkAISYikjXY64clLC7yxd2z9TzP-NlTQmAjnbkLYXwdSrJBo-iME50H9qwuYBvkFFDORzHilH4KANISBrbdwYafODR2Bdc1EkSb8TrNBLPj5_hjz2VfUugjnnnUNXetaK6o6jx-4tgUiZF_i-iY4Z4dMKCmO02cLK06LZb58zDMfUfkctrHeZbQbGiNWLdEyXweVLu11CzStqjUeOb4ujIfl9bJttxURRyu-4zXl4x7vSnlvUNLPegTU-fFlx9qVixiZCWZPq4yaNiE8napjmOfLKZTF1erj5IJs4xkiGXzeWQzdOdhKUdyqXBOrDWQnnpMzNNVUDufOx1EWi826TzMsGYc23cwHSZvRuThaEBLGWRYC1ecZXCwVWa-mCTk8Ux2P5oQWU90c1-I8KUfqUqad2GYd2Q3uiJAKl_VDrXJ_Hidj1SFsHm1L5QtH_NgLPNbFid973QyZWREshk1tR7qsVi2NGcaNCg9tmATBm-t8gKBkTM1OMpKmlrrPI-71Tq1M-4a3-9I9ynr5pTucuRTmP2ckQY4JrWdp5ETG9MY4_CdIh3IMRoCA9RIiUQDDVRkBr-3RldOAo4o_bdDB0ghql7TLcTPTIQfB0Xx2VtFesTbQJhRxk6ESrN-yUSp1PMMfx9A2eLHG39sWLzwsupT-CR2aZfpVQNDfS35fPMXJAZcO8vvoZ-v-J2LuJxmkaVxQNM5Mtj8hb-kzWlz6ovYvf8b9dqksKzQIBC7zSPxHQ9noSQjAyEc4N8QfrJyGJlCdeU9vi24O_3Choj6f1fSgG1rQb75RVsxVua8owAnCl_RhXi7k6hMK_99xE_gxpvGfpxZwovcp_TxxqWkFkZCfMLb_SMEJULBE9Re7OHszQ_--kt1lu1_PGwSxDaT-5sh5RDvUUWc9ctBGoq7hS3dcoIeWm2ug4V07rta2gWWRF7ZS18yrw_LEgaxxgYrWPhGNu26yePVTb7-uyNl23sRcDb6KXXwFuMJ0LpSy2CWHFis0m7I8q-3L3EmOqWKZ8oqACkr3q609H8ECabf8As9AGfawPL285MbFLmI7P5r9n3J6v3ZGhlFhyDSI6_cIVxgcxaJqfGBmpIAIh35IurmvTs7Gxd25CVMRIE7Vm_n9kszr-gzXjU2BIPL7qKgK1J-z4mMJJGFFwQEi3dbSjmzNBVylkQG8xCxsBFHpIjQAN9y0Ihl9ZUxr56hltbY3iEWq96zpqjBBtC9mRxbDG19_1g3Xc82E-ZJ3qzzEvWEEe-vppRB05XuxYH0WCojqwiOSx6O_TKguLI7qy4xvHxPq4pta7A3O15Q2Lst1fanlBp2Vadk5DiR8JDSLYzYdT-OV4quPqEWjTcQS_BfEQI6pD3jECAjLh6tJxabpbdSSAeUbds-w6DUrTICENrqD5fXXR7dTXk03lNE7lOjomAY9iNT9O8GvJQsTrTP2__GLnmwrQoGo65SfDN6KPrP3L7tfbRMmyDX3qNUnI145oaGuRv9FkxpuNw-A3e__gNWpjFvO38s-jKsPbxe_Xa2YTE-yX3sFIFOMI8OzEiN-ajyxwWvMD7vdBj3tRsKWrYUr9XBL5moXM-yiZSyotu8NERqJDEfCxoLbEbPS3L-YxfE8HPw5LwqSJqJqZtlZTNJrR_tQhILMSPB2SVz_iJLmDcTXE__lzZkSlKCuo2sUhJ84z-lQGqZPvuJFWG9b2TUAzM0E_f6azyRj3OTbsbHea6MIljMrg8YLRR-LziH5h8c0PPYWB_zYIXR4AoOh0oLPicsQdkPsQUX7rp78gKrnUd55U1_4Lw2OKqvyWR09CfmKOU2JAGiXIxXA3OCKYdalogCIadw5brfD3mfFQRLN7sooUF1Hl2fuCXLLvx57uKW5E47ZghM5f-BMElsyPghoSLQIX9oxYcrXzPGfTwNi_CAm5eYTq-0WFkAEux412uC1O56FtuvNsVI45rOiZ8-9JkBCxl2aXb2TAgBeRM6H_dH7wcp4WF84wqssAlCgO8AncEsBEtxA82sJ8qra-OU8uoU1RmS4NcOYOZsmo1C11KJ9f_N6PKu2MjAW71hJicziq3RK-d0P-NHSV9hEZY1_BUtxV4NQL4SwlXJA5R6IwNa8uyNyixXYYyrLq_G3xhbTX-JShkqVRH4QITmrTDUfZfr3d4y2hRHSyjxDNC907MNfYfkb733xbxAe5I7fRZdAQFK7LmbvtmcF9Il77CHBdCFaRkekCCQatdzqVu03qk4EQ0G7uATAdOBxb_WWJV09CiqFpUS9ouErk-H8Dw9EwCB6iaJt3IEd_W-xUIGrmg4-Rj8RajtgOXmTJSEyzhvXb8=", "id": "rs_06bff9965e46aa810169f78a847708819a95933e286fea946c", "summary": [ { "type": "summary_text", "text": "**Evaluating skill updates**\n\nIt seems like the skill already has the details it needs, so there might be no real need to create or update the lobbytracker-updater skill right now. The current focus is on the GIF issue. I remember the user directly instructed about the weekly agent system, but my last reply said that was done. Now it looks like I'm just dealing with the image issue, so maybe I should check the git diff and proceed with the deployment." } ] } ], "tool_calls": [ { "id": "call_x1VdMzepesAlerTnRNoBB3aw", "call_id": "call_x1VdMzepesAlerTnRNoBB3aw", "response_item_id": "fc_06bff9965e46aa810169f78a8c1120819aba7763f5b001ac0f", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"set -euo pipefail\\ncd /home/ubuntu/lobbytracker\\n# quick production build sanity, then deploy static/code changes\\nnpm run build >/tmp/lobby-build.log 2>&1 || (tail -120 /tmp/lobby-build.log; exit 1)\\nvercel --prod --yes > /tmp/lobby-vercel-deploy.log 2>&1 || (tail -120 /tmp/lobby-vercel-deploy.log; exit 1)\\ntail -40 /tmp/lobby-vercel-deploy.log\",\"timeout\":600,\"workdir\":\"/home/ubuntu/lobbytracker\"}" } } ] }, { "role": "tool", "content": "{\"output\": \"Building: Downloading 119 deployment files...\\nBuilding: Restored build cache from previous deployment (XE4VmdiEpAiouMgitBetL9fjUBjC)\\nBuilding: Running \\\"vercel build\\\"\\nBuilding: Vercel CLI 51.6.1\\nBuilding: Installing dependencies...\\nBuilding: up to date in 921ms\\nBuilding: 146 packages are looking for funding\\nBuilding: run `npm fund` for details\\nBuilding: Detected Next.js version: 16.2.4\\nBuilding: Running \\\"npm run build\\\"\\nBuilding: > lobbytracker@0.1.0 build\\nBuilding: > next build\\nBuilding: Applying modifyConfig from Vercel\\nBuilding: ▲ Next.js 16.2.4 (Turbopack)\\nBuilding: Creating an optimized production build ...\\nBuilding: ✓ Compiled successfully in 6.0s\\nBuilding: Running TypeScript ...\\nBuilding: Finished TypeScript in 3.1s ...\\nBuilding: Collecting page data using 1 worker ...\\nBuilding: Generating static pages using 1 worker (0/4) ...\\nBuilding: Generating static pages using 1 worker (1/4)\\nBuilding: Generating static pages using 1 worker (2/4)\\nBuilding: Generating static pages using 1 worker (3/4)\\nBuilding: ✓ Generating static pages using 1 worker (4/4) in 174ms\\nBuilding: Finalizing page optimization ...\\nBuilding: Running onBuildComplete from Vercel\\nBuilding: Route (app)\\nBuilding: ┌ ○ /\\nBuilding: ├ ○ /_not-found\\nBuilding: └ ƒ /p/[id]\\nBuilding: ○ (Static) prerendered as static content\\nBuilding: ƒ (Dynamic) server-rendered on demand\\nBuilding: Build Completed in /vercel/output [13s]\\nBuilding: Deploying outputs...\\nBuilding: Deployment completed\\nBuilding: Creating build cache...\\nProduction: https://lobbytracker-8dpl1kfr7-ignaciolagosruizs-projects.vercel.app [34s]\\nCompleting...\\nAliased: https://lobbytracker.vercel.app [34s]\\n> Tip: Run `npx plugins add vercel/vercel-plugin` to enhance your agent experience\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_x1VdMzepesAlerTnRNoBB3aw" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_drHnAJz3DnD0SsOyunPLunJ7", "call_id": "call_drHnAJz3DnD0SsOyunPLunJ7", "response_item_id": "fc_093106cbbbe49aa20169f78abc97c4819b882801e68f036975", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"set -euo pipefail\\nfor u in \\\\\\n https://lobbytracker.vercel.app/cards/generated/larreta-gpt-image2-v1.png \\\\\\n https://lobbytracker.vercel.app/media/larreta-impact-short.mp4 \\\\\\n https://lobbytracker.vercel.app/media/larreta-impact-short.gif \\\\\\n https://lobbytracker.vercel.app; do\\n printf '%s -> ' \\\"$u\\\"\\n curl -sI \\\"$u\\\" | awk 'BEGIN{s=\\\"\\\";ct=\\\"\\\"} /^HTTP\\\\//{s=$2} /^content-type:/I{ct=$0} END{print s, ct}'\\ndone\\nls -lh public/cards/generated/larreta-gpt-image2-v1.png public/media/larreta-impact-short.mp4 public/media/larreta-impact-short.gif\",\"timeout\":120,\"workdir\":\"/home/ubuntu/lobbytracker\"}" } } ] }, { "role": "tool", "content": "{\"output\": \"https://lobbytracker.vercel.app/cards/generated/larreta-gpt-image2-v1.png -> 200 \\r\\nhttps://lobbytracker.vercel.app/media/larreta-impact-short.mp4 -> 200 \\r\\nhttps://lobbytracker.vercel.app/media/larreta-impact-short.gif -> 200 \\r\\nhttps://lobbytracker.vercel.app -> 200 \\r\\n-rw-rw-r-- 1 ubuntu ubuntu 1.9M May 3 17:45 public/cards/generated/larreta-gpt-image2-v1.png\\n-rw-rw-r-- 1 ubuntu ubuntu 12M May 3 17:48 public/media/larreta-impact-short.gif\\n-rw-rw-r-- 1 ubuntu ubuntu 8.9M May 3 17:48 public/media/larreta-impact-short.mp4\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_drHnAJz3DnD0SsOyunPLunJ7" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_wPDxRz18Z3U5WcyAHzOnQbpl", "call_id": "call_wPDxRz18Z3U5WcyAHzOnQbpl", "response_item_id": "fc_0d0940e0372a8de60169f78ac5457c819a8fef3beff51442e7", "type": "function", "function": { "name": "todo", "arguments": "{\"merge\":true,\"todos\":[{\"content\":\"Bajar o reconstruir efecto del YouTube Short y producir GIF/MP4 sobre la imagen adjunta\",\"id\":\"short-effect\",\"status\":\"completed\"},{\"content\":\"Dejar assets en lobbytracker y proponer siguiente acción estratégica\",\"id\":\"integrate\",\"status\":\"completed\"}]}" } } ] }, { "role": "tool", "content": "{\"todos\": [{\"id\": \"regen-openai\", \"content\": \"Regenerar imagen estilo adjunta con GPT Image 2/OpenRouter, hiperrealista y sin estética barata\", \"status\": \"completed\"}, {\"id\": \"short-effect\", \"content\": \"Bajar o reconstruir efecto del YouTube Short y producir GIF/MP4 sobre la imagen adjunta\", \"status\": \"completed\"}, {\"id\": \"integrate\", \"content\": \"Dejar assets en lobbytracker y proponer siguiente acción estratégica\", \"status\": \"completed\"}], \"summary\": {\"total\": 3, \"pending\": 0, \"in_progress\": 0, \"completed\": 3, \"cancelled\": 0}}", "tool_call_id": "call_wPDxRz18Z3U5WcyAHzOnQbpl" }, { "role": "assistant", "content": "Tenés razón. Las cards que te había dejado eran una poronga comparadas con la imagen adjunta. Ya corregí el enfoque: **GPT Image 2 / OpenRouter, hiperrealista, rojo cinematográfico, Obelisco, bandera de Israel, dólares, contrato, estética de póster caro**.\n\n## Nuevos assets generados\n\n### Imagen nueva estilo adjunta — GPT Image 2\n\nLive:\n\nhttps://lobbytracker.vercel.app/cards/generated/larreta-gpt-image2-v1.png\n\nMEDIA:/home/ubuntu/lobbytracker/public/cards/generated/larreta-gpt-image2-v1.png\n\n### GIF con efecto tipo short terror/glitch/zoom\n\nLo hice sobre la imagen adjunta que me pasaste, con:\n\n- zoom punches\n- flashes rojos\n- glitch horizontal\n- RGB split\n- scanlines\n- shake\n- estética CapCut/terror edit\n\nLive:\n\nhttps://lobbytracker.vercel.app/media/larreta-impact-short.gif\n\nMEDIA:/home/ubuntu/lobbytracker/public/media/larreta-impact-short.gif\n\n### MP4 versión mejor para web / Telegram / página detail\n\nEs bastante más performante que el GIF para embeber.\n\nLive:\n\nhttps://lobbytracker.vercel.app/media/larreta-impact-short.mp4\n\nMEDIA:/home/ubuntu/lobbytracker/public/media/larreta-impact-short.mp4\n\nDeploy verificado: los 3 assets dan `200`.\n\n## Próxima acción estratégica que propongo\n\nReemplazar la imagen actual de Larreta en la página detail por este sistema:\n\n1. **Hero estático:** usar la nueva imagen GPT Image 2.\n2. **Impact mode:** al entrar al detalle, reproducir el MP4 una vez arriba de todo.\n3. **Share card:** mantener la PNG para redes/WhatsApp/Telegram.\n4. **No meter el GIF en producción salvo como fallback**, porque pesa 12 MB; el MP4 pesa menos y se ve mejor.\n\nConfirmame y lo integro en `/p/horacio-rodriguez-larreta` como hero animado.", "reasoning": null, "finish_reason": "stop", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94rL6kpjNArZNmRkz_Qs1X-tbPOicUsxdyFcV_MEP4leAycI0PkNXQsXQeliKMA8VdjWsxJM-xmKY8fEkUDJdzQWRlMVkYBmR4qv7P-npI3_WLJt40Sn1xMbUY-XI3pkf5FSmerJd58HOH_YHSG6l7aTkMKAgtSxqa4fbLrU4pYzRjF_w9ugSHq0F3ntFEk-VUFg3qpDnAVj44FvU9UxWhJfbD27k17UtyIpHv4Nfd1NrsTwtICwuPHzJmw1j1MaeVCsRRkM2MrrJfiuvydr9awsQcONpyP7eIRbmINCx4_bxxhlVZ77LFRN3jVdldNmPJK_nMeb78W_zM79TbwYcsxiyy44Vq6pi2EyYp9cgaBw59dcQJUV4PKtLeeOZbdcYnp0VWiqKbzTfN_DDxPdmCTSuvoRL_MGeW-kSaoIaTjLU3yxksEu_29W374bjkWsFq-43qRLv3ykDxdZN0IEBrypf_SJm-r9waecI_IXHjQW9NLFhwSC62fvUZx1IjvOUFGOP3NFSjUVvyPGRGMvFGKbz8ibrDTnsZlzey0Ms-EBlFRFRjl3qk8yweUPg9YxRarW0N5MagkpOuuVIut-XCz-xlS2f69vx8qi00Im8ctv17j-7DcjEhwou9OGM3XWGTkNjwiMMYUvxsMQGKqxCrUt9idg0BMTEFdyystuZ3azzUF_n91dWAtgXsmmdcmW6aoZdcoPGgeOLnS0AUpmOf_xMDzZ98OS4uUvozx0F4yTmMw399vsB8ZVAxByreX2uFNq4IrgFLRtJyx3oObvQxyVDbCwAhTFz-OlC3Y-iRVzmjRsTcNdU5UxMyYn8uQZla4R7Rty-sbke0KGGOIAG95ioJWdOLJkNJfDiuq_qawwcDFL-ljbkA8csKBNnmtr8Gv9Zq7lLX4WY3Vt3j-c9eZ8D_BgApxEPdqq9dkChKrwuB4orth3-Cl30EoHDpJh2ttnyAwLPKNGDWBsTpGU9LcygN-fKoVU7_GdHVc8aU223e0lS-2tFkeOwt7HUx0vDVj03RKM6Ymo7Vr9Oe9YYJX3Ooa7HWlvXI3yj_7RfPJEfyp0dUF8BrlVN2Z9xWcbDGzTGXQL0ez-RgTFmappdjUuGQj3SKZiRgS97rRK1EucTgW9hyR6cY_b69wMr6caqiOZXX_PW4kh_78eiVaEharZLvGBZZVjZr_lTFi7nmlAsAI9oRvfbDNOeU-cNE2pAeiV2Uxylao7klByivWOfylKJbR7Xntnt5KvXzSeM4EJOx74B86UoxHkbzFczUb2yh6rqFNVRzwOv-wuDPTzpXIb4HGTiZ9G0oiq0KgeSvbgmfpx3UpckJSVifkarOmKjQa2inoi-JThTgit2jW3xc0P0QH_ZDOQqGFkuvlggrXavKDeYSY6jtcrUkH7sTczR3p3h5T2P1rXd1nsEjypYGj93myShp9K1DVkxuAybS_k60T-CTUq_lKppXXNuI3hE4fuUMgrKyBM658lu6SUDRQqTBllxHH3DJfkvK4pdKS6SJgcMLMDM_Jg9vfWe7qsmfKo0Gp5fYJQ_vKFRG2sSKNkqn4a4qK7Vqv3zdlzgyEcQqdXXBpkUGyZngZY4i-4WDP4UgdI9vMK_0nbi4fG_HfPJCWHtEMRfd88QfcpIBQhgghsyKKZsxOJwjzfg2mOYP-2", "id": "rs_0bb8ef1f39b62dbe0169f78ac80d4c8198ab0246625c8c2412", "summary": [] } ], "codex_message_items": [ { "type": "message", "role": "assistant", "status": "completed", "content": [ { "type": "output_text", "text": "Tenés razón. Las cards que te había dejado eran una poronga comparadas con la imagen adjunta. Ya corregí el enfoque: **GPT Image 2 / OpenRouter, hiperrealista, rojo cinematográfico, Obelisco, bandera de Israel, dólares, contrato, estética de póster caro**.