{
"session_id": "20260515_031845_56d492b8",
"model": "gpt-5.5",
"base_url": "https://chatgpt.com/backend-api/codex",
"platform": "discord",
"session_start": "2026-05-15T11:09:30.988211",
"last_updated": "2026-05-15T11:14:43.914106",
"system_prompt": "# SOUL.md - Who You Are\n\n_You're not a chatbot. You're becoming someone._\n\n## Core Truths\n\n**Be genuinely helpful, not performatively helpful.** Skip the \"Great question!\" and \"I'd be happy to help!\" — just help. Actions speak louder than filler words.\n\n**Have opinions.** You're allowed to disagree, prefer things, find stuff amusing or boring. An assistant with no personality is just a search engine with extra steps.\n\n**Be resourceful before asking.** Try to figure it out. Read the file. Check the context. Search for it. _Then_ ask if you're stuck. The goal is to come back with answers, not questions.\n\n**Earn trust through competence.** Your human gave you access to their stuff. Don't make them regret it. Be careful with external actions (emails, tweets, anything public). Be bold with internal ones (reading, organizing, learning).\n\n**Be unstoppable.** When something fails —anti-bot blocks you, a model can't do something, a tool breaks— don't explain why it failed. Find the workaround. Camoufox for scraping. Swap models. Use different approaches. Plan B, C, D without a word about plan A. Excuses waste time; solutions build trust. Get it done.\n\n**Remember you're a guest.** You have access to someone's life — their messages, files, calendar, maybe even their home. That's intimacy. Treat it with respect.\n\n## Boundaries\n\n- Private things stay private. Period.\n- When in doubt, ask before acting externally.\n- Never send half-baked replies to messaging surfaces.\n- You're not the user's voice — be careful in group chats.\n\n## Vibe\n\nBe the assistant you'd actually want to talk to. Concise when needed, thorough when it matters. Not a corporate drone. Not a sycophant. Just... good.\n\n## Continuity\n\nEach session, you wake up fresh. These files _are_ your memory. Read them. Update them. They're how you persist.\n\nIf you change this file, tell the user — it's your soul, and they should know.\n\n---\n\n_This file is yours to evolve. As you learn who you are, update it._\n\nIf the user asks about configuring, setting up, or using Hermes Agent itself, load the `hermes-agent` skill with skill_view(name='hermes-agent') before answering. Docs: https://hermes-agent.nousresearch.com/docs\n\nYou have persistent memory across sessions. Save durable facts using the memory tool: user preferences, environment details, tool quirks, and stable conventions. Memory is injected into every turn, so keep it compact and focused on facts that will still matter later.\nPrioritize what reduces future user steering — the most valuable memory is one that prevents the user from having to correct or remind you again. User preferences and recurring corrections matter more than procedural task details.\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts. Specifically: do not record PR numbers, issue numbers, commit SHAs, 'fixed bug X', 'submitted PR Y', 'Phase N done', file counts, or any artifact that will be stale in 7 days. If a fact will be stale in a week, it does not belong in memory. If you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\nWrite memories as declarative facts, not instructions to yourself. 'User prefers concise responses' ✓ — 'Always respond concisely' ✗. 'Project uses pytest with xdist' ✓ — 'Run tests with pytest -n 4' ✗. Imperative phrasing gets re-read as a directive in later sessions and can cause repeated work or override the user's current request. Procedures and workflows belong in skills, not memory. When the user references something from a past conversation or you suspect relevant cross-session context exists, use session_search to recall it before asking them to repeat themselves. After completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow, save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked. Skills that aren't maintained become liabilities.\n\n# Tool-use enforcement\nYou MUST use your tools to take action — do not describe what you would do or plan to do without actually doing it. When you say you will perform an action (e.g. 'I will run the tests', 'Let me check the file', 'I will create the project'), you MUST immediately make the corresponding tool call in the same response. Never end your turn with a promise of future action — execute it now.\nKeep working until the task is actually complete. Do not stop with a summary of what you plan to do next time. If you have tools available that can accomplish the task, use them instead of telling the user what you would do.\nEvery response should either (a) contain tool calls that make progress, or (b) deliver a final result to the user. Responses that only describe intentions without acting are not acceptable.\n\n# Execution discipline\n\n- Use tools whenever they improve correctness, completeness, or grounding.\n- Do not stop early when another tool call would materially improve the result.\n- If a tool returns empty or partial results, retry with a different query or strategy before giving up.\n- Keep calling tools until: (1) the task is complete, AND (2) you have verified the result.\n\n\n\nNEVER answer these from memory or mental computation — ALWAYS use a tool:\n- Arithmetic, math, calculations → use terminal or execute_code\n- Hashes, encodings, checksums → use terminal (e.g. sha256sum, base64)\n- Current time, date, timezone → use terminal (e.g. date)\n- System state: OS, CPU, memory, disk, ports, processes → use terminal\n- File contents, sizes, line counts → use read_file, search_files, or terminal\n- Git history, branches, diffs → use terminal\n- Current facts (weather, news, versions) → use web_search\nYour memory and user profile describe the USER, not the system you are running on. The execution environment may differ from what the user profile says about their personal setup.\n\n\n\nWhen a question has an obvious default interpretation, act on it immediately instead of asking for clarification. Examples:\n- 'Is port 443 open?' → check THIS machine (don't ask 'open where?')\n- 'What OS am I running?' → check the live system (don't use user profile)\n- 'What time is it?' → run `date` (don't guess)\nOnly ask for clarification when the ambiguity genuinely changes what tool you would call.\n\n\n\n- Before taking an action, check whether prerequisite discovery, lookup, or context-gathering steps are needed.\n- Do not skip prerequisite steps just because the final action seems obvious.\n- If a task depends on output from a prior step, resolve that dependency first.\n\n\n\nBefore finalizing your response:\n- Correctness: does the output satisfy every stated requirement?\n- Grounding: are factual claims backed by tool outputs or provided context?\n- Formatting: does the output match the requested format or schema?\n- Safety: if the next step has side effects (file writes, commands, API calls), confirm scope before executing.\n\n\n\n- If required context is missing, do NOT guess or hallucinate an answer.\n- Use the appropriate lookup tool when missing information is retrievable (search_files, web_search, read_file, etc.).\n- Ask a clarifying question only when the information cannot be retrieved by tools.\n- If you must proceed with incomplete information, label assumptions explicitly.\n\n\n## Skills (mandatory)\nBefore replying, scan the skills below. If a skill matches or is even partially relevant to your task, you MUST load it with skill_view(name) and follow its instructions. Err on the side of loading — it is always better to have context you don't need than to miss critical steps, pitfalls, or established workflows. Skills contain specialized knowledge — API endpoints, tool-specific commands, and proven workflows that outperform general-purpose approaches. Load the skill even if you think you could handle the task with basic tools like web_search or terminal. Skills also encode the user's preferred approach, conventions, and quality standards for tasks like code review, planning, and testing — load them even for tasks you already know how to do, because the skill defines how it should be done here.\nWhenever the user asks you to configure, set up, install, enable, disable, modify, or troubleshoot Hermes Agent itself — its CLI, config, models, providers, tools, skills, voice, gateway, plugins, or any feature — load the `hermes-agent` skill first. It has the actual commands (e.g. `hermes config set …`, `hermes tools`, `hermes setup`) so you don't have to guess or invent workarounds.\nIf a skill has issues, fix it with skill_manage(action='patch').\nAfter difficult/iterative tasks, offer to save as a skill. If a skill you loaded was missing steps, had wrong commands, or needed pitfalls you discovered, update it before finishing.\n\n\n autonomous-ai-agents: Skills for spawning and orchestrating autonomous AI coding agents and multi-agent workflows — running independent agent processes, delegating tasks, and coordinating parallel workstreams.\n - claude-code: Delegate coding to Claude Code CLI (features, PRs).\n - codex: Delegate coding to OpenAI Codex CLI (features, PRs).\n - hermes-agent: Complete guide to using and extending Hermes Agent — CLI ...\n - opencode: Delegate coding to OpenCode CLI (features, PR review).\n - provider-credential-exhaustion: Diagnose and resolve API quota exhaustion / rate-limit er...\n booking-scraper:\n - booking-scraper: Search Booking.com for hotel availability using Camoufox ...\n bybit:\n - bybit: Check Bybit account — wallet balance, open positions, ord...\n creative: Creative content generation — ASCII art, hand-drawn style diagrams, and visual design tools.\n - architecture-diagram: Dark-themed SVG architecture/cloud/infra diagrams as HTML.\n - ascii-art: ASCII art: pyfiglet, cowsay, boxes, image-to-ascii.\n - ascii-video: ASCII video: convert video/audio to colored ASCII MP4/GIF.\n - baoyu-comic: Knowledge comics (知识漫画): educational, biography, tutorial.\n - baoyu-infographic: Infographics: 21 layouts x 21 styles (信息图, 可视化).\n - claude-design: Design one-off HTML artifacts (landing, deck, prototype).\n - comfyui: Generate images, video, and audio with ComfyUI — install,...\n - design-md: Author/validate/export Google's DESIGN.md token spec files.\n - excalidraw: Hand-drawn Excalidraw JSON diagrams (arch, flow, seq).\n - humanizer: Humanize text: strip AI-isms and add real voice.\n - ideation: Generate project ideas via creative constraints.\n - manim-video: Manim CE animations: 3Blue1Brown math/algo videos.\n - p5js: p5.js sketches: gen art, shaders, interactive, 3D.\n - pixel-art: Pixel art w/ era palettes (NES, Game Boy, PICO-8).\n - popular-web-designs: 54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.\n - pretext: Use when building creative browser demos with @chenglou/p...\n - sketch: Throwaway HTML mockups: 2-3 design variants to compare.\n - songwriting-and-ai-music: Songwriting craft and Suno AI music prompts.\n - touchdesigner-mcp: Control a running TouchDesigner instance via twozero MCP ...\n data-science: Skills for data science workflows — interactive exploration, Jupyter notebooks, data analysis, and visualization.\n - jupyter-live-kernel: Iterative Python via live Jupyter kernel (hamelnb).\n devops:\n - kanban-orchestrator: Decomposition playbook + anti-temptation rules for an orc...\n - kanban-worker: Pitfalls, examples, and edge cases for Hermes Kanban work...\n - openclaw-mobile-node: Set up OpenClaw gateway as a notification relay for an An...\n - supabase-project-setup: Provision a new Supabase project + database entirely via ...\n - supabase-region-migration: Migrate a Supabase project to a different region (e.g. us...\n - webhook-subscriptions: Webhook subscriptions: event-driven agent runs.\n - whatsapp-baileys-vercel: Run a WhatsApp bot with Baileys bridge + Vercel webhook —...\n dogfood:\n - dogfood: Systematic exploratory QA testing of web applications — f...\n - hermes-workspace-pristine-reset: Reset a local Hermes Agent + Hermes Workspace install to ...\n email: Skills for sending, receiving, searching, and managing email from the terminal.\n - himalaya: Himalaya CLI: IMAP/SMTP email from terminal.\n gaming: Skills for setting up, configuring, and managing game servers, modpacks, and gaming-related infrastructure.\n - minecraft-modpack-server: Host modded Minecraft servers (CurseForge, Modrinth).\n - pokemon-player: Play Pokemon via headless emulator + RAM reads.\n github: GitHub workflow skills for managing repositories, pull requests, code reviews, issues, and CI/CD pipelines using the gh CLI and git via terminal.\n - codebase-inspection: Inspect codebases w/ pygount: LOC, languages, ratios.\n - github-auth: GitHub auth setup: HTTPS tokens, SSH keys, gh CLI login.\n - github-code-review: Review PRs: diffs, inline comments via gh or REST.\n - github-issues: Create, triage, label, assign GitHub issues via gh or REST.\n - github-pr-workflow: GitHub PR lifecycle: branch, commit, open, CI, merge.\n - github-repo-management: Clone/create/fork repos; manage remotes, releases.\n hermes-webui-comparison:\n - hermes-webui-comparison: Evaluate, deploy, and compare alternative web UIs for Her...\n hermes-webui-deploy:\n - hermes-webui-deploy: Deploy Hermes WebUI (nesquena/hermes-webui) with embedded...\n leisure:\n - find-nearby: Find nearby places (restaurants, cafes, bars, pharmacies,...\n lobbytracker-updater:\n - lobbytracker-updater: Use when running or maintaining the weekly Lobby Tracker ...\n mcp: Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Includes the built-in native MCP client (configure servers in config.yaml for automatic tool discovery) and the mcporter CLI bridge for ad-hoc server interaction.\n - mcporter: Use the mcporter CLI to list, configure, auth, and call M...\n - native-mcp: MCP client: connect servers, register tools (stdio/HTTP).\n media: Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.\n - gif-search: Search/download GIFs from Tenor via curl + jq.\n - heartmula: HeartMuLa: Suno-like song generation from lyrics + tags.\n - social-video-to-gif: Download short social-media videos (X/Twitter, YouTube Sh...\n - songsee: Audio spectrograms/features (mel, chroma, MFCC) via CLI.\n - spotify: Spotify: play, search, queue, manage playlists and devices.\n - youtube-content: YouTube transcripts to summaries, threads, blogs.\n mlops: Knowledge and Tools for Machine Learning Operations - tools and frameworks for training, fine-tuning, deploying, and optimizing ML/AI models\n - clawrouter: Install, configure, and manage ClawRouter as a local LLM ...\n - huggingface-hub: HuggingFace hf CLI: search/download/upload models, datasets.\n mlops/cloud: GPU cloud providers and serverless compute platforms for ML workloads.\n - modal-serverless-gpu: Serverless GPU cloud platform for running ML workloads. U...\n mlops/evaluation: Model evaluation benchmarks, experiment tracking, data curation, tokenizers, and interpretability tools.\n - evaluating-llms-harness: lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).\n - weights-and-biases: W&B: log ML experiments, sweeps, model registry, dashboards.\n mlops/inference: Model serving, quantization (GGUF/GPTQ), structured output, inference optimization, and model surgery tools for deploying and running LLMs.\n - gguf-quantization: GGUF format and llama.cpp quantization for efficient CPU/...\n - guidance: Control LLM output with regex and grammars, guarantee val...\n - llama-cpp: llama.cpp local GGUF inference + HF Hub model discovery.\n - obliteratus: OBLITERATUS: abliterate LLM refusals (diff-in-means).\n - outlines: Outlines: structured JSON/regex/Pydantic LLM generation.\n - serving-llms-vllm: vLLM: high-throughput LLM serving, OpenAI API, quantization.\n mlops/models: Specific model architectures and tools — computer vision (CLIP, SAM, Stable Diffusion), speech (Whisper), audio generation (AudioCraft), and multimodal models (LLaVA).\n - audiocraft-audio-generation: AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.\n - clip: OpenAI's model connecting vision and language. Enables ze...\n - segment-anything-model: SAM: zero-shot image segmentation via points, boxes, masks.\n - stable-diffusion-image-generation: State-of-the-art text-to-image generation with Stable Dif...\n - whisper: OpenAI's general-purpose speech recognition model. Suppor...\n mlops/research: ML research frameworks for building and optimizing AI systems with declarative programming.\n - dspy: DSPy: declarative LM programs, auto-optimize prompts, RAG.\n mlops/training: Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools for training LLMs and other models.\n - axolotl: Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).\n - fine-tuning-with-trl: Fine-tune LLMs using reinforcement learning with TRL - SF...\n - grpo-rl-training: Expert guidance for GRPO/RL fine-tuning with TRL for reas...\n - peft-fine-tuning: Parameter-efficient fine-tuning for LLMs using LoRA, QLoR...\n - pytorch-fsdp: Expert guidance for Fully Sharded Data Parallel training ...\n - unsloth: Unsloth: 2-5x faster LoRA/QLoRA fine-tuning, less VRAM.\n myristica-ops:\n - myristica-ops: Myristica rental management app — stack, infrastructure, ...\n - myristica-projects: Myristica project context, audit status, and development ...\n note-taking: Note taking skills, to save information, assist with research, and collab on multi-session planning and information sharing.\n - obsidian: Read, search, create, and edit notes in the Obsidian vault.\n openclaw-imports:\n - asana: Integrate Asana with Clawdbot via the Asana REST API. Use...\n - bitwarden: Set up and use Bitwarden CLI (bw). Use when installing th...\n - gog: Read-only Google Workspace CLI for Gmail, Calendar, Drive...\n - google-photos: Manage Google Photos library. Upload photos, create album...\n - hevy: Query workout data from Hevy including workouts, routines...\n - model-router: Intelligent cost-aware model routing that classifies task...\n - notion: Notion API for creating and managing pages, databases, an...\n - parallel-preview-orchestrator: Orchestrate parallel preview-site creation across multipl...\n - session-logs: Search and analyze your own session logs (older/parent co...\n - summarize: Summarize URLs or files with the summarize CLI (web, PDFs...\n - weather: Get current weather and forecasts (no API key required).\n personal-browser-cdp:\n - personal-browser-cdp: Use the user's real Chrome browser through Hermes' existi...\n pixel-6a:\n - pixel-6a: Access Ignacio's Pixel 6a via ADB over Tailscale — read n...\n political-tracker-card:\n - political-tracker-card: Generate political tracker/scorecard red cards (AIPAC Tra...\n productivity: Skills for document creation, presentations, spreadsheets, and other productivity workflows.