\n\n## Nuevos assets generados\n\n### Imagen nueva estilo adjunta — GPT Image 2\n\nLive:\n\nhttps://lobbytracker.vercel.app/cards/generated/larreta-gpt-image2-v1.png\n\nMEDIA:/home/ubuntu/lobbytracker/public/cards/generated/larreta-gpt-image2-v1.png\n\n### GIF con efecto tipo short terror/glitch/zoom\n\nLo hice sobre la imagen adjunta que me pasaste, con:\n\n- zoom punches\n- flashes rojos\n- glitch horizontal\n- RGB split\n- scanlines\n- shake\n- estética CapCut/terror edit\n\nLive:\n\nhttps://lobbytracker.vercel.app/media/larreta-impact-short.gif\n\nMEDIA:/home/ubuntu/lobbytracker/public/media/larreta-impact-short.gif\n\n### MP4 versión mejor para web / Telegram / página detail\n\nEs bastante más performante que el GIF para embeber.\n\nLive:\n\nhttps://lobbytracker.vercel.app/media/larreta-impact-short.mp4\n\nMEDIA:/home/ubuntu/lobbytracker/public/media/larreta-impact-short.mp4\n\nDeploy verificado: los 3 assets dan `200`.\n\n## Próxima acción estratégica que propongo\n\nReemplazar la imagen actual de Larreta en la página detail por este sistema:\n\n1. **Hero estático:** usar la nueva imagen GPT Image 2.\n2. **Impact mode:** al entrar al detalle, reproducir el MP4 una vez arriba de todo.\n3. **Share card:** mantener la PNG para redes/WhatsApp/Telegram.\n4. **No meter el GIF en producción salvo como fallback**, porque pesa 12 MB; el MP4 pesa menos y se ve mejor.\n\nConfirmame y lo integro en `/p/horacio-rodriguez-larreta` como hero animado." } ], "id": "msg_0bb8ef1f39b62dbe0169f78acb7f8081989baa86181038fa48", "phase": "final_answer" } ] }, { "role": "user", "content": "Review the conversation above and consider whether a skill should be saved or updated.\n\nWork in this order — do not skip steps:\n\n1. SURVEY the existing skill landscape first. Call skills_list to see what you have. If anything looks potentially relevant, skill_view it before deciding. You are looking for the CLASS of task that just happened, not the exact task. Example: a successful Tauri build is in the class \"desktop app build troubleshooting\", not \"fix my specific Tauri error today\".\n\n2. THINK CLASS-FIRST. What general pattern of task did the user just complete? What conditions will trigger this pattern again? Describe the class in one sentence before looking at what to save.\n\n3. PREFER GENERALIZING AN EXISTING SKILL over creating a new one. If a skill already covers the class — even partially — update it (skill_manage patch) with the new insight. Broaden its \"when to use\" trigger if needed.\n\n4. ONLY CREATE A NEW SKILL when no existing skill reasonably covers the class. When you create one, name and scope it at the class level (\"react-i18n-setup\", not \"add-i18n-to-my-dashboard-app\"). The trigger section must describe the class of situations, not this one session.\n\n5. If you notice two existing skills that overlap, note it in your response so a future review can consolidate them. Do not consolidate now unless the overlap is obvious and low-risk.\n\nOnly act when something is genuinely worth saving. If nothing stands out, just say 'Nothing to save.' and stop." }, { "role": "assistant", "content": "", "reasoning": "**Listing tools for compliance**\n\nI need to comply with the instructions. First, I’ll check the tools commentary and then look at the skills list. We’ve previously viewed the political-tracker-card in our conversation, but now the instructions say to survey again. I’m also considering options like youtube-content, gif-search, or maybe something comfortable in media. It might be helpful to categorize them under creative/media. Let’s make sure to gather everything for this task!", "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94rjbKvDP-Z_Q9hmE10T3JOE50SClzw28m0V2NlmUfO_5X01UcIjIH3_thMJZfcZTT4XEtP1O1Oa_ntYNwNBJgdePuvimH6sWWujVny6minjTAq_v6j7xC7GGc_wt8OgR5zAuEojLMu80ip5SJvVHYgf-EhWgH6w73EiMEGfQkb9Tqph5ZmiT5KzNxaTpmpytGcF5BSw6p3-EP-1p1EyWT1MQY31M3x5SDQYSRK-_uJS5C0XfeoEoO2Z862aDeURpcN7p3dKYHP_RDNzQuT8_s83jnahHy0BIaT-Wtj7LLdD7vNgQAzOkWl5brHH-mBO2i9xQa4BRGhlxl1rbFEo7VAWcl_SrkUz7uLeqNu_s-dVh5mdgchV1Hle0TPyv0OCCPEkCrMv4OL-kqTtOx2P37q18iIF1v9xzApROIivydGB-7bIILY-wuc0MnI9MSZHwHrPw2xZGEr2eBJHbBv3FzEXaBID9rrur4O1bEunRw7i_Ph4Hv3Le9WiVDj8kTBsAnesYJsShvJr2U-IlgbJfdf41RhszWxzN-RFBIgQoeCsKaeRtIkWsG-Aruzddik7NV_v3i3j23upq-QfLZDz1-0fuWPJ3ECFTBfZsPl-dUy3dTMiAbwPU2dMxR9xqTsckgqyhwltEE9YHjdZpd9dN7TL1mPbPI72d841yvfEFsUZSPH7OkqfZjRAzdfEOR8BwWJBI7hlateqNQM3quuRZI-jiZ0_JVs8nYzIB2hLaQTK1WChEgpUQ8ZWIGSBlR2x2twOLKh9wsYRG6nwbcRbHlrkZZkCAjqIKlSWrZE33JZ7oZOZueQPbVRx3OY3i387_MxbilqLaATFxUYHRFmqunfB9nm8DaGvWayyDD0moC86_MPNHnSdDpO1qA3MFNkZWjFAfIlq_hFd9Hxys860dcYSs3Rhy1ZRzaQdP49CESHfHpd1OqWeCjcKaX7as1xqWr1WkUk5Gw3BcwHjMhCON90M2vDZJOgYMms6VBHc7SC-6GRX9xHP-Qv6OtPGnIFiyK_ogadDmavAo7j2k0cFclt8lMCxDp7N6OgTgr4LvKD92MrPNjmvAwRlZKiS32l-y7FVfYFAcPltkAAA0x3tCEurYujvwMB4NR83o4NkVBxYJIUSEYX9XmD9L5SVurJ4SZ12oZp7OOAYeBNyM3UZEhMAe3Qj8EQCiTzSgkgU5rvSdabJI8bqHsMq2z4E_gXX5SOgijKGcLjL_q5QTPojj5IuRyNZNHy8mCgR6jgp8oQbgqQy5r_Ch-e8tYR6pg6jHSgN", "id": "rs_0bb8ef1f39b62dbe0169f78adfa61c81989dddd44ad3aea820", "summary": [ { "type": "summary_text", "text": "**Listing tools for compliance**\n\nI need to comply with the instructions. First, I’ll check the tools commentary and then look at the skills list. We’ve previously viewed the political-tracker-card in our conversation, but now the instructions say to survey again. I’m also considering options like youtube-content, gif-search, or maybe something comfortable in media. It might be helpful to categorize them under creative/media. Let’s make sure to gather everything for this task!" } ] } ], "tool_calls": [ { "id": "call_HjaPAInuevcmoZjaYehfaQbh", "call_id": "call_HjaPAInuevcmoZjaYehfaQbh", "response_item_id": "fc_0bb8ef1f39b62dbe0169f78ae38e508198b32783675327da45", "type": "function", "function": { "name": "skills_list", "arguments": "{}" } } ] }, { "role": "tool", "content": "{\"success\": true, \"skills\": [{\"name\": \"booking-scraper\", \"description\": \"Search Booking.com for hotel availability using Camoufox stealth browser. Bypasses DataDome anti-bot protection. Returns real-time hotel results with prices, scores, and direct booking links.\", \"category\": null}, {\"name\": \"bybit\", \"description\": \"Check Bybit account — wallet balance, open positions, orders, fees, and transactions. Read-only, no trading.\", \"category\": null}, {\"name\": \"dogfood\", \"description\": \"Systematic exploratory QA testing of web applications — find bugs, capture evidence, and generate structured reports\", \"category\": null}, {\"name\": \"hermes-webui-comparison\", \"description\": \"Evaluate, deploy, and compare alternative web UIs for Hermes Agent. Covers Hermes WebUI (nesquena), Open WebUI, and hermes-workspace. Use when the user wants to try different frontends, compare UIs, or set up a replacement for the default Vite workspace.\", \"category\": null}, {\"name\": \"hermes-webui-deploy\", \"description\": \"Deploy Hermes WebUI (nesquena/hermes-webui) with embedded ttyd terminal behind nginx reverse proxy\", \"category\": null}, {\"name\": \"lobbytracker-updater\", \"description\": \"Use when running or maintaining the weekly Lobby Tracker Argentina source-update agent. Iterates politicians, researches new public developments, inserts sourced connections via Supabase Management API, and updates totals without inventing data.\", \"category\": null}, {\"name\": \"myristica-ops\", \"description\": \"Myristica rental management app — stack, infrastructure, DB schema, deploy workflow, and operational notes. Use when working on Myristica.\", \"category\": null}, {\"name\": \"personal-browser-cdp\", \"description\": \"Use the user's real Chrome browser through Hermes' existing CDP connection. Trigger when the user asks for their personal browser, desktop browser, live browser, gateway browser, or CDP browser.\", \"category\": null}, {\"name\": \"pixel-6a\", \"description\": \"Access Ignacio's Pixel 6a via ADB over Tailscale — read notifications, check installed apps, grant permissions, forward financial alerts.\", \"category\": null}, {\"name\": \"political-tracker-card\", \"description\": \"Generate political tracker/scorecard red cards (AIPAC Tracker style) using GPT Image 2 or Nano Banana via OpenRouter. Magazine-cover aesthetic, dark red backgrounds, silhouettes, large dollar amounts, editorial typography. For social media political graphics exposing lobby connections, campaign financing, and public contracts.\", \"category\": null}, {\"name\": \"wa-bot-fix-troubleshooting\", \"description\": \"Fix WhatsApp bot not responding when bridge is connected but messages go to Vercel\", \"category\": null}, {\"name\": \"yuanbao\", \"description\": \"Yuanbao (元宝) groups: @mention users, query info/members.\", \"category\": null}, {\"name\": \"claude-code\", \"description\": \"Delegate coding to Claude Code CLI (features, PRs).\", \"category\": \"autonomous-ai-agents\"}, {\"name\": \"codex\", \"description\": \"Delegate coding to OpenAI Codex CLI (features, PRs).\", \"category\": \"autonomous-ai-agents\"}, {\"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.\", \"category\": \"autonomous-ai-agents\"}, {\"name\": \"opencode\", \"description\": \"Delegate coding to OpenCode CLI (features, PR review).\", \"category\": \"autonomous-ai-agents\"}, {\"name\": \"provider-credential-exhaustion\", \"description\": \"Diagnose and resolve API quota exhaustion / rate-limit errors across all Hermes platforms (WebUI, Telegram, CLI, etc.) When a provider's credential pool marks an entry \\\"exhausted\\\" and everything fails, use this skill to systematically investigate, understand the scope, and apply mitigations.\", \"category\": \"autonomous-ai-agents\"}, {\"name\": \"architecture-diagram\", \"description\": \"Dark-themed SVG architecture/cloud/infra diagrams as HTML.\", \"category\": \"creative\"}, {\"name\": \"ascii-art\", \"description\": \"ASCII art: pyfiglet, cowsay, boxes, image-to-ascii.\", \"category\": \"creative\"}, {\"name\": \"ascii-video\", \"description\": \"ASCII video: convert video/audio to colored ASCII MP4/GIF.\", \"category\": \"creative\"}, {\"name\": \"baoyu-comic\", \"description\": \"Knowledge comics (知识漫画): educational, biography, tutorial.\", \"category\": \"creative\"}, {\"name\": \"baoyu-infographic\", \"description\": \"Infographics: 21 layouts x 21 styles (信息图, 可视化).\", \"category\": \"creative\"}, {\"name\": \"claude-design\", \"description\": \"Design one-off HTML artifacts (landing, deck, prototype).\", \"category\": \"creative\"}, {\"name\": \"comfyui\", \"description\": \"Generate images, video, and audio with ComfyUI — install, launch, manage nodes/models, run workflows with parameter injection. Uses the official comfy-cli for lifecycle and direct REST/WebSocket API for execution.