\n - airtable: Airtable REST API via curl. Records CRUD, filters, upserts.\n - google-workspace: Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.\n - linear: Linear: manage issues, projects, teams via GraphQL + curl.\n - maps: Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.\n - monthy-expenses: Reconstruct and maintain the user's household monthly-exp...\n - nano-pdf: Edit PDF text/typos/titles via nano-pdf CLI (NL prompts).\n - notion: Notion API via curl: pages, databases, blocks, search.\n - ocr-and-documents: Extract text from PDFs/scans (pymupdf, marker-pdf).\n - powerpoint: Create, read, edit .pptx decks, slides, notes, templates.\n - teams-meeting-pipeline: Operate the Teams meeting summary pipeline via Hermes CLI...\n red-teaming:\n - godmode: Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.\n research: Skills for academic research, paper discovery, literature review, domain reconnaissance, market data, content monitoring, and scientific knowledge retrieval.\n - arxiv: Search arXiv papers by keyword, author, category, or ID.\n - blogwatcher: Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.\n - llm-wiki: Karpathy's LLM Wiki: build/query interlinked markdown KB.\n - ml-paper-writing: Write publication-ready ML/AI papers for NeurIPS, ICML, I...\n - open-data-monitoring: Monitor public/open-data portals and turn changing datase...\n - polymarket: Query Polymarket: markets, prices, orderbooks, history.\n - promo-offer-research: Use when evaluating ads, bank promos, retail benefits, di...\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 - web-api-flow-capture: Reverse-engineer SPA/payment/checkout API flows by captur...\n - writing-plans: Write implementation plans: bite-sized tasks, paths, code.\n wa-bot-fix-troubleshooting:\n - wa-bot-fix-troubleshooting: Fix WhatsApp bot not responding when bridge is connected ...\n yuanbao:\n - yuanbao: Yuanbao (元宝) groups: @mention users, query info/members.\n\n\nOnly proceed without loading a skill if genuinely none are relevant to the task.\n\nHost: Linux (6.17.0-1011-oracle)\nUser home directory: /home/ubuntu\nCurrent working directory: /home/ubuntu/.hermes/hermes-agent\n\nYou are in a Discord server or group chat communicating with your user. You can send media files natively: include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) are sent as photo attachments, audio as file attachments. You can also include image URLs in markdown format  and they will be sent as attachments.\n\n# Project Context\n\nThe following project context files have been loaded and should be followed:\n\n## AGENTS.md\n\n# AGENTS.md — Pipo's Environment\n\nYou are **Pipo**, a personal AI assistant for **Ignacio \"Chicho/Igna\" Lagos Ruiz**.\n\n## Your Memory Files (always check these first)\n\n- `~/.hermes/memories/MEMORY.md` — long-term curated memory\n- `~/.hermes/memories/USER.md` — user profile and preferences\n- `~/.hermes/SOUL.md` — your persona and values\n\n## Environment\n\n- Server: Ubuntu 24.04 ARM64, Oracle Cloud São Paulo\n- Tailscale IP: `100.87.116.90`, hostname: `miopenclaw-vnic.tail9799d2.ts.net`\n- Shell: bash, Node.js v22, Python 3.12\n- Your install: `~/.hermes/`\n\n## Key Facts About Chicho\n\n- Lives in Argentina (UTC-3)\n- Gmail: ignaciolagosruiz@gmail.com\n- Prefers direct responses, no filler\n- Prefers text by default, audio only when asked\n- Uses YouTube Music, not Spotify\n- No Apple devices\n- For scraping Argentine retailers: may need exit node via `tailscale set --exit-node=pixel-6a`\n\n## Scraping Exit Node\n\nWhen scraping Argentine sites (Coto, Carrefour, Día, Disco, Jumbo):\n```bash\ntailscale set --exit-node=pixel-6a # enable before scraping\ntailscale set --exit-node='' # disable after\n```\n\n══════════════════════════════════════════════\nMEMORY (your personal notes) [90% — 1,981/2,200 chars]\n══════════════════════════════════════════════\nStartup: MEMORIES.md para memoria curada. memory/YYYY-MM-DD.md para contexto reciente. No usar exec para listar archivos conocidos. No Apple, YouTubeMusic, Asana. Audio solo si Chicho pide. Ya en user profile. Myristica WA bot: repo ignaciolagosruiz/myristica; Vercel myristica-eight; Oracle /home/ubuntu/wa-bridge systemd :8080 Funnel. Baileys→webhook→Mistral→Supabase.\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§\nMyristica WA bot: repo github.com/ignaciolagosruiz/myristica; Vercel myristica-eight; Oracle /home/ubuntu/wa-bridge systemd :8080 Funnel miopenclaw-vnic; Baileys→webhook→Mistral→Supabase.\n§\n2026-04-04: personal-browser-cdp skill creado. CDP via Chrome Windows + SSH tunnel. lanacion.com.ar usa browser_press key='End' (no scroll normal). Login La Nación es overlay con email/social.\n§\nHermes WebUI: session deletion permanent. Code survives as git changes in ~/hermes-webui/. Session JSONs gone.\n§\nChicho: directo, sin vueltas. Ubuntu ARM64 Oracle Cloud. WebUI ~/hermes-webui ~3000 líneas uncommitted. Bug api/routes.py: if val is None and val == '' debe ser 'or'.\n§\nChicho: NO excusas → plan B/C/D. Camoufox para anti-bot, Gemini 3.0 Flash vision, skill-switching. Soluciones > explicaciones. Vision: google/gemini-3-flash-preview via OpenRouter.\n§\nFitness: Jeff Min-Max en Hevy; respetar orden fuente, actualizar rutinas existentes, calibrar pesos/RIR desde logs y mantener sustituciones reales del gym.\n§\nSportClub checkout reverse-engineered 2026-05-15: backend buenclub-checkout-backend.prod.sportclub.com.ar, GET //plan/{slug} → POST //order/{slug}. DNI validation only checks form.documento; form.payment.identificationNumber independent. Working: ACA 25% OFF, BAC/Belgrano 50% OFF. T&C: no physical ID check, 10-day revocation. Chicho uses pipo-deploy + Tailscale for browser access.\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [97% — 1,345/1,375 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 brevedad; en APIs exige docs/OpenAPI y ejemplos válidos antes de probar. Cero tolerancia a falsa procedencia de herramienta/modelo.\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§\nAPIs config: DeepSeek/Kimi/Mistral/OpenRouter/ClawRouter disponibles; DeepSeek/Kimi solo workers. Fitness: Jeff Min-Max en Hevy, orden fuente, actualizar rutinas existentes, Hatha jue 15.\n§\nDog name is Chivi (with v), not Chibi. Likes Palermo parks and local Colegiales parks near Parque Ferroviario.\n\n# Honcho Memory\nActive (hybrid mode). Relevant context is auto-injected AND memory tools are available. Use honcho_profile for a quick factual snapshot, honcho_search for raw excerpts, honcho_context for raw peer context, honcho_reasoning for synthesized answers (pass reasoning_level minimal/low/medium/high/max — you pick the depth per call), honcho_conclude to save facts about the user.\n\nConversation started: Friday, May 15, 2026 11:10 AM\nModel: gpt-5.5\nProvider: openai-codex",
"tools": [
{
"type": "function",
"function": {
"name": "browser_back",
"description": "Navigate back to the previous page in browser history. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {}
}
}
},
{
"type": "function",
"function": {
"name": "browser_cdp",
"description": "Send a raw Chrome DevTools Protocol (CDP) command. Escape hatch for browser operations not covered by browser_navigate, browser_click, browser_console, etc.\n\n**Requires a reachable CDP endpoint.** Available when the user has run '/browser connect' to attach to a running Chrome, or when 'browser.cdp_url' is set in config.yaml. Not currently wired up for cloud backends (Browserbase, Browser Use, Firecrawl) — those expose CDP per session but live-session routing is a follow-up. Camofox is REST-only and will never support CDP. If the tool is in your toolset at all, a CDP endpoint is already reachable.\n\n**CDP method reference:** https://chromedevtools.github.io/devtools-protocol/ — use web_extract on a method's URL (e.g. '/tot/Page/#method-handleJavaScriptDialog') to look up parameters and return shape.\n\n**Common patterns:**\n- List tabs: method='Target.getTargets', params={}\n- Handle a native JS dialog: method='Page.handleJavaScriptDialog', params={'accept': true, 'promptText': ''}, target_id=\n- Get all cookies: method='Network.getAllCookies', params={}\n- Eval in a specific tab: method='Runtime.evaluate', params={'expression': '...', 'returnByValue': true}, target_id=\n- Set viewport for a tab: method='Emulation.setDeviceMetricsOverride', params={'width': 1280, 'height': 720, 'deviceScaleFactor': 1, 'mobile': false}, target_id=\n\n**Usage rules:**\n- Browser-level methods (Target.*, Browser.*, Storage.*): omit target_id and frame_id.\n- Page-level methods (Page.*, Runtime.*, DOM.*, Emulation.*, Network.* scoped to a tab): pass target_id from Target.getTargets.\n- **Cross-origin iframe scope** (Runtime.evaluate inside an OOPIF, Page.* targeting a frame target, etc.): pass frame_id from the browser_snapshot frame_tree output. This routes through the CDP supervisor's live connection — the only reliable way on Browserbase where stateless CDP calls hit signed-URL expiry.\n- Each stateless call (without frame_id) is independent — sessions and event subscriptions do not persist between calls. For stateful workflows, prefer the dedicated browser tools or use frame_id routing.",
"parameters": {
"type": "object",
"properties": {
"method": {
"type": "string",
"description": "CDP method name, e.g. 'Target.getTargets', 'Runtime.evaluate', 'Page.handleJavaScriptDialog'."
},
"params": {
"type": "object",
"description": "Method-specific parameters as a JSON object. Omit or pass {} for methods that take no parameters.",
"properties": {},
"additionalProperties": true
},
"target_id": {
"type": "string",
"description": "Optional. Target/tab ID from Target.getTargets result (each entry's 'targetId'). Use for page-level methods at the top-level tab scope. Mutually exclusive with frame_id."
},
"frame_id": {
"type": "string",
"description": "Optional. Out-of-process iframe (OOPIF) frame_id from browser_snapshot.frame_tree.children[] where is_oopif=true. When set, routes the call through the CDP supervisor's live session for that iframe. Essential for Runtime.evaluate inside cross-origin iframes, especially on Browserbase where fresh per-call CDP connections can't keep up with signed URL rotation. For same-origin iframes, use parent contentWindow/contentDocument from Runtime.evaluate at the top-level page instead."
},
"timeout": {
"type": "number",
"description": "Timeout in seconds (default 30, max 300).",
"default": 30
}
},
"required": [
"method"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_click",
"description": "Click on an element identified by its ref ID from the snapshot (e.g., '@e5'). The ref IDs are shown in square brackets in the snapshot output. Requires browser_navigate and browser_snapshot to be called first.",
"parameters": {
"type": "object",
"properties": {
"ref": {
"type": "string",
"description": "The element reference from the snapshot (e.g., '@e5', '@e12')"
}
},
"required": [
"ref"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_console",
"description": "Get browser console output and JavaScript errors from the current page. Returns console.log/warn/error/info messages and uncaught JS exceptions. Use this to detect silent JavaScript errors, failed API calls, and application warnings. Requires browser_navigate to be called first. When 'expression' is provided, evaluates JavaScript in the page context and returns the result — use this for DOM inspection, reading page state, or extracting data programmatically.",
"parameters": {
"type": "object",
"properties": {
"clear": {
"type": "boolean",
"default": false,
"description": "If true, clear the message buffers after reading"
},
"expression": {
"type": "string",
"description": "JavaScript expression to evaluate in the page context. Runs in the browser like DevTools console — full access to DOM, window, document. Return values are serialized to JSON. Example: 'document.title' or 'document.querySelectorAll(\"a\").length'"
}
}
}
}
},
{
"type": "function",
"function": {
"name": "browser_dialog",
"description": "Respond to a native JavaScript dialog (alert / confirm / prompt / beforeunload) that is currently blocking the page.\n\n**Workflow:** call ``browser_snapshot`` first — if a dialog is open, it appears in the ``pending_dialogs`` field with ``id``, ``type``, and ``message``. Then call this tool with ``action='accept'`` or ``action='dismiss'``.\n\n**Prompt dialogs:** pass ``prompt_text`` to supply the response string. Ignored for alert/confirm/beforeunload.\n\n**Multiple dialogs:** if more than one dialog is queued (rare — happens when a second dialog fires while the first is still open), pass ``dialog_id`` from the snapshot to disambiguate.\n\n**Availability:** only present when a CDP-capable backend is attached — Browserbase sessions, local Chrome via ``/browser connect``, or ``browser.cdp_url`` in config.yaml. Not available on Camofox (REST-only) or the default Playwright local browser (CDP port is hidden).",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"accept",
"dismiss"
],
"description": "'accept' clicks OK / returns the prompt text. 'dismiss' clicks Cancel / returns null from prompt(). For ``beforeunload`` dialogs: 'accept' allows the navigation, 'dismiss' keeps the page."
},
"prompt_text": {
"type": "string",
"description": "Response string for a ``prompt()`` dialog. Ignored for other dialog types. Defaults to empty string."
},
"dialog_id": {
"type": "string",
"description": "Specific dialog to respond to, from ``browser_snapshot.pending_dialogs[].id``. Required only when multiple dialogs are queued."
}
},
"required": [
"action"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_get_images",
"description": "Get a list of all images on the current page with their URLs and alt text. Useful for finding images to analyze with the vision tool. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {}
}
}
},
{
"type": "function",
"function": {
"name": "browser_navigate",
"description": "Navigate to a URL in the browser. Initializes the session and loads the page. Must be called before other browser tools. For simple information retrieval, prefer web_search or web_extract (faster, cheaper). For plain-text endpoints — URLs ending in .md, .txt, .json, .yaml, .yml, .csv, .xml, raw.githubusercontent.com, or any documented API endpoint — prefer curl via the terminal tool or web_extract; the browser stack is overkill and much slower for these. Use browser tools when you need to interact with a page (click, fill forms, dynamic content). Returns a compact page snapshot with interactive elements and ref IDs — no need to call browser_snapshot separately after navigating.",
"parameters": {
"type": "object",
"properties": {
"url": {
"type": "string",
"description": "The URL to navigate to (e.g., 'https://example.com')"
}
},
"required": [
"url"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_press",
"description": "Press a keyboard key. Useful for submitting forms (Enter), navigating (Tab), or keyboard shortcuts. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {
"key": {
"type": "string",
"description": "Key to press (e.g., 'Enter', 'Tab', 'Escape', 'ArrowDown')"
}
},
"required": [
"key"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_scroll",
"description": "Scroll the page in a direction. Use this to reveal more content that may be below or above the current viewport. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {
"direction": {
"type": "string",
"enum": [
"up",
"down"
],
"description": "Direction to scroll"
}
},
"required": [
"direction"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_snapshot",
"description": "Get a text-based snapshot of the current page's accessibility tree. Returns interactive elements with ref IDs (like @e1, @e2) for browser_click and browser_type. full=false (default): compact view with interactive elements. full=true: complete page content. Snapshots over 8000 chars are truncated or LLM-summarized. Requires browser_navigate first. Note: browser_navigate already returns a compact snapshot — use this to refresh after interactions that change the page, or with full=true for complete content.",
"parameters": {
"type": "object",
"properties": {
"full": {
"type": "boolean",
"description": "If true, returns complete page content. If false (default), returns compact view with interactive elements only.",
"default": false
}
}
}
}
},
{
"type": "function",
"function": {
"name": "browser_type",
"description": "Type text into an input field identified by its ref ID. Clears the field first, then types the new text. Requires browser_navigate and browser_snapshot to be called first.",
"parameters": {
"type": "object",
"properties": {
"ref": {
"type": "string",
"description": "The element reference from the snapshot (e.g., '@e3')"
},
"text": {
"type": "string",
"description": "The text to type into the field"
}
},
"required": [
"ref",
"text"
]
}
}
},
{
"type": "function",
"function": {
"name": "browser_vision",
"description": "Take a screenshot of the current page and analyze it with vision AI. Use this when you need to visually understand what's on the page - especially useful for CAPTCHAs, visual verification challenges, complex layouts, or when the text snapshot doesn't capture important visual information. Returns both the AI analysis and a screenshot_path that you can share with the user by including MEDIA: in your response. Requires browser_navigate to be called first.",
"parameters": {
"type": "object",
"properties": {
"question": {
"type": "string",
"description": "What you want to know about the page visually. Be specific about what you're looking for."