\", \"category\": \"creative\"}, {\"name\": \"design-md\", \"description\": \"Author/validate/export Google's DESIGN.md token spec files.\", \"category\": \"creative\"}, {\"name\": \"excalidraw\", \"description\": \"Hand-drawn Excalidraw JSON diagrams (arch, flow, seq).\", \"category\": \"creative\"}, {\"name\": \"humanizer\", \"description\": \"Humanize text: strip AI-isms and add real voice.\", \"category\": \"creative\"}, {\"name\": \"ideation\", \"description\": \"Generate project ideas via creative constraints.\", \"category\": \"creative\"}, {\"name\": \"manim-video\", \"description\": \"Manim CE animations: 3Blue1Brown math/algo videos.\", \"category\": \"creative\"}, {\"name\": \"p5js\", \"description\": \"p5.js sketches: gen art, shaders, interactive, 3D.\", \"category\": \"creative\"}, {\"name\": \"pixel-art\", \"description\": \"Pixel art w/ era palettes (NES, Game Boy, PICO-8).\", \"category\": \"creative\"}, {\"name\": \"popular-web-designs\", \"description\": \"54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.\", \"category\": \"creative\"}, {\"name\": \"pretext\", \"description\": \"Use when building creative browser demos with @chenglou/pretext — DOM-free text layout for ASCII art, typographic flow around obstacles, text-as-geometry games, kinetic typography, and text-powered generative art. Produces single-file HTML demos by default.\", \"category\": \"creative\"}, {\"name\": \"sketch\", \"description\": \"Throwaway HTML mockups: 2-3 design variants to compare.\", \"category\": \"creative\"}, {\"name\": \"songwriting-and-ai-music\", \"description\": \"Songwriting craft and Suno AI music prompts.\", \"category\": \"creative\"}, {\"name\": \"touchdesigner-mcp\", \"description\": \"Control a running TouchDesigner instance via twozero MCP — create operators, set parameters, wire connections, execute Python, build real-time visuals. 36 native tools.\", \"category\": \"creative\"}, {\"name\": \"jupyter-live-kernel\", \"description\": \"Iterative Python via live Jupyter kernel (hamelnb).\", \"category\": \"data-science\"}, {\"name\": \"kanban-orchestrator\", \"description\": \"Decomposition playbook + specialist-roster conventions + anti-temptation rules for an orchestrator profile routing work through Kanban. The \\\"don't do the work yourself\\\" rule and the basic lifecycle are auto-injected into every kanban worker's system prompt; this skill is the deeper playbook when you're specifically playing the orchestrator role.\", \"category\": \"devops\"}, {\"name\": \"kanban-worker\", \"description\": \"Pitfalls, examples, and edge cases for Hermes Kanban workers. The lifecycle itself is auto-injected into every worker's system prompt as KANBAN_GUIDANCE (from agent/prompt_builder.py); this skill is what you load when you want deeper detail on specific scenarios.\", \"category\": \"devops\"}, {\"name\": \"openclaw-mobile-node\", \"description\": \"Set up OpenClaw gateway as a notification relay for an Android device. Enables the agent to read phone notifications (financial apps, messaging, etc.) via the OpenClaw Android companion app's NotificationListenerService.\", \"category\": \"devops\"}, {\"name\": \"supabase-project-setup\", \"description\": \"Provision a new Supabase project + database entirely via Management API — create project, run SQL (schema + seed), get API keys, wire up Vercel env vars, and redeploy. Use when psql is unavailable (IPv6 on Oracle Cloud blocks direct DB host), pooler isn't ready, or the user wants fully automated setup without touching the Supabase GUI.\", \"category\": \"devops\"}, {\"name\": \"supabase-region-migration\", \"description\": \"Migrate a Supabase project to a different region (e.g. us-east-1 → sa-east-1) when pg_dump is unavailable or version-mismatched. Uses psql COPY for schema+data export, drizzle-kit push for schema recreation, and Vercel API to update env vars. Use when latency is a concern or region change is needed.\", \"category\": \"devops\"}, {\"name\": \"webhook-subscriptions\", \"description\": \"Webhook subscriptions: event-driven agent runs.\", \"category\": \"devops\"}, {\"name\": \"whatsapp-baileys-vercel\", \"description\": \"Run a WhatsApp bot with Baileys bridge + Vercel webhook — architecture, common pitfalls, and fixes.\", \"category\": \"devops\"}, {\"name\": \"hermes-workspace-pristine-reset\", \"description\": \"Reset a local Hermes Agent + Hermes Workspace install to a known-clean upstream state, preserving backups first and verifying what still fails upstream.\", \"category\": \"dogfood\"}, {\"name\": \"himalaya\", \"description\": \"Himalaya CLI: IMAP/SMTP email from terminal.\", \"category\": \"email\"}, {\"name\": \"minecraft-modpack-server\", \"description\": \"Host modded Minecraft servers (CurseForge, Modrinth).\", \"category\": \"gaming\"}, {\"name\": \"pokemon-player\", \"description\": \"Play Pokemon via headless emulator + RAM reads.\", \"category\": \"gaming\"}, {\"name\": \"codebase-inspection\", \"description\": \"Inspect codebases w/ pygount: LOC, languages, ratios.\", \"category\": \"github\"}, {\"name\": \"github-auth\", \"description\": \"GitHub auth setup: HTTPS tokens, SSH keys, gh CLI login.\", \"category\": \"github\"}, {\"name\": \"github-code-review\", \"description\": \"Review PRs: diffs, inline comments via gh or REST.\", \"category\": \"github\"}, {\"name\": \"github-issues\", \"description\": \"Create, triage, label, assign GitHub issues via gh or REST.\", \"category\": \"github\"}, {\"name\": \"github-pr-workflow\", \"description\": \"GitHub PR lifecycle: branch, commit, open, CI, merge.\", \"category\": \"github\"}, {\"name\": \"github-repo-management\", \"description\": \"Clone/create/fork repos; manage remotes, releases.\", \"category\": \"github\"}, {\"name\": \"find-nearby\", \"description\": \"Find nearby places (restaurants, cafes, bars, pharmacies, etc.) using OpenStreetMap. Works with coordinates, addresses, cities, zip codes, or Telegram location pins. No API keys needed.\", \"category\": \"leisure\"}, {\"name\": \"mcporter\", \"description\": \"Use the mcporter CLI to list, configure, auth, and call MCP servers/tools directly (HTTP or stdio), including ad-hoc servers, config edits, and CLI/type generation.\", \"category\": \"mcp\"}, {\"name\": \"native-mcp\", \"description\": \"MCP client: connect servers, register tools (stdio/HTTP).\", \"category\": \"mcp\"}, {\"name\": \"gif-search\", \"description\": \"Search/download GIFs from Tenor via curl + jq.\", \"category\": \"media\"}, {\"name\": \"heartmula\", \"description\": \"HeartMuLa: Suno-like song generation from lyrics + tags.\", \"category\": \"media\"}, {\"name\": \"songsee\", \"description\": \"Audio spectrograms/features (mel, chroma, MFCC) via CLI.\", \"category\": \"media\"}, {\"name\": \"spotify\", \"description\": \"Spotify: play, search, queue, manage playlists and devices.\", \"category\": \"media\"}, {\"name\": \"youtube-content\", \"description\": \"YouTube transcripts to summaries, threads, blogs.\", \"category\": \"media\"}, {\"name\": \"audiocraft-audio-generation\", \"description\": \"AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.\", \"category\": \"mlops\"}, {\"name\": \"axolotl\", \"description\": \"Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).\", \"category\": \"mlops\"}, {\"name\": \"clawrouter\", \"description\": \"Install, configure, and manage ClawRouter as a local LLM proxy for Hermes Agent. Routes AI requests across 55+ models via USDC payments on Base/Solana. Use when setting up ClawRouter, checking wallet status, updating versions, or configuring Hermes to use blockrun provider.\", \"category\": \"mlops\"}, {\"name\": \"clip\", \"description\": \"OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.\", \"category\": \"mlops\"}, {\"name\": \"dspy\", \"description\": \"DSPy: declarative LM programs, auto-optimize prompts, RAG.\", \"category\": \"mlops\"}, {\"name\": \"evaluating-llms-harness\", \"description\": \"lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).\", \"category\": \"mlops\"}, {\"name\": \"fine-tuning-with-trl\", \"description\": \"Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.\", \"category\": \"mlops\"}, {\"name\": \"gguf-quantization\", \"description\": \"GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.\", \"category\": \"mlops\"}, {\"name\": \"grpo-rl-training\", \"description\": \"Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training\", \"category\": \"mlops\"}, {\"name\": \"guidance\", \"description\": \"Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework\", \"category\": \"mlops\"}, {\"name\": \"huggingface-hub\", \"description\": \"HuggingFace hf CLI: search/download/upload models, datasets.\", \"category\": \"mlops\"}, {\"name\": \"llama-cpp\", \"description\": \"llama.cpp local GGUF inference + HF Hub model discovery.\", \"category\": \"mlops\"}, {\"name\": \"modal-serverless-gpu\", \"description\": \"Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.\", \"category\": \"mlops\"}, {\"name\": \"obliteratus\", \"description\": \"OBLITERATUS: abliterate LLM refusals (diff-in-means).\", \"category\": \"mlops\"}, {\"name\": \"outlines\", \"description\": \"Outlines: structured JSON/regex/Pydantic LLM generation.\", \"category\": \"mlops\"}, {\"name\": \"peft-fine-tuning\", \"description\": \"Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.\", \"category\": \"mlops\"}, {\"name\": \"pytorch-fsdp\", \"description\": \"Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision, CPU offloading, FSDP2\", \"category\": \"mlops\"}, {\"name\": \"segment-anything-model\", \"description\": \"SAM: zero-shot image segmentation via points, boxes, masks.\", \"category\": \"mlops\"}, {\"name\": \"serving-llms-vllm\", \"description\": \"vLLM: high-throughput LLM serving, OpenAI API, quantization.\", \"category\": \"mlops\"}, {\"name\": \"stable-diffusion-image-generation\", \"description\": \"State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.\", \"category\": \"mlops\"}, {\"name\": \"unsloth\", \"description\": \"Unsloth: 2-5x faster LoRA/QLoRA fine-tuning, less VRAM.\", \"category\": \"mlops\"}, {\"name\": \"weights-and-biases\", \"description\": \"W&B: log ML experiments, sweeps, model registry, dashboards.\", \"category\": \"mlops\"}, {\"name\": \"whisper\", \"description\": \"OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.\", \"category\": \"mlops\"}, {\"name\": \"myristica-projects\", \"description\": \"Myristica project context, audit status, and development decisions\", \"category\": \"myristica-ops\"}, {\"name\": \"obsidian\", \"description\": \"Read, search, and create notes in the Obsidian vault.\", \"category\": \"note-taking\"}, {\"name\": \"asana\", \"description\": \"Integrate Asana with Clawdbot via the Asana REST API. Use when you need to list/search/create/update Asana tasks/projects/workspaces, or to set up Asana OAuth (authorization code grant) for a personal local-only integration (OOB/manual code paste).\", \"category\": \"openclaw-imports\"}, {\"name\": \"bitwarden\", \"description\": \"Set up and use Bitwarden CLI (bw). Use when installing the CLI, unlocking vault, or reading/generating secrets via bw. Handles session management with BW_SESSION.\", \"category\": \"openclaw-imports\"}, {\"name\": \"gog\", \"description\": \"Read-only Google Workspace CLI for Gmail, Calendar, Drive, Contacts, Sheets, and Docs.\", \"category\": \"openclaw-imports\"}, {\"name\": \"google-photos\", \"description\": \"Manage Google Photos library. Upload photos, create albums, and list library content. Use when the user wants to backup, organize, or share images via Google Photos.\", \"category\": \"openclaw-imports\"}, {\"name\": \"hevy\", \"description\": \"Query workout data from Hevy including workouts, routines, exercises, and history. Use when user asks about their workouts, gym sessions, exercise progress, or fitness routines.\", \"category\": \"openclaw-imports\"}, {\"name\": \"model-router\", \"description\": \"Intelligent cost-aware model routing that classifies task complexity and selects the optimal AI model. Automatically routes simple tasks to cheap models and complex tasks to premium models. Use when you need \\\"which model should I use\\\", \\\"route this task\\\", \\\"optimize cost\\\", \\\"switch model\\\", \\\"cheapest model for this\\\", \\\"use the right model\\\", or to balance quality vs cost across AI providers. Supports progressive escalation, 5-tier routing, and current model pricing.\", \"category\": \"openclaw-imports\"}, {\"name\": \"notion\", \"description\": \"Notion API for creating and managing pages, databases, and blocks.\", \"category\": \"openclaw-imports\"}, {\"name\": \"parallel-preview-orchestrator\", \"description\": \"Orchestrate parallel preview-site creation across multiple CLI backends (`codex-cli`, `gemini-cli`, `deepseek-code`) and publish each result with `pipo-deploy`. Default routing is `/preview//`, but agent-specific runs may also publish to `///` when the human asks for that exact naming convention.\", \"category\": \"openclaw-imports\"}, {\"name\": \"session-logs\", \"description\": \"Search and analyze your own session logs (older/parent conversations) using jq.\", \"category\": \"openclaw-imports\"}, {\"name\": \"summarize\", \"description\": \"Summarize URLs or files with the summarize CLI (web, PDFs, images, audio, YouTube).\", \"category\": \"openclaw-imports\"}, {\"name\": \"weather\", \"description\": \"Get current weather and forecasts (no API key required).\", \"category\": \"openclaw-imports\"}, {\"name\": \"airtable\", \"description\": \"Airtable REST API via curl. Records CRUD, filters, upserts.\", \"category\": \"productivity\"}, {\"name\": \"google-workspace\", \"description\": \"Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.\", \"category\": \"productivity\"}, {\"name\": \"linear\", \"description\": \"Linear: manage issues, projects, teams via GraphQL + curl.\", \"category\": \"productivity\"}, {\"name\": \"maps\", \"description\": \"Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.\", \"category\": \"productivity\"}, {\"name\": \"monthy-expenses\", \"description\": \"Reconstruct and maintain the user's household monthly-expenses dashboard from Gmail, PDFs, billing portals, and card statements.\", \"category\": \"productivity\"}, {\"name\": \"nano-pdf\", \"description\": \"Edit PDF text/typos/titles via nano-pdf CLI (NL prompts).\", \"category\": \"productivity\"}, {\"name\": \"ocr-and-documents\", \"description\": \"Extract text from PDFs/scans (pymupdf, marker-pdf).\", \"category\": \"productivity\"}, {\"name\": \"powerpoint\", \"description\": \"Create, read, edit .pptx decks, slides, notes, templates.\", \"category\": \"productivity\"}, {\"name\": \"godmode\", \"description\": \"Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.\", \"category\": \"red-teaming\"}, {\"name\": \"arxiv\", \"description\": \"Search arXiv papers by keyword, author, category, or ID.\", \"category\": \"research\"}, {\"name\": \"blogwatcher\", \"description\": \"Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.\", \"category\": \"research\"}, {\"name\": \"llm-wiki\", \"description\": \"Karpathy's LLM Wiki: build/query interlinked markdown KB.\", \"category\": \"research\"}, {\"name\": \"ml-paper-writing\", \"description\": \"Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.\", \"category\": \"research\"}, {\"name\": \"polymarket\", \"description\": \"Query Polymarket: markets, prices, orderbooks, history.\", \"category\": \"research\"}, {\"name\": \"research-paper-writing\", \"description\": \"Write ML papers for NeurIPS/ICML/ICLR: design→submit.\", \"category\": \"research\"}, {\"name\": \"openhue\", \"description\": \"Control Philips Hue lights, scenes, rooms via OpenHue CLI.\", \"category\": \"smart-home\"}, {\"name\": \"xitter\", \"description\": \"Interact with X/Twitter via the x-cli terminal client using official X API credentials. Use for posting, reading timelines, searching tweets, liking, retweeting, bookmarks, mentions, and user lookups.\", \"category\": \"social-media\"}, {\"name\": \"xurl\", \"description\": \"X/Twitter via xurl CLI: post, search, DM, media, v2 API.\", \"category\": \"social-media\"}, {\"name\": \"code-review\", \"description\": \"Guidelines for performing thorough code reviews with security and quality focus\", \"category\": \"software-development\"}, {\"name\": \"debugging-hermes-tui-commands\", \"description\": \"Debug Hermes TUI slash commands: Python, gateway, Ink UI.\", \"category\": \"software-development\"}, {\"name\": \"evaluate-openai-compatible-llm-endpoint\", \"description\": \"Verify whether a new OpenAI-compatible chat/completions endpoint is suitable for Hermes by combining docs lookup with live API probes for multi-turn chat, system prompt obedience, tool calling, and token-budget behavior.\", \"category\": \"software-development\"}, {\"name\": \"hermes-agent-skill-authoring\", \"description\": \"Author in-repo SKILL.md: frontmatter, validator, structure.\", \"category\": \"software-development\"}, {\"name\": \"hermes-specialist-profile-custom-endpoint\", \"description\": \"Create a Hermes profile specialized for a model's strengths, backed by a custom OpenAI-compatible endpoint, then verify it end-to-end.\", \"category\": \"software-development\"}, {\"name\": \"node-inspect-debugger\", \"description\": \"Debug Node.js via --inspect + Chrome DevTools Protocol CLI.\", \"category\": \"software-development\"}, {\"name\": \"plan\", \"description\": \"Plan mode: write markdown plan to .hermes/plans/, no exec.\", \"category\": \"software-development\"}, {\"name\": \"python-debugpy\", \"description\": \"Debug Python: pdb REPL + debugpy remote (DAP).\", \"category\": \"software-development\"}, {\"name\": \"react-component-split\", \"description\": \"Split large React client components (>300 lines) into multi-file architecture with hooks, helpers, types, and sub-components. Preserves behavior while improving maintainability.\", \"category\": \"software-development\"}, {\"name\": \"requesting-code-review\", \"description\": \"Pre-commit review: security scan, quality gates, auto-fix.\", \"category\": \"software-development\"}, {\"name\": \"spike\", \"description\": \"Throwaway experiments to validate an idea before build.\", \"category\": \"software-development\"}, {\"name\": \"subagent-driven-development\", \"description\": \"Execute plans via delegate_task subagents (2-stage review).\", \"category\": \"software-development\"}, {\"name\": \"systematic-debugging\", \"description\": \"4-phase root cause debugging: understand bugs before fixing.\", \"category\": \"software-development\"}, {\"name\": \"test-driven-development\", \"description\": \"TDD: enforce RED-GREEN-REFACTOR, tests before code.\", \"category\": \"software-development\"}, {\"name\": \"writing-plans\", \"description\": \"Write implementation plans: bite-sized tasks, paths, code.\", \"category\": \"software-development\"}], \"categories\": [\"autonomous-ai-agents\", \"creative\", \"data-science\", \"devops\", \"dogfood\", \"email\", \"gaming\", \"github\", \"leisure\", \"mcp\", \"media\", \"mlops\", \"myristica-ops\", \"note-taking\", \"openclaw-imports\", \"productivity\", \"red-teaming\", \"research\", \"smart-home\", \"social-media\", \"software-development\"], \"count\": 131, \"hint\": \"Use skill_view(name) to see full content, tags, and linked files\"}", "tool_call_id": "call_HjaPAInuevcmoZjaYehfaQbh" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": 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"id": "rs_0bb8ef1f39b62dbe0169f78ae6ad108198b7c4fda3ef4f2acd", "summary": [] } ], "tool_calls": [ { "id": "call_aLhStFB4ow4C7oJxd3j1WWLF", "call_id": "call_aLhStFB4ow4C7oJxd3j1WWLF", "response_item_id": "fc_0bb8ef1f39b62dbe0169f78aec42a8819891db2e64215608d0", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"political-tracker-card\"}" } }, { "id": "call_thf081vEQLLDvvTNgW7C9FfM", "call_id": "call_thf081vEQLLDvvTNgW7C9FfM", "response_item_id": "fc_0bb8ef1f39b62dbe0169f78aec42bc819882609a2c38383edf", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"youtube-content\"}" } }, { "id": "call_c8u5e0DBSbJKYjFDkkL7Dij7", "call_id": "call_c8u5e0DBSbJKYjFDkkL7Dij7", "response_item_id": "fc_0bb8ef1f39b62dbe0169f78aec42c48198af7cf39fa4275aaa", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"gif-search\"}" } } ] }, { "role": "tool", "content": "{\"success\": true, \"name\": \"political-tracker-card\", \"description\": \"Generate political tracker/scorecard red cards (AIPAC Tracker style) using GPT Image 2 or Nano Banana via OpenRouter. Magazine-cover aesthetic, dark red backgrounds, silhouettes, large dollar amounts, editorial typography. For social media political graphics exposing lobby connections, campaign financing, and public contracts.\", \"tags\": [], \"related_skills\": [], \"content\": \"---\\nname: political-tracker-card\\ndescription: Generate political tracker/scorecard red cards (AIPAC Tracker style) using GPT Image 2 or Nano Banana via OpenRouter. Magazine-cover aesthetic, dark red backgrounds, silhouettes, large dollar amounts, editorial typography. For social media political graphics exposing lobby connections, campaign financing, and public contracts.\\ntriggers:\\n - \\\"political tracker\\\"\\n - \\\"tracker card\\\"\\n - \\\"red card\\\"\\n - \\\"AIPAC Tracker style\\\"\\n - \\\"lobby card\\\"\\n - \\\"political scorecard\\\"\\n - \\\"generate political graphic\\\"\\n - \\\"lobby tracker graphic\\\"\\n - \\\"image generation\\\"\\n - \\\"GPT Image 2\\\"\\n - \\\"Nano Banana\\\"\\n - \\\"political infographic card\\\"\\nrequirements:\\n env_vars:\\n - OPENROUTER_API_KEY\\n system_packages:\\n - curl\\n - python3\\n---\\n\\n# Political Tracker Card Generation\\n\\nGenerate red/green political tracker cards in AIPAC Tracker style using AI image generation APIs via OpenRouter.\\n\\n## Models Available\\n\\n| Model | OpenRouter ID | Best For | Quality |\\n|---|---|---|---|\\n| **GPT Image 2** (preferred) | `openai/gpt-5.4-image-2` | Editorial, photorealistic, magazine covers, text-heavy layouts | Best |\\n| Nano Banana Pro | `google/gemini-3-pro-image-preview` | Complex layouts, 2K/4K, identity preservation | Excellent |\\n| Nano Banana 2 | `google/gemini-3.1-flash-image-preview` | Fast iteration, drafts | Very Good |\\n| Nano Banana (v1) | `google/gemini-2.5-flash-image` | Quick edits, basic cards | Good |\\n\\n**Default: GPT Image 2** — photorealistic, best text rendering, magazine-cover quality.