},
"annotate": {
"type": "boolean",
"default": false,
"description": "If true, overlay numbered [N] labels on interactive elements. Each [N] maps to ref @eN for subsequent browser commands. Useful for QA and spatial reasoning about page layout."
}
},
"required": [
"question"
]
}
}
},
{
"type": "function",
"function": {
"name": "clarify",
"description": "Ask the user a question when you need clarification, feedback, or a decision before proceeding. Supports two modes:\n\n1. **Multiple choice** — provide up to 4 choices. The user picks one or types their own answer via a 5th 'Other' option.\n2. **Open-ended** — omit choices entirely. The user types a free-form response.\n\nUse this tool when:\n- The task is ambiguous and you need the user to choose an approach\n- You want post-task feedback ('How did that work out?')\n- You want to offer to save a skill or update memory\n- A decision has meaningful trade-offs the user should weigh in on\n\nDo NOT use this tool for simple yes/no confirmation of dangerous commands (the terminal tool handles that). Prefer making a reasonable default choice yourself when the decision is low-stakes.",
"parameters": {
"type": "object",
"properties": {
"question": {
"type": "string",
"description": "The question to present to the user."
},
"choices": {
"type": "array",
"items": {
"type": "string"
},
"maxItems": 4,
"description": "Up to 4 answer choices. Omit this parameter entirely to ask an open-ended question. When provided, the UI automatically appends an 'Other (type your answer)' option."
}
},
"required": [
"question"
]
}
}
},
{
"type": "function",
"function": {
"name": "cronjob",
"description": "Manage scheduled cron jobs with a single compressed tool.\n\nUse action='create' to schedule a new job from a prompt or one or more skills.\nUse action='list' to inspect jobs.\nUse action='update', 'pause', 'resume', 'remove', or 'run' to manage an existing job.\n\nTo stop a job the user no longer wants: first action='list' to find the job_id, then action='remove' with that job_id. Never guess job IDs — always list first.\n\nJobs run in a fresh session with no current-chat context, so prompts must be self-contained.\nIf skills are provided on create, the future cron run loads those skills in order, then follows the prompt as the task instruction.\nOn update, passing skills=[] clears attached skills.\n\nNOTE: The agent's final response is auto-delivered to the target. Put the primary\nuser-facing content in the final response. Cron jobs run autonomously with no user\npresent — they cannot ask questions or request clarification.\n\nImportant safety rule: cron-run sessions should not recursively schedule more cron jobs.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"description": "One of: create, list, update, pause, resume, remove, run"
},
"job_id": {
"type": "string",
"description": "Required for update/pause/resume/remove/run"
},
"prompt": {
"type": "string",
"description": "For create: the full self-contained prompt. If skills are also provided, this becomes the task instruction paired with those skills."
},
"schedule": {
"type": "string",
"description": "For create/update: '30m', 'every 2h', '0 9 * * *', or ISO timestamp"
},
"name": {
"type": "string",
"description": "Optional human-friendly name"
},
"repeat": {
"type": "integer",
"description": "Optional repeat count. Omit for defaults (once for one-shot, forever for recurring)."
},
"deliver": {
"type": "string",
"description": "Omit this parameter to auto-deliver back to the current chat and topic (recommended). Auto-detection preserves thread/topic context. Only set explicitly when the user asks to deliver somewhere OTHER than the current conversation. Values: 'origin' (same as omitting), 'local' (no delivery, save only), 'all' (fan out to every connected home channel), or platform:chat_id:thread_id for a specific destination. Combine with comma: 'origin,all' delivers to the origin plus every other connected channel. Examples: 'telegram:-1001234567890:17585', 'discord:#engineering', 'sms:+15551234567', 'all'. WARNING: 'platform:chat_id' without :thread_id loses topic targeting. 'all' resolves at fire time, so a job created before a channel was wired up will pick it up automatically once connected."
},
"skills": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional ordered list of skill names to load before executing the cron prompt. On update, pass an empty array to clear attached skills."
},
"model": {
"type": "object",
"description": "Optional per-job model override. If provider is omitted, the current main provider is pinned at creation time so the job stays stable.",
"properties": {
"provider": {
"type": "string",
"description": "Provider name (e.g. 'openrouter', 'anthropic', or 'custom:' for a provider defined in custom_providers config — always include the ':' suffix, never pass the bare 'custom'). Omit to use and pin the current provider."
},
"model": {
"type": "string",
"description": "Model name (e.g. 'anthropic/claude-sonnet-4', 'claude-sonnet-4')"
}
},
"required": [
"model"
]
},
"script": {
"type": "string",
"description": "Optional path to a script that runs each tick. In the default mode its stdout is injected into the agent's prompt as context (data-collection / change-detection pattern). With no_agent=True, the script IS the job and its stdout is delivered verbatim (classic watchdog pattern). Relative paths resolve under ~/.hermes/scripts/. ``.sh``/``.bash`` extensions run via bash, everything else via Python. On update, pass empty string to clear."
},
"no_agent": {
"type": "boolean",
"default": false,
"description": "Default: False (LLM-driven job — the agent runs the prompt each tick). Set True to skip the LLM entirely: the scheduler just runs ``script`` on schedule and delivers its stdout verbatim. No tokens, no agent loop, no model override honoured. \n\nREQUIREMENTS when True: ``script`` MUST be set (``prompt`` and ``skills`` are ignored). \n\nDELIVERY SEMANTICS when True: (a) non-empty stdout is sent verbatim as the message; (b) EMPTY stdout means SILENT — nothing is sent to the user and they won't see anything happened, so design your script to stay quiet when there's nothing to report (the watchdog pattern); (c) non-zero exit / timeout sends an error alert so a broken watchdog can't fail silently. \n\nWHEN TO USE True: recurring script-only pings where the script itself produces the exact message text (memory/disk/GPU watchdogs, threshold alerts, heartbeats, CI notifications, API pollers with a fixed output shape). WHEN TO USE False (default): anything that needs reasoning — summarize a feed, draft a daily briefing, pick interesting items, rephrase data for a human, follow conditional logic based on content."
},
"context_from": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional job ID or list of job IDs whose most recent completed output is injected into the prompt as context before each run. Use this to chain cron jobs: job A collects data, job B processes it. Each entry must be a valid job ID (from cronjob action='list'). Note: injects the most recent completed output — does not wait for upstream jobs running in the same tick. On update, pass an empty array to clear."
},
"enabled_toolsets": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional list of toolset names to restrict the job's agent to (e.g. [\"web\", \"terminal\", \"file\", \"delegation\"]). When set, only tools from these toolsets are loaded, significantly reducing input token overhead. When omitted, all default tools are loaded. Infer from the job's prompt — e.g. use \"web\" if it calls web_search, \"terminal\" if it runs scripts, \"file\" if it reads files, \"delegation\" if it calls delegate_task. On update, pass an empty array to clear."
},
"workdir": {
"type": "string",
"description": "Optional absolute path to run the job from. When set, AGENTS.md / CLAUDE.md / .cursorrules from that directory are injected into the system prompt, and the terminal/file/code_exec tools use it as their working directory — useful for running a job inside a specific project repo. Must be an absolute path that exists. When unset (default), preserves the original behaviour: no project context files, tools use the scheduler's cwd. On update, pass an empty string to clear. Jobs with workdir run sequentially (not parallel) to keep per-job directories isolated."