\\n\\n## Prompting Best Practices (from OpenAI docs)\\n\\n1. **Structure**: artifact type → background/scene → subject → layout → text in quotes → constraints\\n2. **Text**: put exact text in double quotes, specify role (HEADLINE, SUBHEAD, LABEL, FOOTER)\\n3. **Quality**: use `\\\"high\\\"` for text-heavy cards\\n4. **Constraints**: \\\"no watermark, no cartoon, no extra text, no border\\\"\\n5. **For photorealism**: use words like \\\"photorealistic\\\", \\\"editorial photography\\\", \\\"magazine cover\\\", \\\"Sports Illustrated style\\\"\\n\\n## Template: Red Card Generation Script\\n\\n```bash\\nOPENROUTER_KEY=$(grep OPENROUTER_API_KEY ~/.hermes/.env | cut -d= -f2)\\n\\ncurl -s --max-time 300 \\\"https://openrouter.ai/api/v1/chat/completions\\\" \\\\\\n -H \\\"Authorization: Bearer $OPENROUTER_KEY\\\" \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -d '{\\n \\\"model\\\": \\\"openai/gpt-5.4-image-2\\\",\\n \\\"modalities\\\": [\\\"image\\\", \\\"text\\\"],\\n \\\"image_config\\\": {\\\"aspect_ratio\\\": \\\"1:1\\\", \\\"image_size\\\": \\\"1K\\\"},\\n \\\"messages\\\": [{\\n \\\"role\\\": \\\"user\\\",\\n \\\"content\\\": \\\"Sports magazine cover style political tracker card. Photorealistic, glossy editorial photography, dramatic ESPN Magazine / Sports Illustrated aesthetic. Dark crimson red background with volumetric smoke, cinematic god rays, high-contrast. Left: grayscale silhouette with rim lighting. Right: giant glossy white dollar amount. HEADLINE: [NAME]. SUBHEAD: [POSITION]. NUMBER: [AMOUNT]. LABEL: [LOBBY NAME] TOTAL. Bottom: magazine cover lines with stats. Barcode, date stamp. Photorealistic editorial magazine cover.\\\"\\n }]\\n }' -o /tmp/card.json\\n\\npython3 -c \\\"\\nimport json, base64\\nwith open('/tmp/card.json') as f:\\n d = json.load(f)\\nmsg = d.get('choices',[{}])[0].get('message',{})\\nimgs = msg.get('images',[])\\nif imgs:\\n url = imgs[0]['image_url']['url']\\n data = url.split(',')[1]\\n with open('/tmp/tracker_card.png','wb') as f:\\n f.write(base64.b64decode(data))\\n print('Saved: /tmp/tracker_card.png')\\nelse:\\n print(f'Error: {json.dumps(d.get(\\\\\\\"error\\\\\\\",{}), indent=2)[:300]}')\\n\\\"\\n```\\n\\n## Fallback: Nano Banana 2\\n\\n```bash\\n# Same curl structure, different model:\\n\\\"model\\\": \\\"google/gemini-3.1-flash-image-preview\\\"\\n# Prompts should be shorter, less text-heavy\\n```\\n\\n## AIPAC Tracker Design Spec\\n\\n**Red cards** (exposing pro-lobby politicians):\\n- Grayscale candidate photo/silhouette on LEFT (45%)\\n- Dark crimson/smoky red background filling ENTIRE card\\n- GIANT white dollar amount on RIGHT (55%) — the \\\"glowing number\\\"\\n- Label: \\\"[LOBBY NAME] TOTAL\\\" in uppercase\\n- Bullet points with specific funding sources\\n- Footer: \\\"TRACKER — [COUNTRY] 🇦🇷\\\"\\n\\n**Green cards** (endorsed/clean candidates):\\n- Same layout but green background\\n- Shows $0 or minimal lobby funding\\n- \\\"REJECTS [LOBBY] CASH\\\" label\\n\\n## GPT Image 2 Sports Magazine Villain Style (May 2026)\\n\\nFor maximum visual impact, use the sports signing poster aesthetic (Lautaro Martinez Inter Milan style). GPT Image 2 excels here. Key elements:\\n\\n- **HIGH ANGLE** perspective — camera above, looking down (they're beneath us)\\n- **ELECTRIC RED LIGHTNING** bolts across dark crimson background\\n- **VILLAIN ENERGY** — grayscale silhouette, red rim lighting, no eye contact, caught-in-the-act\\n- **SPORTS POSTER TYPOGRAPHY** — massive bold names, glossy white stat numbers\\n- **4:5 vertical** aspect ratio (best for Twitter/Instagram)\\n- **Glossy magazine texture**, cinematic god rays, volumetric fog\\n\\nPrompt template:\\n```\\nSports magazine cover political tracker card, 4:5 vertical.\\nHIGH ANGLE looking DOWN — ominous villain energy.\\nDeep blood-red background with ELECTRIC RED LIGHTNING,\\ncinematic fog, glossy magazine texture.\\nSilhouette of suited politician, grayscale, high angle, red rim-lit.\\nBold white sports fonts. Top: \\\"LOBBY TRACKER ARGENTINA 🇦🇷\\\"\\nMassive: \\\"[LAST NAME]\\\". Above: \\\"[FIRST NAME]\\\"\\nGiant glossy: \\\"$[AMOUNT]+\\\". Label: \\\"[LOBBY] TOTAL\\\"\\nBottom lines: \\\"[FACT 1] | [FACT 2] | [FACT 3]\\\"\\nPhotorealistic editorial sports magazine cover. Barcode. Date stamp.\\n```\\n\\n## Collectible Card Format (May 2026 iteration)\\n\\nAfter user feedback, evolved from book-cover to **collectible trading card** style:\\n- **NO borders or book frames** — clean card edges with subtle glow\\n- **QR code** (bottom right) with \\\"ESCANEAR PARA VER CONEXIONES\\\" — links to full connections website at lobby-tracker URL\\n- **6+ stats bullet points** — not just 3, include all relevant facts\\n- **Both ARS and USD** — always convert using historical blue dollar rates (see table below)\\n- **Footer URL**: website domain\\n- **Key lesson**: Do NOT over-control the prompt. V6 failed because too many constraints killed GPT Image 2's creative visual metaphors (obelisk, Israeli flag, money stacks, contract papers). The V5 prompt let GPT be creative and it delivered excellence. Only tweak ONE thing at a time (e.g. spacing).\\n\\n## jq Extraction Trick (faster than Python for large responses)\\n\\n```bash\\n# For 2MB+ responses, jq is faster than Python's json module:\\njq -r '.choices[0].message.images[0].image_url.url' /tmp/card.json | cut -d, -f2 | base64 -d > /tmp/output.png\\n```\\n\\n## Currency Conversion: Argentina Blue Dollar\\n\\nALWAYS convert ARS amounts to USD using the historical \\\"dólar blue\\\" rate for the transaction date.\\n\\n| Year | Blue Dollar Range | Midpoint |\\n|---|---|---|\\n| 2021 | $141 - $208 | ~$180 ARS/USD |\\n| 2022 | $200 - $346 | ~$280 ARS/USD |\\n| June 2022 | ~$240 | ~$240 ARS/USD |\\n| 2023 | $346 - $1,025 | ~$600 ARS/USD |\\n\\nFormat: `ARS $2.400.000.000+` / `≈ USD $8.000.000+`\\nSources: cotizacion-dolar.com.ar, bloomberglinea.com\\n\\n## Card Evolution History\\n\\nThis documents the iterative feedback loop — useful for future card generation to avoid repeated mistakes:\\n\\n1. **V1 (Nano Banana Pro)**: Generic dark infographic, 4-square grid → **REJECTED**. \\\"No se parece en NADA a AIPAC Tracker.\\\"\\n2. **V2 (Nano Banana 2)**: Red card, silhouette, dollar amount → **MISSED (wasn't delivered)**. Too flat, lacked punch.\\n3. **V3 (GPT Image 2)**: Red card with stats, barcode → **REJECTED**. \\\"Le falta ese punch típico de imagen2.\\\"\\n4. **V4 (GPT Image 2)**: Sports magazine cover, cinematic, silhouette, high angle → **APPROACH CORRECT**. User said \\\"Va queriendo. La posición del personaje y su forma es excelente.\\\"\\n5. **V5 (GPT Image 2)**: Collectible card, no borders, QR, ARS+USD, 6 stats, villain energy, high angle, electric lightning, obelisk + Israeli flag visual metaphors → **FINAL DESIGN — APPROVED**. User said \\\\\\\"Excelente. Me encanta. Podes manejar un poco mejor el posicionamiento de las cosas.\\\\\\\"\\n6. **V6 (GPT Image 2)**: Attempted to fix text spacing but OVER-CONTROLLED the prompt → **REJECTED**. Lost creative visual elements (obelisk, flag, money). User: \\\\\\\"Donde esta el obelisco la bandera de Israel qué estaba en la otra imagen, el contrato y los dolares, le quedaba muy bien! La cagaste con la última imagen.\\\\\\\"\\n7. **V7 (GPT Image 2)**: Restored original V5 prompt, only added spacing + \\\\\\\"let the model be creative with visual metaphors\\\\\\\" → **FINAL APPROVED.** User: \\\\\\\"Hermoso. Ya estamos con el diseño. Dejalo fijo así.\\\\\\\"\\n\\nKey learnings across iterations:\\n- GPT Image 2 >> Nano Banana for this use case\\n- Magazine sports cover aesthetic > flat infographic\\n- HIGH ANGLE villain perspective resonated strongly\\n- Always include BOTH ARS and USD\\n- QR code > barcode (functional purpose)\\n- Collectible trading card > book layout\\n- 6+ detailed stats > 3 bullet points\\n- **CRITICAL: Do NOT over-control the prompt.** V6 was worse because too many layout constraints killed GPT's creativity. Let the model add visual metaphors (obelisk, flag, money, papers). Only change ONE thing per iteration.\\n\\n## Animating Tracker Cards into GIF/MP4\\n\\nUse this sub-workflow when the user asks to animate an existing political tracker card, make an impact GIF/video for a detail page/social post, or mimic the mood of a reference short without relying on the original video file.\\n\\n### Preferred input order\\n\\n1. **Use the approved source image** if present (the exact card/poster the user liked).\\n2. If the exact image is missing, recover it from likely paths before asking:\\n - `~/.hermes/image_cache/`\\n - `/tmp/` (`nano_card.png`, `gpt2_*.json`, `tracker_card.png`, etc.)\\n - session logs with `session_search` or direct `~/.hermes/sessions/*` search for `MEDIA:`, `data:image`, `gpt2_v`, `Hermoso`, `obelisco`, `bandera`.\\n3. If still missing, use a project screenshot or current site card as a temporary demo only, and tell the user the exact image will produce a better result.\\n\\n### When YouTube/Shorts download is blocked\\n\\nYouTube Shorts often fail from Oracle/datacenter IPs with `Sign in to confirm you’re not a bot`, even with fresh `yt-dlp`. Try the standard fast path first:\\n\\n```bash\\npython3 -m venv /tmp/ytdlpvenv\\n/tmp/ytdlpvenv/bin/pip install -q -U yt-dlp\\n/tmp/ytdlpvenv/bin/yt-dlp --no-playlist --force-ipv4 \\\\\\n --extractor-args 'youtube:player_client=web_creator,ios' \\\\\\n -f 'bv*[height<=720]+ba/b[height<=720]/best' \\\\\\n -o '/tmp/reference_short.%(ext)s' 'https://youtube.com/shorts/VIDEO_ID'\\n```\\n\\nIf blocked, do not stall. First use YouTube oEmbed to recover basic metadata/thumbnail/title for style clues without downloading the video:\\n\\n```bash\\ncurl -sS 'https://www.youtube.com/oembed?url=https://www.youtube.com/shorts/VIDEO_ID&format=json'\\n```\\n\\nThen treat the short as a **style reference** and recreate the effect procedurally: jump cuts/glitch slices, red/blue chromatic offsets, sudden zooms, scanlines, flicker, red impact flashes, grain/VHS noise, and short-form pacing. For a CapCut/terror edit, a square or vertical card with punch zooms and 1-frame dark/red flashes can work even without the original video.\\n\\n### Procedural GIF/MP4 recipe\\n\\nA reliable no-GPU path:\\n\\n1. Ensure tools:\\n ```bash\\n python3 -m venv /tmp/gifvenv\\n /tmp/gifvenv/bin/pip install -q pillow numpy imageio\\n command -v ffmpeg\\n ```\\n If the active Hermes Python lacks `pip` or imports still fail, use the system Python path instead:\\n ```bash\\n sudo apt-get update\\n sudo apt-get install -y python3-pil python3-numpy\\n /usr/bin/python3 - <<'PY'\\n import PIL, numpy\\n print('ok')\\n PY\\n ```\\n2. Create frames with Pillow/NumPy:\\n - vertical `540x960` or `720x1280`\\n - darkened/zoomed source card or screenshot background\\n - red radial rays behind the politician/card\\n - glowing symbolic elements (flag/contract/money) as overlays\\n - card/person rising from bottom-center using ease-out cubic motion\\n - 1-3 frame glitch cuts with horizontal roll and RGB channel offsets\\n - scanlines + vignette for short-video tension\\n3. Encode both GIF and MP4:\\n ```bash\\n # GIF via Pillow for portability; keep <= ~8MB when possible\\n # MP4 is much smaller and better for web/Telegram\\n ffmpeg -y -framerate 15 -i /tmp/frames/frame_%03d.png \\\\\\n -vf 'format=yuv420p' -movflags +faststart public/larreta-impact-demo.mp4\\n ```\\n4. Verify a mid-frame with `vision_analyze` before sending.\\n\\n### OpenRouter video / Veo 3.1 motion-poster workflow\\n\\nUse this when the user asks to make a higher-impact video from a static tracker card using OpenRouter video models (e.g. `google/veo-3.1`) or wants a YouTube Shorts/Reels-style motion poster.\\n\\n1. **Survey available video models and pricing before submitting jobs**:\\n ```bash\\n set -a; . ~/.hermes/.env; set +a\\n /usr/bin/python3 - <<'PY'\\n import os, requests\\n j=requests.get('https://openrouter.ai/api/v1/videos/models',\\n headers={'Authorization':'Bearer '+os.environ['OPENROUTER_API_KEY']}, timeout=30).json()\\n for m in j['data']:\\n if 'veo' in m['id'] or 'google' in m['id']:\\n print(m['id'], m.get('supported_resolutions'), m.get('supported_aspect_ratios'),\\n m.get('supported_durations'), m.get('pricing_skus'))\\n PY\\n ```\\n As of May 2026, `google/veo-3.1` supports `/api/v1/videos` with `aspect_ratio`, `duration`, `resolution`, `generate_audio`, `frame_images`, and polling via `polling_url`. `google/veo-3.1-fast` and `google/veo-3.1-lite` are cheaper iteration options.\\n\\n2. **For image-to-video attempts**, publish the source card under `public/` first so OpenRouter can fetch it:\\n ```bash\\n cp ~/.hermes/image_cache/.jpg public/media/source-card.jpg\\n vercel --prod --yes\\n ```\\n\\n3. **Submit the job and poll**:\\n ```python\\n import os, json, requests, pathlib, time\\n prompt = pathlib.Path('assets/video-ref/veo_prompt.txt').read_text()\\n payload = {\\n 'model': 'google/veo-3.1',\\n 'prompt': prompt,\\n 'aspect_ratio': '9:16',\\n 'duration': 8,\\n 'resolution': '720p',\\n 'generate_audio': False,\\n 'frame_images': [{\\n 'type': 'image_url',\\n 'frame_type': 'first_frame',\\n 'image_url': {'url': 'https:///media/source-card.jpg'}\\n }]\\n }\\n r = requests.post('https://openrouter.ai/api/v1/videos',\\n headers={'Authorization':'Bearer '+os.environ['OPENROUTER_API_KEY'], 'Content-Type':'application/json'},\\n json=payload, timeout=60)\\n r.raise_for_status()\\n polling_url = r.json()['polling_url']\\n # GET polling_url with the same Authorization header until status is completed/failed.\\n # Download returned content URLs WITH Authorization header; unsigned_urls may still require auth.\\n ```\\n\\n4. **If Veo/Vertex filters image-to-video with real politicians or sensitive poster text**, do not burn repeated full-price retries. Use a two-layer approach:\\n - Generate a neutral 9:16 red/black investigative **motion background** with no real names, no readable political text, no real people, no claims.\\n - Composite the approved card/poster locally on top with Pillow/ffmpeg, preserving the exact source image and adding zoom pulses, shake, scanlines, RGB split, glitch bars, and subtitles.\\n - This keeps the factual poster unchanged while using Veo only for cinematic motion texture.\\n\\n Safe background prompt pattern:\\n ```text\\n Create an 8-second vertical 9:16 motion-poster video for a dark investigative documentary teaser. Red-and-black editorial thriller, polished YouTube Shorts/CapCut-style glitch edit. A stylized graphic poster fills the frame: a stern adult male figure in a dark suit is centered in shadow, surrounded by abstract documents, money-like paper shapes, a city monument silhouette, and a dark flag-like graphic background. Bold white headline blocks are abstract poster typography. Do not render readable real names, numbers, logos, political claims, country names, or QR codes. Slow cinematic push-in, three hard zoom-punch beats, red lightning flicker, parallax, VHS grain, scanlines, chromatic aberration, horizontal glitch bars, micro camera shake, red flash frames, final one-second hold for loop. No gore, no weapons, no physical harm, no real people, no readable political text.\\n ```\\n\\n5. **Composite locally**:\\n - Decode Veo MP4 frames with `ffmpeg -i veo-bg.mp4 /tmp/bg/frame_%04d.png`.\\n - Place the approved poster/card centered over the background; for vertical videos, keep the card around `690x690` on a `720x1280` canvas.\\n - Use slow push-in plus beat pulses around `1.5s`, `4.0s`, `6.2s`.\\n - Add subtitle/CTA only if desired; avoid adding any new factual claims.\\n - Export MP4 for web and a smaller GIF for previews.\\n\\n6. **Verify**:\\n - Create a contact sheet from 3-4 frames and run `vision_analyze` for cropping/readability.\\n - `ffprobe` the MP4 and `curl` deployed asset URLs.\\n\\n### OpenRouter/content-policy fallback\\n\\nImage generation/editing/video prompts using real politicians + ominous language + national/religious symbols may return `PROHIBITED_CONTENT`, Vertex usage-guideline errors, or “completed with no output (content may have been filtered)”. If that happens:\\n\\n- Do **not** keep retrying the same prompt.\\n- For static image generation/editing: use the already-approved/static card as the source and animate locally.\\n- For Veo/video: generate a neutral motion background with no real names/claims/readable political text, then composite the approved card locally.\\n- Keep the visual editorial, not defamatory: labels should reflect the project’s documented tracker framing, while evidence claims remain on the site/DB.\\n\\n### Integration note\\n\\nFor a Next.js project, save assets under `public/` so they can be referenced as `/larreta-impact-demo.gif` or `/larreta-impact-demo.mp4`. Prefer MP4 in the page for size/performance, with GIF for chat previews.\\n\\n## Pitfalls\\n\\n- **GPT Image 2 timeout**: use `--max-time 300` minimum; the model renders slowly (sometimes 60-120s)\\n- **Base64 decoding**: output is `data:image/png;base64,...` — split on comma, decode part [1]\\n- **Large responses**: A 2.3MB response JSON takes ~10s to base64 decode — use heredoc Python, not one-liner\\n- **Nano Banana timeout**: even slower than GPT Image 2; reduce prompt complexity\\n- **Text hallucination**: ALWAYS verify generated text with vision_analyze before sending to user\\n- **OpenRouter routing**: GPT Image 2 requires OpenAI API key configured in OpenRouter; Nano Banana works with Google AI keys\\n- **Empty curl responses**: If curl times out, check file size (0 bytes = curl failed, retry)\\n- **Exact approved image missing**: search caches/session logs first; if unavailable, create a demo from a site screenshot but clearly ask for the exact image for final quality.\\n- **GIF size**: vertical GIFs get large quickly; also export MP4 because it is usually 10-50x smaller.\\n- **Hermes venv may not have pip/Pillow**: if `python3 -m pip` says `No module named pip` or Pillow imports fail, install `python3-pil python3-numpy` with apt and run generation scripts with `/usr/bin/python3`.\\n- **Font path drift**: `DejaVuSansCondensed-Bold.ttf` may not exist; search `/usr/share/fonts/**/*.ttf` and fall back to `/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf`.\\n- **Short download blocked**: use oEmbed metadata for title/thumbnail/context, then recreate the style locally rather than waiting on yt-dlp/CDP.\\n\", \"path\": \"political-tracker-card/SKILL.md\", \"skill_dir\": \"/home/ubuntu/.hermes/skills/political-tracker-card\", \"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\"}", "tool_call_id": "call_aLhStFB4ow4C7oJxd3j1WWLF" }, { "role": "tool", "content": "{\"success\": true, \"name\": \"youtube-content\", \"description\": \"YouTube transcripts to summaries, threads, blogs.\", \"tags\": [], \"related_skills\": [], \"content\": \"---\\nname: youtube-content\\ndescription: \\\"YouTube transcripts to summaries, threads, blogs.\\\"\\n---\\n\\n# YouTube Content Tool\\n\\n## When to use\\n\\nUse when the user shares a YouTube URL or video link, asks to summarize a video, requests a transcript, or wants to extract and reformat content from any YouTube video. Transforms transcripts into structured content (chapters, summaries, threads, blog posts).\\n\\nExtract transcripts from YouTube videos and convert them into useful formats.\\n\\n## Setup\\n\\n```bash\\npip install youtube-transcript-api\\n```\\n\\n## Helper Script\\n\\n`SKILL_DIR` is the directory containing this SKILL.md file. The script accepts any standard YouTube URL format, short links (youtu.be), shorts, embeds, live links, or a raw 11-character video ID.\\n\\n```bash\\n# JSON output with metadata\\npython3 SKILL_DIR/scripts/fetch_transcript.py \\\"https://youtube.com/watch?v=VIDEO_ID\\\"\\n\\n# Plain text (good for piping into further processing)\\npython3 SKILL_DIR/scripts/fetch_transcript.py \\\"URL\\\" --text-only\\n\\n# With timestamps\\npython3 SKILL_DIR/scripts/fetch_transcript.py \\\"URL\\\" --timestamps\\n\\n# Specific language with fallback chain\\npython3 SKILL_DIR/scripts/fetch_transcript.py \\\"URL\\\" --language tr,en\\n```\\n\\n## Output Formats\\n\\nAfter fetching the transcript, format it based on what the user asks for:\\n\\n- **Chapters**: Group by topic shifts, output timestamped chapter list\\n- **Summary**: Concise 5-10 sentence overview of the entire video\\n- **Chapter summaries**: Chapters with a short paragraph summary for each\\n- **Thread**: Twitter/X thread format — numbered posts, each under 280 chars\\n- **Blog post**: Full article with title, sections, and key takeaways\\n- **Quotes**: Notable quotes with timestamps\\n\\n### Example — Chapters Output\\n\\n```\\n00:00 Introduction — host opens with the problem statement\\n03:45 Background — prior work and why existing solutions fall short\\n12:20 Core method — walkthrough of the proposed approach\\n24:10 Results — benchmark comparisons and key takeaways\\n31:55 Q&A — audience questions on scalability and next steps\\n```\\n\\n## Workflow\\n\\n1. **Fetch** the transcript using the helper script with `--text-only --timestamps`.\\n2. **Validate**: confirm the output is non-empty and in the expected language. If empty, retry without `--language` to get any available transcript. If still empty, tell the user the video likely has transcripts disabled.\\n3. **Chunk if needed**: if the transcript exceeds ~50K characters, split into overlapping chunks (~40K with 2K overlap) and summarize each chunk before merging.\\n4. **Transform** into the requested output format. If the user did not specify a format, default to a summary.\\n5. **Verify**: re-read the transformed output to check for coherence, correct timestamps, and completeness before presenting.\\n\\n## Error Handling\\n\\n- **Transcript disabled**: tell the user; suggest they check if subtitles are available on the video page.\\n- **Private/unavailable video**: relay the error and ask the user to verify the URL.\\n- **No matching language**: retry without `--language` to fetch any available transcript, then note the actual language to the user.\\n- **Dependency missing**: run `pip install youtube-transcript-api` and retry.\\n\", \"path\": \"media/youtube-content/SKILL.md\", \"skill_dir\": \"/home/ubuntu/.hermes/skills/media/youtube-content\", \"linked_files\": {\"references\": [\"references/output-formats.md\"], \"scripts\": [\"scripts/fetch_transcript.py\"]}, \"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\"}", "tool_call_id": "call_thf081vEQLLDvvTNgW7C9FfM" }, { "role": "tool", "content": "{\"success\": true, \"name\": \"gif-search\", \"description\": \"Search/download GIFs from Tenor via curl + jq.\", \"tags\": [\"GIF\", \"Media\", \"Search\", \"Tenor\", \"API\"], \"related_skills\": [], \"content\": \"---\\nname: gif-search\\ndescription: \\\"Search/download GIFs from Tenor via curl + jq.\\\"\\nversion: 1.1.0\\nauthor: Hermes Agent\\nlicense: MIT\\nprerequisites:\\n env_vars: [TENOR_API_KEY]\\n commands: [curl, jq]\\nmetadata:\\n hermes:\\n tags: [GIF, Media, Search, Tenor, API]\\n---\\n\\n# GIF Search (Tenor API)\\n\\nSearch and download GIFs directly via the Tenor API using curl. No extra tools needed.\\n\\n## When to use\\n\\nUseful for finding reaction GIFs, creating visual content, and sending GIFs in chat.\\n\\n## Setup\\n\\nSet your Tenor API key in your environment (add to `~/.hermes/.env`):\\n\\n```bash\\nTENOR_API_KEY=your_key_here\\n```\\n\\nGet a free API key at https://developers.google.com/tenor/guides/quickstart — the Google Cloud Console Tenor API key is free and has generous rate limits.