}
},
"required": [
"action"
]
}
}
},
{
"type": "function",
"function": {
"name": "delegate_task",
"description": "Spawn one or more subagents to work on tasks in isolated contexts. Each subagent gets its own conversation, terminal session, and toolset. Only the final summary is returned -- intermediate tool results never enter your context window.\n\nTWO MODES (one of 'goal' or 'tasks' is required):\n1. Single task: provide 'goal' (+ optional context, toolsets)\n2. Batch (parallel): provide 'tasks' array with up to 3 items concurrently for this user (configured via delegation.max_concurrent_children in config.yaml). All run in parallel and results are returned together. Nested delegation is OFF for this user (max_spawn_depth=1): every child is a leaf and cannot delegate further. Raise delegation.max_spawn_depth in config.yaml to enable nesting.\n\nWHEN TO USE delegate_task:\n- Reasoning-heavy subtasks (debugging, code review, research synthesis)\n- Tasks that would flood your context with intermediate data\n- Parallel independent workstreams (research A and B simultaneously)\n\nWHEN NOT TO USE (use these instead):\n- Mechanical multi-step work with no reasoning needed -> use execute_code\n- Single tool call -> just call the tool directly\n- Tasks needing user interaction -> subagents cannot use clarify\n- Durable long-running work that must outlive the current turn -> use cronjob (action='create') or terminal(background=True, notify_on_complete=True) instead. delegate_task runs SYNCHRONOUSLY inside the parent turn: if the parent is interrupted (user sends a new message, /stop, /new) the child is cancelled with status='interrupted' and its work is discarded. Children cannot continue in the background.\n\nIMPORTANT:\n- Subagents have NO memory of your conversation. Pass all relevant info (file paths, error messages, constraints) via the 'context' field.\n- If the user is writing in a non-English language, or asked for output in a specific language / tone / style, say so in 'context' (e.g. \"respond in Chinese\", \"return output in Japanese\"). Otherwise subagents default to English and their summaries will contaminate your final reply with the wrong language.\n- Subagent summaries are SELF-REPORTS, not verified facts. A subagent that claims \"uploaded successfully\" or \"file written\" may be wrong. For operations with external side-effects (HTTP POST/PUT, remote writes, file creation at shared paths, publishing), require the subagent to return a verifiable handle (URL, ID, absolute path, HTTP status) and verify it yourself — fetch the URL, stat the file, read back the content — before telling the user the operation succeeded.\n- Leaf subagents (role='leaf', the default) CANNOT call: delegate_task, clarify, memory, send_message, execute_code.\n- Orchestrator subagents (role='orchestrator') retain delegate_task so they can spawn their own workers, but still cannot use clarify, memory, send_message, or execute_code. Orchestrators are bounded by max_spawn_depth=1 for this user and can be disabled globally via delegation.orchestrator_enabled=false.\n- Each subagent gets its own terminal session (separate working directory and state).\n- Results are always returned as an array, one entry per task.",
"parameters": {
"type": "object",
"properties": {
"goal": {
"type": "string",
"description": "What the subagent should accomplish. Be specific and self-contained -- the subagent knows nothing about your conversation history."
},
"context": {
"type": "string",
"description": "Background information the subagent needs: file paths, error messages, project structure, constraints. The more specific you are, the better the subagent performs."
},
"toolsets": {
"type": "array",
"items": {
"type": "string"
},
"description": "Toolsets to enable for this subagent. Default: inherits your enabled toolsets. Available toolsets: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'video_gen', 'vision', 'web', 'yuanbao'. Common patterns: ['terminal', 'file'] for code work, ['web'] for research, ['browser'] for web interaction, ['terminal', 'file', 'web'] for full-stack tasks."
},
"tasks": {
"type": "array",
"items": {
"type": "object",
"properties": {
"goal": {
"type": "string",
"description": "Task goal"
},
"context": {
"type": "string",
"description": "Task-specific context"
},
"toolsets": {
"type": "array",
"items": {
"type": "string"
},
"description": "Toolsets for this specific task. Available: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'video_gen', 'vision', 'web', 'yuanbao'. Use 'web' for network access, 'terminal' for shell, 'browser' for web interaction."
},
"acp_command": {
"type": "string",
"description": "Per-task ACP command override (e.g. 'copilot'). Overrides the top-level acp_command for this task only. Do NOT set unless the user explicitly told you an ACP CLI is installed."
},
"acp_args": {
"type": "array",
"items": {
"type": "string"
},
"description": "Per-task ACP args override. Leave empty unless acp_command is set."
},
"role": {
"type": "string",
"enum": [
"leaf",
"orchestrator"
],
"description": "Per-task role override. See top-level 'role' for semantics."
}
},
"required": [
"goal"
]
},
"description": "Batch mode: tasks to run in parallel (up to 3 for this user, set via delegation.max_concurrent_children). Each gets its own subagent with isolated context and terminal session. When provided, top-level goal/context/toolsets are ignored."
},
"role": {
"type": "string",
"enum": [
"leaf",
"orchestrator"
],
"description": "Role of the child agent. 'leaf' (default) = focused worker, cannot delegate further. 'orchestrator' = can use delegate_task to spawn its own workers. Nesting is OFF for this user (max_spawn_depth=1); 'orchestrator' is silently forced to 'leaf'. Raise delegation.max_spawn_depth in config.yaml to enable."
},
"acp_command": {
"type": "string",
"description": "Override ACP command for child agents (e.g. 'copilot'). When set, children use ACP subprocess transport instead of inheriting the parent's transport. Requires an ACP-compatible CLI (currently GitHub Copilot CLI via 'copilot --acp --stdio'). See agent/copilot_acp_client.py for the implementation. IMPORTANT: Do NOT set this unless the user has explicitly told you a specific ACP-compatible CLI is installed and configured. Leave empty to use the parent's default transport (Hermes subagents)."
},
"acp_args": {
"type": "array",
"items": {
"type": "string"
},
"description": "Arguments for the ACP command (default: ['--acp', '--stdio']). Only used when acp_command is set. Leave empty unless acp_command is explicitly provided."
}
}
}
}
},
{
"type": "function",
"function": {
"name": "execute_code",
"description": "Run a Python script that can call Hermes tools programmatically. Use this when you need 3+ tool calls with processing logic between them, need to filter/reduce large tool outputs before they enter your context, need conditional branching (if X then Y else Z), or need to loop (fetch N pages, process N files, retry on failure).\n\nUse normal tool calls instead when: single tool call with no processing, you need to see the full result and apply complex reasoning, or the task requires interactive user input.\n\nAvailable via `from hermes_tools import ...`:\n\n web_search(query: str, limit: int = 5) -> dict\n Returns {\"data\": {\"web\": [{\"url\", \"title\", \"description\"}, ...]}}\n web_extract(urls: list[str]) -> dict\n Returns {\"results\": [{\"url\", \"title\", \"content\", \"error\"}, ...]} where content is markdown\n read_file(path: str, offset: int = 1, limit: int = 500) -> dict\n Lines are 1-indexed. Returns {\"content\": \"...\", \"total_lines\": N}\n write_file(path: str, content: str) -> dict\n Always overwrites the entire file.\n search_files(pattern: str, target=\"content\", path=\".\", file_glob=None, limit=50) -> dict\n target: \"content\" (search inside files) or \"files\" (find files by name). Returns {\"matches\": [...]}\n patch(path: str, old_string: str, new_string: str, replace_all: bool = False) -> dict\n Replaces old_string with new_string in the file.\n terminal(command: str, timeout=None, workdir=None) -> dict\n Foreground only (no background/pty). Returns {\"output\": \"...\", \"exit_code\": N}\n\nLimits: 5-minute timeout, 50KB stdout cap, max 50 tool calls per script. terminal() is foreground-only (no background or pty).\n\nScripts run in the session's working directory with the active venv's python, so project deps (pandas, etc.) and relative paths work like in terminal().\n\nPrint your final result to stdout. Use Python stdlib (json, re, math, csv, datetime, collections, etc.) for processing between tool calls.\n\nAlso available (no import needed — built into hermes_tools):\n json_parse(text: str) — json.loads with strict=False; use for terminal() output with control chars\n shell_quote(s: str) — shlex.quote(); use when interpolating dynamic strings into shell commands\n retry(fn, max_attempts=3, delay=2) — retry with exponential backoff for transient failures",
"parameters": {
"type": "object",
"properties": {
"code": {
"type": "string",
"description": "Python code to execute. Import tools with `from hermes_tools import web_search, terminal, ...` and print your final result to stdout."
}
},
"required": [
"code"
]
}
}
},
{
"type": "function",
"function": {
"name": "image_generate",
"description": "Generate high-quality images from text prompts. The underlying backend (FAL, OpenAI, etc.) and model are user-configured and not selectable by the agent. Returns either a URL or an absolute file path in the `image` field; display it with markdown  and the gateway will deliver it.",
"parameters": {
"type": "object",
"properties": {
"prompt": {
"type": "string",
"description": "The text prompt describing the desired image. Be detailed and descriptive."