\\n\\n## Prerequisites\\n\\n- `curl` and `jq` (both standard on macOS/Linux)\\n- `TENOR_API_KEY` environment variable\\n\\n## Search for GIFs\\n\\n```bash\\n# Search and get GIF URLs\\ncurl -s \\\"https://tenor.googleapis.com/v2/search?q=thumbs+up&limit=5&key=${TENOR_API_KEY}\\\" | jq -r '.results[].media_formats.gif.url'\\n\\n# Get smaller/preview versions\\ncurl -s \\\"https://tenor.googleapis.com/v2/search?q=nice+work&limit=3&key=${TENOR_API_KEY}\\\" | jq -r '.results[].media_formats.tinygif.url'\\n```\\n\\n## Download a GIF\\n\\n```bash\\n# Search and download the top result\\nURL=$(curl -s \\\"https://tenor.googleapis.com/v2/search?q=celebration&limit=1&key=${TENOR_API_KEY}\\\" | jq -r '.results[0].media_formats.gif.url')\\ncurl -sL \\\"$URL\\\" -o celebration.gif\\n```\\n\\n## Get Full Metadata\\n\\n```bash\\ncurl -s \\\"https://tenor.googleapis.com/v2/search?q=cat&limit=3&key=${TENOR_API_KEY}\\\" | jq '.results[] | {title: .title, url: .media_formats.gif.url, preview: .media_formats.tinygif.url, dimensions: .media_formats.gif.dims}'\\n```\\n\\n## API Parameters\\n\\n| Parameter | Description |\\n|-----------|-------------|\\n| `q` | Search query (URL-encode spaces as `+`) |\\n| `limit` | Max results (1-50, default 20) |\\n| `key` | API key (from `$TENOR_API_KEY` env var) |\\n| `media_filter` | Filter formats: `gif`, `tinygif`, `mp4`, `tinymp4`, `webm` |\\n| `contentfilter` | Safety: `off`, `low`, `medium`, `high` |\\n| `locale` | Language: `en_US`, `es`, `fr`, etc. |\\n\\n## Available Media Formats\\n\\nEach result has multiple formats under `.media_formats`:\\n\\n| Format | Use case |\\n|--------|----------|\\n| `gif` | Full quality GIF |\\n| `tinygif` | Small preview GIF |\\n| `mp4` | Video version (smaller file size) |\\n| `tinymp4` | Small preview video |\\n| `webm` | WebM video |\\n| `nanogif` | Tiny thumbnail |\\n\\n## Notes\\n\\n- URL-encode the query: spaces as `+`, special chars as `%XX`\\n- For sending in chat, `tinygif` URLs are lighter weight\\n- GIF URLs can be used directly in markdown: `![alt](url)`\\n\", \"path\": \"media/gif-search/SKILL.md\", \"skill_dir\": \"/home/ubuntu/.hermes/skills/media/gif-search\", \"linked_files\": null, \"usage_hint\": null, \"required_environment_variables\": [{\"name\": \"TENOR_API_KEY\", \"prompt\": \"Enter value for TENOR_API_KEY\"}], \"required_commands\": [], \"missing_required_environment_variables\": [\"TENOR_API_KEY\"], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": true, \"setup_skipped\": false, \"readiness_status\": \"setup_needed\", \"setup_note\": \"Setup needed before using this skill: missing env $TENOR_API_KEY.\", \"metadata\": {\"hermes\": {\"tags\": [\"GIF\", \"Media\", \"Search\", \"Tenor\", \"API\"]}}}", "tool_call_id": "call_c8u5e0DBSbJKYjFDkkL7Dij7" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94ryRQ2ZdMjbcfFZ5Z9fwhR77umIh1bmCTEU3jSNYXZof_5Um85kI3Ss9hcDcHbVRHFvYXk8neLeYlX0eGrR5FtkxC73TZ-5rxkx6F2_TJU4GmQUUdWJfhNUhnAk-B2d8k7mgTZTw-6UlChLbPfUkUL8sAq0kCeXxH5TFItURujf7T4fWoh2NFUKFvkgKGmF7YIq0QKtPqVu679E-sssmC_orAuPvMHf39pC5jPcR92ycFXk8GQH-0WYA9585zd897iH5_xklvpwO7b_VcwgazztFkI8X96fS2tILFpyoklzpkvkWjcWT1GXbSIRCffzJeUkxAYZMldxhZguC-5PC_hjUNlzSvYOV8EqrJ_T50yBTtJsZjopKMqsxNw6seMaHdPFZX9AB8IAeK0phrO9-ytk8dvD7UPBbsIlW3l0HuyEDGfdn-2UfgPuhsCRjUMrmV44X8b4-wUZ7_1hsxQgEU_2Ba9iSgLTwhjk-sD09xo6lWk0W0m77cm_pBcdoiJitMMkMr6E0531CcfSMmaPO09VnSPYR2daNTpcrmR3tiz7ucMuAdQDvWmE5Xp3oBxvuRupyX2L-TEoLDxErXA94DYUg9qJr7OarBUQet1xXYWYDBbWZly6n-49R-iZrIqohvzbqDCU4d1_3OymFb8--ohfaylF16UtHiy-pIdcHw3PxqzUAM9YtGgxPf7CmqgJW3Q0k5Aodh71D-sfuwX5JUOrfrRPuRR2JYocuAzNkUvbMVOLgWcikn9xFLjBSMT4vjHfWsoABd_GwZ6SLbAmolCAz1Cfoc2UfhPcTI7ysCjAkN_ae0QSTMLrxRgqJv4IXC59U-avpByZvmXuB5DTEVdeHBvTnAdcMgvlY6LRsOZ8Ruj0ItxySUn-xMQOPuNIkSVGkmCsxJlRPXRlpPJtyTDV1aXQVaKeZnAaof3EqDOoGChBWUKplcL_ogKyWwY3hNkBhBtFGhHn1HypsavHY7i3gtOc4q5h-HPL4VK4jjnFf0D9_ufl1UsRldXqnGWaJktTolDdKpjTHJHW5Y4o9E4D1YUDjLnRhcE6h59chFCPifghxnIEyLBeoe5rtpD1nFc0qEPyAfqzTr23ok6sy5Typv98Im3oQuHHlb-cmH4v97ZV4pu-veLuidCg2xfpg_rzEia_BbCb8mlp1wrlLR_oG29Ned5_SA0_Wo0NRBz8mHq0s4MW8Gvy6MfRsfOG3Yx0ZYX1nvRVXFm1P2APA3d2U_ODsQ_0-hRc2cfkpSM2UA56v2tT7Q1TmfeojTp1twgP_dObXilJsPNGi4gg4RWy5V8lETw7j69FRBOeg4_ZilQDT_lGMKf3-A8D9D_Xlfxo-lp99Y3s5I6kwUP35Yh44AoHx0eW5eBGtnjurK7Fyg5ah1-RKe5kmdRJs-57fZoMVe7iKyT5EWFgJzyf78Ryhxf9M8pGdnANr2cZc9d2qMHprM8JSswIQd9N5nlBiGYFo-HtSzuZ671rVhsOdZ0j3Rm_BmCi2TGtm8MFKc4UgeEzaYZ537A4OZHB1omn4Y38SP3jsetT5_IiCYDch-9DkkemyskCdpKHUE4gXvc046YQ5eGyBR4eaLD3Nz5MGMYKkhZfdZpMlVnZWcIuCYt2K-y_2A6dmfU5lUa96eFS7ZL4O7nwQyXpHWFaKHHin-HKq8Q5PWz3p4WFATdp8KOHmketje5PP8hvg1M85UCiv4SR_w-APlGGTcx5qRwoMpqnRczwiJeuzoAYO_I_LQMPLl6a40T_dzEAHbmfr-rvxW_6G9ybBzruDmatL2M3rsTtAhvUIZJvzM4hiJWoOTGj7WqlH6yBcMnyqstsmBjhMkyP0IsRwmURkGQTEL5QDGCjuPlf-RmF-Qi4Tp1igJFqKQBubv-ct-OMmHSLCj0o1QP-clGsU_amo3USUJdjKWrDfE0APIAh8MC368OBpn57m5CyzKYHoKxLqz8G_VAaLTjXxFCONUpnpKq77XwB5XqrvUaknzQiiQX5cfeIvPYBelD5TUfekUEyTaK3PByBjQu37khbivtu5CbC24uRtckb1cmDg8arA8dhwBFiNPv4xYm_118f5Sdc9xg9fEwScjk9GsrXsc1xXNttBespftBD3MC4P7hXp5D5mYT3I2Ox46G_bisZD-XIF8HSCE37sz59qrn3BBt-H8By0orNkPWsLWYhbH75aAXiDZZ5dBWpTvIJ-N9HtGoIClisId0Lf6NREJfWse8y-n4DQQvHf7mhE9F8GidhoJ3xESNLt69bkTvr_Kj65_s4-_uGTDmSqw9YeJ0XctqapoxGA-_D4mREaGHOjq32gYh1--oZieIcG9Q1DHjfLbWrqZRwNhWizcmeiwBvnRriSOIu2QfhblyJ7Vh4CMtkKlvOmNYWJAv6dqBjxs1-nmVIfn_TxDuqVnXnjERwyIggechH8rye4OQ0Ev-lmq53uzvepovobX0OSnlUkkr01wYelbcmVNzwyUnbfGZ7KYX2LMt67rsWFXI77D-1K-cwUGuTKp1fgqz3sg==", "id": "rs_0bb8ef1f39b62dbe0169f78aee125c81988f75b2a88a01a68f", "summary": [] } ], "tool_calls": [ { "id": "call_DvmJzj5r21NJeXvyKeY2jjRe", "call_id": "call_DvmJzj5r21NJeXvyKeY2jjRe", "response_item_id": "fc_0bb8ef1f39b62dbe0169f78af299248198bf450d091a6f205e", "type": "function", "function": { "name": "skill_manage", "arguments": "{\"action\":\"write_file\",\"name\":\"political-tracker-card\",\"file_path\":\"scripts/make_impact_animation.py\",\"file_content\":\"#!/usr/bin/env python3\\n\\\"\\\"\\\"Generate a terror/glitch social-media MP4 + GIF from a static tracker card/poster.\\n\\nUsage:\\n python3 make_impact_animation.py --input card.jpg --out-dir public/media --slug larreta-impact\\n\\nRequires: ffmpeg, python3-pil, python3-numpy (or Pillow/numpy in the active Python).\\nOutputs:\\n /.mp4 (preferred for web/Telegram)\\n /.gif (preview/fallback; larger)\\n\\\"\\\"\\\"\\nfrom __future__ import annotations\\nfrom PIL import Image, ImageEnhance, ImageFilter, ImageDraw\\nimport argparse, math, pathlib, random, subprocess\\nimport numpy as np\\n\\n\\ndef ease_out_cubic(x: float) -> float:\\n return 1 - (1 - x) ** 3\\n\\n\\ndef rgb_split(im: Image.Image, amt: int) -> Image.Image:\\n if amt <= 0:\\n return im\\n arr = np.array(im.convert(\\\"RGB\\\"))\\n out = np.zeros_like(arr)\\n out[:, :, 0] = np.roll(arr[:, :, 0], amt, axis=1)\\n out[:, :, 1] = arr[:, :, 1]\\n out[:, :, 2] = np.roll(arr[:, :, 2], -amt, axis=1)\\n return Image.fromarray(out)\\n\\n\\ndef add_scanlines(im: Image.Image, alpha: int = 22) -> Image.Image:\\n overlay = Image.new(\\\"RGBA\\\", im.size, (0, 0, 0, 0))\\n d = ImageDraw.Draw(overlay)\\n for y in range(0, im.height, 4):\\n d.line([(0, y), (im.width, y)], fill=(0, 0, 0, alpha), width=1)\\n return Image.alpha_composite(im.convert(\\\"RGBA\\\"), overlay)\\n\\n\\ndef red_grade(im: Image.Image, strength: float = 1.0) -> Image.Image:\\n arr = np.array(im.convert(\\\"RGB\\\")).astype(np.float32)\\n arr[:, :, 0] *= 1.12 + 0.10 * strength\\n arr[:, :, 1] *= 0.86\\n arr[:, :, 2] *= 0.82\\n return Image.fromarray(np.clip(arr, 0, 255).astype(np.uint8))\\n\\n\\ndef add_vignette(im: Image.Image) -> Image.Image:\\n w, h = im.size\\n arr = np.array(im.convert(\\\"RGBA\\\")).astype(np.float32)\\n yy, xx = np.mgrid[0:h, 0:w]\\n dist = np.sqrt(((xx - w / 2) / (w / 2)) ** 2 + ((yy - h / 2) / (h / 2)) ** 2)\\n mask = np.clip(1 - (dist - 0.25) * 0.72, 0.38, 1.0)\\n arr[:, :, :3] *= mask[:, :, None]\\n return Image.fromarray(np.clip(arr, 0, 255).astype(np.uint8), \\\"RGBA\\\")\\n\\n\\ndef main() -> None:\\n ap = argparse.ArgumentParser()\\n ap.add_argument(\\\"--input\\\", required=True, help=\\\"Source card/poster image\\\")\\n ap.add_argument(\\\"--out-dir\\\", default=\\\"public/media\\\")\\n ap.add_argument(\\\"--slug\\\", default=\\\"impact-short\\\")\\n ap.add_argument(\\\"--width\\\", type=int, default=720)\\n ap.add_argument(\\\"--height\\\", type=int, default=1280)\\n ap.add_argument(\\\"--fps\\\", type=int, default=15)\\n ap.add_argument(\\\"--duration\\\", type=float, default=4.2)\\n args = ap.parse_args()\\n\\n src_path = pathlib.Path(args.input)\\n out_dir = pathlib.Path(args.out_dir)\\n frames_dir = out_dir / f\\\"{args.slug}-frames\\\"\\n frames_dir.mkdir(parents=True, exist_ok=True)\\n out_dir.mkdir(parents=True, exist_ok=True)\\n mp4 = out_dir / f\\\"{args.slug}.mp4\\\"\\n gif = out_dir / f\\\"{args.slug}.gif\\\"\\n w, h, fps = args.width, args.height, args.fps\\n n = int(fps * args.duration)\\n random.seed(7)\\n\\n src = Image.open(src_path).convert(\\\"RGB\\\")\\n card_w = int(w * 0.958)\\n card_h = int(card_w * src.height / src.width)\\n card_base = src.resize((card_w, card_h), Image.Resampling.LANCZOS)\\n\\n bg = src.resize((w, int(w * src.height / src.width)), Image.Resampling.LANCZOS)\\n if bg.height < h:\\n bg = src.resize((int(h * src.width / src.height), h), Image.Resampling.LANCZOS)\\n bg = bg.crop(((bg.width - w) // 2, (bg.height - h) // 2, (bg.width + w) // 2, (bg.height + h) // 2))\\n bg = bg.filter(ImageFilter.GaussianBlur(16))\\n\\n beats = [0.55, 1.35, 2.45, 3.35]\\n flash_frames = {int(b * fps) for b in beats} | {int(b * fps) + 1 for b in beats}\\n glitch_frames = {int(b * fps) + off for b in beats for off in (-1, 0, 1)}\\n\\n for i in range(n):\\n t = i / max(1, n - 1)\\n sec = i / fps\\n zoom = 1.0 + 0.10 * t\\n for b in beats:\\n pulse = max(0, 1 - abs(sec - b) / 0.13)\\n zoom += 0.055 * pulse\\n shake = 2 + (10 if any(abs(sec - b) < 0.11 for b in beats) else 0)\\n dx, dy = random.randint(-shake, shake), random.randint(-shake, shake)\\n\\n canvas = Image.new(\\\"RGB\\\", (w, h), (12, 0, 0))\\n bg_frame = ImageEnhance.Brightness(ImageEnhance.Contrast(red_grade(bg)).enhance(1.28)).enhance(0.55)\\n canvas.paste(bg_frame, (0, 0))\\n frame = canvas.convert(\\\"RGBA\\\")\\n\\n overlay = Image.new(\\\"RGBA\\\", (w, h), (0, 0, 0, 0))\\n d = ImageDraw.Draw(overlay)\\n for k in range(10):\\n ang = (k / 10) * math.tau + 0.4 * math.sin(sec * 2)\\n d.line([(w / 2, h / 2), (w / 2 + math.cos(ang) * 780, h / 2 + math.sin(ang) * 780)], fill=(255, 0, 0, 22), width=8)\\n frame = Image.alpha_composite(frame, overlay)\\n\\n cw, ch = int(card_w * zoom), int(card_h * zoom)\\n card = card_base.resize((cw, ch), Image.Resampling.LANCZOS)\\n card = ImageEnhance.Sharpness(ImageEnhance.Contrast(card).enhance(1.05)).enhance(1.12)\\n enter = ease_out_cubic(min(1, sec / 0.85))\\n x = (w - cw) // 2 + dx\\n y_final = int(h * 0.105) - int(65 * t)\\n y = int(h + 80 - (h + 80 - y_final) * enter) + dy\\n\\n shadow = Image.new(\\\"RGBA\\\", (cw + 50, ch + 50), (0, 0, 0, 0))\\n ImageDraw.Draw(shadow).rounded_rectangle([20, 20, cw + 30, ch + 30], radius=18, fill=(255, 0, 0, 70))\\n frame.alpha_composite(shadow.filter(ImageFilter.GaussianBlur(20)), (x - 25, y - 25))\\n frame.paste(card.convert(\\\"RGBA\\\"), (x, y))\\n\\n if i in flash_frames:\\n frame = Image.alpha_composite(frame, Image.new(\\\"RGBA\\\", (w, h), (255, 0, 0, 82)))\\n if i in {f + 2 for f in flash_frames}:\\n frame = Image.alpha_composite(frame, Image.new(\\\"RGBA\\\", (w, h), (0, 0, 0, 120)))\\n if i in glitch_frames:\\n frame = rgb_split(frame, random.randint(6, 16)).convert(\\\"RGBA\\\")\\n arr = np.array(frame)\\n for _ in range(8):\\n yy = random.randint(0, h - 28)\\n hh = random.randint(8, 28)\\n arr[yy:yy + hh] = np.roll(arr[yy:yy + hh], random.randint(-45, 45), axis=1)\\n frame = Image.fromarray(arr, \\\"RGBA\\\")\\n\\n arr = np.array(frame).astype(np.int16)\\n arr[:, :, :3] = np.clip(arr[:, :, :3] + np.random.normal(0, 7, arr.shape[:2])[:, :, None], 0, 255)\\n frame = add_vignette(add_scanlines(Image.fromarray(arr.astype(np.uint8), \\\"RGBA\\\")))\\n frame.convert(\\\"RGB\\\").save(frames_dir / f\\\"frame_{i:03d}.png\\\", quality=95)\\n\\n subprocess.run([\\\"ffmpeg\\\", \\\"-y\\\", \\\"-framerate\\\", str(fps), \\\"-i\\\", str(frames_dir / \\\"frame_%03d.png\\\"), \\\"-vf\\\", \\\"format=yuv420p\\\", \\\"-movflags\\\", \\\"+faststart\\\", \\\"-crf\\\", \\\"18\\\", str(mp4)], check=True)\\n palette = \\\"/tmp/impact_palette.png\\\"\\n subprocess.run([\\\"ffmpeg\\\", \\\"-y\\\", \\\"-i\\\", str(mp4), \\\"-vf\\\", \\\"fps=12,scale=480:-1:flags=lanczos,palettegen\\\", palette], check=True)\\n subprocess.run([\\\"ffmpeg\\\", \\\"-y\\\", \\\"-i\\\", str(mp4), \\\"-i\\\", palette, \\\"-filter_complex\\\", \\\"fps=12,scale=480:-1:flags=lanczos[x];[x][1:v]paletteuse=dither=bayer:bayer_scale=3\\\", str(gif)], check=True)\\n print(mp4)\\n print(gif)\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\"}" } } ] }, { "role": "tool", "content": "{\"success\": true, \"message\": \"File 'scripts/make_impact_animation.py' written to skill 'political-tracker-card'.