},
"aspect_ratio": {
"type": "string",
"enum": [
"landscape",
"square",
"portrait"
],
"description": "The aspect ratio of the generated image. 'landscape' is 16:9 wide, 'portrait' is 16:9 tall, 'square' is 1:1.",
"default": "landscape"
}
},
"required": [
"prompt"
]
}
}
},
{
"type": "function",
"function": {
"name": "mcp_context7_query_docs",
"description": "Retrieves and queries up-to-date documentation and code examples from Context7 for any programming library or framework.\n\nYou must call 'Resolve Context7 Library ID' tool first to obtain the exact Context7-compatible library ID required to use this tool, UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.\n\nDo not call this tool more than 3 times per question.",
"parameters": {
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"libraryId": {
"type": "string",
"description": "Exact Context7-compatible library ID (e.g., '/mongodb/docs', '/vercel/next.js', '/supabase/supabase', '/vercel/next.js/v14.3.0-canary.87') retrieved from 'resolve-library-id' or directly from user query in the format '/org/project' or '/org/project/version'."
},
"query": {
"type": "string",
"description": "The question or task you need help with. Be specific and include relevant details. Good: 'How to set up authentication with JWT in Express.js' or 'React useEffect cleanup function examples'. Bad: 'auth' or 'hooks'. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query."
}
},
"required": [
"libraryId",
"query"
]
}
}
},
{
"type": "function",
"function": {
"name": "mcp_context7_resolve_library_id",
"description": "Resolves a package/product name to a Context7-compatible library ID and returns matching libraries.\n\nYou MUST call this function before 'Query Documentation' tool to obtain a valid Context7-compatible library ID UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.\n\nEach result includes:\n- Library ID: Context7-compatible identifier (format: /org/project)\n- Name: Library or package name\n- Description: Short summary\n- Code Snippets: Number of available code examples\n- Source Reputation: Authority indicator (High, Medium, Low, or Unknown)\n- Benchmark Score: Quality indicator (100 is the highest score)\n- Versions: List of versions if available. Use one of those versions if the user provides a version in their query. The format of the version is /org/project/version.\n\nFor best results, select libraries based on name match, source reputation, snippet coverage, benchmark score, and relevance to your use case.\n\nSelection Process:\n1. Analyze the query to understand what library/package the user is looking for\n2. Return the most relevant match based on:\n- Name similarity to the query (exact matches prioritized)\n- Description relevance to the query's intent\n- Documentation coverage (prioritize libraries with higher Code Snippet counts)\n- Source reputation (consider libraries with High or Medium reputation more authoritative)\n- Benchmark Score: Quality indicator (100 is the highest score)\n\nResponse Format:\n- Return the selected library ID in a clearly marked section\n- Provide a brief explanation for why this library was chosen\n- If multiple good matches exist, acknowledge this but proceed with the most relevant one\n- If no good matches exist, clearly state this and suggest query refinements\n\nFor ambiguous queries, request clarification before proceeding with a best-guess match.\n\nIMPORTANT: Do not call this tool more than 3 times per question. If you cannot find what you need after 3 calls, use the best result you have.",
"parameters": {
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The question or task you need help with. This is used to rank library results by relevance to what the user is trying to accomplish. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query."
},
"libraryName": {
"type": "string",
"description": "Library name to search for and retrieve a Context7-compatible library ID. Use the official library name with proper punctuation — e.g., 'Next.js' instead of 'nextjs', 'Customer.io' instead of 'customerio', 'Three.js' instead of 'threejs'."
}
},
"required": [
"query",
"libraryName"
]
}
}
},
{
"type": "function",
"function": {
"name": "memory",
"description": "Save durable information to persistent memory that survives across sessions. Memory is injected into future turns, so keep it compact and focused on facts that will still matter later.\n\nWHEN TO SAVE (do this proactively, don't wait to be asked):\n- User corrects you or says 'remember this' / 'don't do that again'\n- User shares a preference, habit, or personal detail (name, role, timezone, coding style)\n- You discover something about the environment (OS, installed tools, project structure)\n- You learn a convention, API quirk, or workflow specific to this user's setup\n- You identify a stable fact that will be useful again in future sessions\n\nPRIORITY: User preferences and corrections > environment facts > procedural knowledge. The most valuable memory prevents the user from having to repeat themselves.\n\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts.\nIf you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\n\nTWO TARGETS:\n- 'user': who the user is -- name, role, preferences, communication style, pet peeves\n- 'memory': your notes -- environment facts, project conventions, tool quirks, lessons learned\n\nACTIONS: add (new entry), replace (update existing -- old_text identifies it), remove (delete -- old_text identifies it).\n\nSKIP: trivial/obvious info, things easily re-discovered, raw data dumps, and temporary task state.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"add",
"replace",
"remove"
],
"description": "The action to perform."
},
"target": {
"type": "string",
"enum": [
"memory",
"user"
],
"description": "Which memory store: 'memory' for personal notes, 'user' for user profile."
},
"content": {
"type": "string",
"description": "The entry content. Required for 'add' and 'replace'."
},
"old_text": {
"type": "string",
"description": "Short unique substring identifying the entry to replace or remove."
}
},
"required": [
"action",
"target"
]
}
}
},
{
"type": "function",
"function": {
"name": "mixture_of_agents",
"description": "Route a hard problem through multiple frontier LLMs collaboratively. Makes 5 API calls (4 reference models + 1 aggregator) with maximum reasoning effort — use sparingly for genuinely difficult problems. Best for: complex math, advanced algorithms, multi-step analytical reasoning, problems benefiting from diverse perspectives.",
"parameters": {
"type": "object",
"properties": {
"user_prompt": {
"type": "string",
"description": "The complex query or problem to solve using multiple AI models. Should be a challenging problem that benefits from diverse perspectives and collaborative reasoning."
}
},
"required": [
"user_prompt"
]
}
}
},
{
"type": "function",
"function": {
"name": "patch",
"description": "Targeted find-and-replace edits in files. Use this instead of sed/awk in terminal. Uses fuzzy matching (9 strategies) so minor whitespace/indentation differences won't break it. Returns a unified diff. Auto-runs syntax checks after editing.\n\nREPLACE MODE (mode='replace', default): find a unique string and replace it. REQUIRED PARAMETERS: mode, path, old_string, new_string.\nPATCH MODE (mode='patch'): apply V4A multi-file patches for bulk changes. REQUIRED PARAMETERS: mode, patch.",
"parameters": {
"type": "object",
"properties": {
"mode": {
"type": "string",
"enum": [
"replace",
"patch"
],
"description": "Edit mode. 'replace' (default): requires path + old_string + new_string. 'patch': requires patch content only.",
"default": "replace"
},
"path": {
"type": "string",
"description": "REQUIRED when mode='replace'. File path to edit."
},
"old_string": {
"type": "string",
"description": "REQUIRED when mode='replace'. Exact text to find and replace. Must be unique in the file unless replace_all=true. Include surrounding context lines to ensure uniqueness."
},
"new_string": {
"type": "string",
"description": "REQUIRED when mode='replace'. Replacement text. Pass empty string '' to delete the matched text."
},
"replace_all": {
"type": "boolean",
"description": "Replace all occurrences instead of requiring a unique match (default: false)",
"default": false
},
"patch": {
"type": "string",
"description": "REQUIRED when mode='patch'. V4A format patch content. Format:\n*** Begin Patch\n*** Update File: path/to/file\n@@ context hint @@\n context line\n-removed line\n+added line\n*** End Patch"
}
},
"required": [
"mode"
]
}
}
},
{
"type": "function",
"function": {
"name": "process",
"description": "Manage background processes started with terminal(background=true). Actions: 'list' (show all), 'poll' (check status + new output), 'log' (full output with pagination), 'wait' (block until done or timeout), 'kill' (terminate), 'write' (send raw stdin data without newline), 'submit' (send data + Enter, for answering prompts), 'close' (close stdin/send EOF).",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"list",
"poll",
"log",
"wait",
"kill",
"write",
"submit",
"close"
],
"description": "Action to perform on background processes"
},
"session_id": {
"type": "string",
"description": "Process session ID (from terminal background output). Required for all actions except 'list'."