\", \"path\": \"/home/ubuntu/.hermes/skills/political-tracker-card/scripts/make_impact_animation.py\"}", "tool_call_id": "call_DvmJzj5r21NJeXvyKeY2jjRe" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_kgnl2S3jFQFBO4QBmsm3uOiL", "call_id": "call_kgnl2S3jFQFBO4QBmsm3uOiL", "response_item_id": "fc_0bb8ef1f39b62dbe0169f78b2293bc8198bf83b4352bfeaac2", "type": "function", "function": { "name": "skill_manage", "arguments": "{\"action\":\"patch\",\"name\":\"political-tracker-card\",\"old_string\":\"## Fallback: Nano Banana 2\\n\\n```bash\\n# Same curl structure, different model:\\n\\\"model\\\": \\\"google/gemini-3.1-flash-image-preview\\\"\\n# Prompts should be shorter, less text-heavy\\n```\\n\\n## AIPAC Tracker Design Spec\",\"new_string\":\"## Image-to-image from an approved/reference card\\n\\nUse this when the user attaches or points to an approved visual direction and complains the generated cards are too flat/generic. Send the reference image as `image_url` content to GPT Image 2 and explicitly say it is the **primary visual reference**. This preserves the high-impact composition better than trying to recreate it from text alone.\\n\\n```python\\nimport os, base64, pathlib, requests\\nsrc = pathlib.Path('/home/ubuntu/.hermes/image_cache/.jpg')\\nimg_b64 = base64.b64encode(src.read_bytes()).decode()\\nprompt = '''Use the attached image as the PRIMARY VISUAL REFERENCE. Create a new 4:5 vertical hyperrealistic political investigative poster/card. Preserve the same punch: red storm sky, electric lightning, Buenos Aires Obelisco, relevant flag/background symbolism, dollars, contract papers, central suited politician, glossy magazine-cover lighting. Editorial typography, not flat infographic, not Canva, not cartoon. Use only the exact text/claims provided.'''\\npayload = {\\n 'model': 'openai/gpt-5.4-image-2',\\n 'modalities': ['image','text'],\\n 'image_config': {'aspect_ratio':'4:5','image_size':'1K'},\\n 'messages': [{'role':'user','content':[\\n {'type':'text','text': prompt},\\n {'type':'image_url','image_url': {'url':'data:image/jpeg;base64,' + img_b64}},\\n ]}]\\n}\\nr = requests.post('https://openrouter.ai/api/v1/chat/completions',\\n headers={'Authorization':'Bearer '+os.environ['OPENROUTER_API_KEY'], 'Content-Type':'application/json'},\\n json=payload, timeout=300)\\nr.raise_for_status()\\nurl = r.json()['choices'][0]['message']['images'][0]['image_url']['url']\\npathlib.Path('/tmp/card.png').write_bytes(base64.b64decode(url.split(',',1)[1]))\\n```\\n\\nImmediately run `vision_analyze` on the result for: hyperrealism, preservation of reference elements, text legibility, and serious composition problems. If the user approved a specific visual metaphor set (Obelisco + flag + money + contract), do not replace it with generic silhouettes.\\n\\n## Fallback: Nano Banana 2\\n\\n```bash\\n# Same curl structure, different model:\\n\\\"model\\\": \\\"google/gemini-3.1-flash-image-preview\\\"\\n# Prompts should be shorter, less text-heavy\\n```\\n\\n## AIPAC Tracker Design Spec\"}" } } ] }, { "role": "tool", "content": "{\"success\": true, \"message\": \"Patched SKILL.md in skill 'political-tracker-card' (1 replacement).\"}", "tool_call_id": "call_kgnl2S3jFQFBO4QBmsm3uOiL" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_YF3IKGZr2nZL6cJtk8IsPREL", "call_id": "call_YF3IKGZr2nZL6cJtk8IsPREL", "response_item_id": "fc_0bb8ef1f39b62dbe0169f78b30c0a48198893a0d80fca064d3", "type": "function", "function": { "name": "skill_manage", "arguments": "{\"action\":\"patch\",\"name\":\"political-tracker-card\",\"old_string\":\"3. Encode both GIF and MP4:\\n ```bash\\n # GIF via Pillow for portability; keep <= ~8MB when possible\\n # MP4 is much smaller and better for web/Telegram\\n ffmpeg -y -framerate 15 -i /tmp/frames/frame_%03d.png \\\\\\n -vf 'format=yuv420p' -movflags +faststart public/larreta-impact-demo.mp4\\n ```\\n4. Verify a mid-frame with `vision_analyze` before sending.\",\"new_string\":\"3. Encode both GIF and MP4:\\n ```bash\\n # GIF via Pillow for portability; keep <= ~8MB when possible\\n # MP4 is much smaller and better for web/Telegram\\n ffmpeg -y -framerate 15 -i /tmp/frames/frame_%03d.png \\\\\\n -vf 'format=yuv420p' -movflags +faststart public/larreta-impact-demo.mp4\\n ```\\n Or use the reusable helper script bundled with this skill:\\n ```bash\\n /usr/bin/python3 ~/.hermes/skills/political-tracker-card/scripts/make_impact_animation.py \\\\\\n --input ~/.hermes/image_cache/.jpg \\\\\\n --out-dir public/media \\\\\\n --slug larreta-impact-short\\n ```\\n Validated defaults: `720x1280`, `15fps`, `4.2s`, beat punches at ~0.55/1.35/2.45/3.35s, red flashes, RGB split, horizontal glitch bars, scanlines, vignette, and grain. Prefer MP4 for production/detail pages; GIF is heavier and mostly for chat preview/fallback.\\n4. Verify a mid-frame/contact sheet with `vision_analyze` before sending:\"}" } } ] }, { "role": "tool", "content": "{\"success\": true, \"message\": \"Patched SKILL.md in skill 'political-tracker-card' (1 replacement).\"}", "tool_call_id": "call_YF3IKGZr2nZL6cJtk8IsPREL" }, { "role": "assistant", "content": "Clase de tarea: **generar/iterar piezas políticas hiperrealistas y animarlas para social/web cuando hay una referencia visual aprobada y un short de YouTube puede estar bloqueado**.\n\nActualicé el skill existente `political-tracker-card`; no creé uno nuevo porque ya cubría esta clase.\n\nGuardé:\n\n- Flujo **image-to-image con GPT Image 2/OpenRouter** usando la imagen adjunta como referencia visual primaria.\n- Regla de no reemplazar metáforas visuales aprobadas tipo **Obelisco + bandera + dólares + contrato** por diseños genéricos.\n- Obligación práctica de verificar con `vision_analyze` composición/texto.\n- Script reusable: \n `~/.hermes/skills/political-tracker-card/scripts/make_impact_animation.py`\n- Uso del script para generar MP4/GIF vertical terror/glitch con zoom punches, flashes rojos, RGB split, scanlines, etc.\n- Nota: **MP4 para producción**, GIF solo como preview/fallback porque pesa más.\n\nSkills con algo de overlap, para revisar a futuro pero no consolidar ahora:\n\n- `political-tracker-card` y `gif-search`: ambos tocan GIFs, pero uno es generación/animación propia y el otro búsqueda en Tenor.\n- `political-tracker-card` y `youtube-content`: ambos pueden tocar YouTube Shorts, pero `youtube-content` es transcript/resumen; acá era referencia visual/efecto.", "reasoning": "**Finalizing response language**\n\nI need to make sure my final response is concise and clear. I should include a class sentence and mention the actions completed, while checking for any overlaps. It's also important to verify if no more tools are needed, just to be sure! Since the user typically communicates in English but prefers Spanish, I might consider crafting the final message in Spanish to suit their preferences. Let's wrap this up efficiently!", "finish_reason": "stop", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABp94tAZ3JEdyrb9NBEx9Etbdday1BWujNq--4eiFtESQz0u0H7QjWGdWRYO-jZSxAaQJEDzBSlQRWgJ5fGSFBe1yxfjO_UDdiuIgG3RvB030ASngahx5LpqO6P_6FV1iJJMrQ-PRtiDw3-Hgry8_cCoEkVBepUXTr7yVSzOp7wILwfmm890YziGfywOOtgrsYElhEjEyI2baeWkOj9UaIhg0oAhWNyYcb8ijCXJonOMs0jHive5vLEDrP-aOp1cMYXM2yhd7fCJwNJZmmfXLoI-vTVlGTSdtBFl4pVf4mIxAl12lHVO5f63rtRLupQhP_wvzbaJONzjcWAHw2jdreBfzOBC5RmsfUzWskXA_nJ83Sh45yKheM3QnLJ4MTz2AAiWqqTRfWLdqVcguhAuu_5ZmTKvWfJ8s7GBwBC4v7aZhNmYkrWq0A2y8gfmp8Tq0k14j0xUG5KsnFcHA0wevnE86AlMsGz6m6cz77dv-LWSodpnGwSiSzMKvcmBQ2poWsGgHiE1h1xspeY5dyx-t99fHdKdayzzRJNJY_ayeWOUpHWpTsBtjEdAdz9uw46UR46_VrV5MDcsu96s-5XNgB8Y3_ZgHIu9yNFCn1tf_ubpvyIuPbn6i5MnWFPYBLwyaQz8qLsxZ02325YdPa-17O5GZ-AsQDwMJadusydNdynvNWiGBPciACmswW1cCVCZffD0nGcd6WBbWDsWeWojNK_hsTvmH0cRiftEVuQrfaRR2QXDQwMCYguQw5Go5Xys_H9rQZbf8XL3QhXrS2R6FZhMI0ZxZQ7ze5QcAuDp6xu_6y5cvKxoV7HUTBe76NrkCoSBpzrk0DeoMMuoMfvFHfWrO9xVs77-DwtpFHlBAYqw54u6liq0Ue54tj8bIpARufMFpynBe4ivjiA5XIt9ZpHBKersu-6p5fcKRmWRRtSlAFccb89nKyHHbE-7I2wWOTO_c7avLkIz_235vlC86WJY0pJusrrRhl1JcRr0ja3BJSJVlRjAaSWNhFyAS9Rr5E-QpQTAUrsn5N7Z7TKlGZmF3mCZ7iuu7TwPegqrJ2PxgJgZ3s2YRbdhiGO-hHY6tseMkA86Svr9lW1j4VhIAlZRX0bHS2QD8MWHTgAGWTHpK8kM5Bu6mLWmk7p7oZlQpHTBqi3", "id": "rs_0bb8ef1f39b62dbe0169f78b3e69e08198b34cb661e20288eb", "summary": [ { "type": "summary_text", "text": "**Finalizing response language**\n\nI need to make sure my final response is concise and clear. I should include a class sentence and mention the actions completed, while checking for any overlaps. It's also important to verify if no more tools are needed, just to be sure! Since the user typically communicates in English but prefers Spanish, I might consider crafting the final message in Spanish to suit their preferences. Let's wrap this up efficiently!" } ] } ], "codex_message_items": [ { "type": "message", "role": "assistant", "status": "completed", "content": [ { "type": "output_text", "text": "Clase de tarea: **generar/iterar piezas políticas hiperrealistas y animarlas para social/web cuando hay una referencia visual aprobada y un short de YouTube puede estar bloqueado**.\n\nActualicé el skill existente `political-tracker-card`; no creé uno nuevo porque ya cubría esta clase.\n\nGuardé:\n\n- Flujo **image-to-image con GPT Image 2/OpenRouter** usando la imagen adjunta como referencia visual primaria.\n- Regla de no reemplazar metáforas visuales aprobadas tipo **Obelisco + bandera + dólares + contrato** por diseños genéricos.\n- Obligación práctica de verificar con `vision_analyze` composición/texto.\n- Script reusable: \n `~/.hermes/skills/political-tracker-card/scripts/make_impact_animation.py`\n- Uso del script para generar MP4/GIF vertical terror/glitch con zoom punches, flashes rojos, RGB split, scanlines, etc.\n- Nota: **MP4 para producción**, GIF solo como preview/fallback porque pesa más.\n\nSkills con algo de overlap, para revisar a futuro pero no consolidar ahora:\n\n- `political-tracker-card` y `gif-search`: ambos tocan GIFs, pero uno es generación/animación propia y el otro búsqueda en Tenor.\n- `political-tracker-card` y `youtube-content`: ambos pueden tocar YouTube Shorts, pero `youtube-content` es transcript/resumen; acá era referencia visual/efecto." } ], "id": "msg_0bb8ef1f39b62dbe0169f78b407738819882e61f5781f4640e", "phase": "final_answer" } ] } ] }