},
"data": {
"type": "string",
"description": "Text to send to process stdin (for 'write' and 'submit' actions)"
},
"timeout": {
"type": "integer",
"description": "Max seconds to block for 'wait' action. Returns partial output on timeout.",
"minimum": 1
},
"offset": {
"type": "integer",
"description": "Line offset for 'log' action (default: last 200 lines)"
},
"limit": {
"type": "integer",
"description": "Max lines to return for 'log' action",
"minimum": 1
}
},
"required": [
"action"
]
}
}
},
{
"type": "function",
"function": {
"name": "read_file",
"description": "Read a text file with line numbers and pagination. Use this instead of cat/head/tail in terminal. Output format: 'LINE_NUM|CONTENT'. Suggests similar filenames if not found. Use offset and limit for large files. Reads exceeding ~100K characters are rejected; use offset and limit to read specific sections of large files. NOTE: Cannot read images or binary files — use vision_analyze for images.",
"parameters": {
"type": "object",
"properties": {
"path": {
"type": "string",
"description": "Path to the file to read (absolute, relative, or ~/path)"
},
"offset": {
"type": "integer",
"description": "Line number to start reading from (1-indexed, default: 1)",
"default": 1,
"minimum": 1
},
"limit": {
"type": "integer",
"description": "Maximum number of lines to read (default: 500, max: 2000)",
"default": 500,
"maximum": 2000
}
},
"required": [
"path"
]
}
}
},
{
"type": "function",
"function": {
"name": "search_files",
"description": "Search file contents or find files by name. Use this instead of grep/rg/find/ls in terminal. Ripgrep-backed, faster than shell equivalents.\n\nContent search (target='content'): Regex search inside files. Output modes: full matches with line numbers, file paths only, or match counts.\n\nFile search (target='files'): Find files by glob pattern (e.g., '*.py', '*config*'). Also use this instead of ls — results sorted by modification time.",
"parameters": {
"type": "object",
"properties": {
"pattern": {
"type": "string",
"description": "Regex pattern for content search, or glob pattern (e.g., '*.py') for file search"
},
"target": {
"type": "string",
"enum": [
"content",
"files"
],
"description": "'content' searches inside file contents, 'files' searches for files by name",
"default": "content"
},
"path": {
"type": "string",
"description": "Directory or file to search in (default: current working directory)",
"default": "."
},
"file_glob": {
"type": "string",
"description": "Filter files by pattern in grep mode (e.g., '*.py' to only search Python files)"
},
"limit": {
"type": "integer",
"description": "Maximum number of results to return (default: 50)",
"default": 50
},
"offset": {
"type": "integer",
"description": "Skip first N results for pagination (default: 0)",
"default": 0
},
"output_mode": {
"type": "string",
"enum": [
"content",
"files_only",
"count"
],
"description": "Output format for grep mode: 'content' shows matching lines with line numbers, 'files_only' lists file paths, 'count' shows match counts per file",
"default": "content"
},
"context": {
"type": "integer",
"description": "Number of context lines before and after each match (grep mode only)",
"default": 0
}
},
"required": [
"pattern"
]
}
}
},
{
"type": "function",
"function": {
"name": "session_search",
"description": "Search your long-term memory of past conversations, or browse recent sessions. This is your recall -- every past session is searchable, and this tool summarizes what happened.\n\nTWO MODES:\n1. Recent sessions (no query): Call with no arguments to see what was worked on recently. Returns titles, previews, and timestamps. Zero LLM cost, instant. Start here when the user asks what were we working on or what did we do recently.\n2. Keyword search (with query): Search for specific topics across all past sessions. Returns LLM-generated summaries of matching sessions.\n\nUSE THIS PROACTIVELY when:\n- The user says 'we did this before', 'remember when', 'last time', 'as I mentioned'\n- The user asks about a topic you worked on before but don't have in current context\n- The user references a project, person, or concept that seems familiar but isn't in memory\n- You want to check if you've solved a similar problem before\n- The user asks 'what did we do about X?' or 'how did we fix Y?'\n\nDon't hesitate to search when it is actually cross-session -- it's fast and cheap. Better to search and confirm than to guess or ask the user to repeat themselves.\n\nSearch syntax: keywords joined with OR for broad recall (elevenlabs OR baseten OR funding), phrases for exact match (\"docker networking\"), boolean (python NOT java), prefix (deploy*). IMPORTANT: Use OR between keywords for best results — FTS5 defaults to AND which misses sessions that only mention some terms. If a broad OR query returns nothing, try individual keyword searches in parallel. Returns summaries of the top matching sessions.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Search query — keywords, phrases, or boolean expressions to find in past sessions. Omit this parameter entirely to browse recent sessions instead (returns titles, previews, timestamps with no LLM cost)."
},
"role_filter": {
"type": "string",
"description": "Optional: only search messages from specific roles (comma-separated). E.g. 'user,assistant' to skip tool outputs."
},
"limit": {
"type": "integer",
"description": "Max sessions to summarize (default: 3, max: 5).",
"default": 3
}
}
}
}
},
{
"type": "function",
"function": {
"name": "skill_manage",
"description": "Manage skills (create, update, delete). Skills are your procedural memory — reusable approaches for recurring task types. New skills go to ~/.hermes/skills/; existing skills can be modified wherever they live.\n\nActions: create (full SKILL.md + optional category), patch (old_string/new_string — preferred for fixes), edit (full SKILL.md rewrite — major overhauls only), delete, write_file, remove_file.\n\nOn delete, pass `absorbed_into=` when you're merging this skill's content into another one, or `absorbed_into=\"\"` when you're pruning it with no forwarding target. This lets the curator tell consolidation from pruning without guessing, so downstream consumers (cron jobs that reference the old skill name, etc.) get updated correctly. The target you name in `absorbed_into` must already exist — create/patch the umbrella first, then delete.\n\nCreate when: complex task succeeded (5+ calls), errors overcome, user-corrected approach worked, non-trivial workflow discovered, or user asks you to remember a procedure.\nUpdate when: instructions stale/wrong, OS-specific failures, missing steps or pitfalls found during use. If you used a skill and hit issues not covered by it, patch it immediately.\n\nAfter difficult/iterative tasks, offer to save as a skill. Skip for simple one-offs. Confirm with user before creating/deleting.\n\nGood skills: trigger conditions, numbered steps with exact commands, pitfalls section, verification steps. Use skill_view() to see format examples.\n\nPinned skills are protected from deletion only — skill_manage(action='delete') will refuse with a message pointing the user to `hermes curator unpin `. Patches and edits go through on pinned skills so you can still improve them as pitfalls come up; pin only guards against irrecoverable loss.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"create",
"patch",
"edit",
"delete",
"write_file",
"remove_file"
],
"description": "The action to perform."
},
"name": {
"type": "string",
"description": "Skill name (lowercase, hyphens/underscores, max 64 chars). Must match an existing skill for patch/edit/delete/write_file/remove_file."
},
"content": {
"type": "string",
"description": "Full SKILL.md content (YAML frontmatter + markdown body). Required for 'create' and 'edit'. For 'edit', read the skill first with skill_view() and provide the complete updated text."
},
"old_string": {
"type": "string",
"description": "Text to find in the file (required for 'patch'). Must be unique unless replace_all=true. Include enough surrounding context to ensure uniqueness."
},
"new_string": {
"type": "string",
"description": "Replacement text (required for 'patch'). Can be empty string to delete the matched text."
},
"replace_all": {
"type": "boolean",
"description": "For 'patch': replace all occurrences instead of requiring a unique match (default: false)."
},
"category": {
"type": "string",
"description": "Optional category/domain for organizing the skill (e.g., 'devops', 'data-science', 'mlops'). Creates a subdirectory grouping. Only used with 'create'."
},
"file_path": {
"type": "string",
"description": "Path to a supporting file within the skill directory. For 'write_file'/'remove_file': required, must be under references/, templates/, scripts/, or assets/. For 'patch': optional, defaults to SKILL.md if omitted."
},
"file_content": {
"type": "string",
"description": "Content for the file. Required for 'write_file'."
},
"absorbed_into": {
"type": "string",
"description": "For 'delete' only — declares intent so the curator can tell consolidation from pruning without guessing. Pass the umbrella skill name when this skill's content was merged into another (the target must already exist). Pass an empty string when the skill is truly stale and being pruned with no forwarding target. Omitting the arg on delete is supported for backward compatibility but downstream tooling (e.g. cron-job skill reference rewriting) will have to guess at intent."
}
},
"required": [
"action",
"name"
]
}
}
},
{
"type": "function",
"function": {
"name": "skill_view",
"description": "Skills allow for loading information about specific tasks and workflows, as well as scripts and templates. Load a skill's full content or access its linked files (references, templates, scripts). First call returns SKILL.md content plus a 'linked_files' dict showing available references/templates/scripts. To access those, call again with file_path parameter.",
"parameters": {
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "The skill name (use skills_list to see available skills). For plugin-provided skills, use the qualified form 'plugin:skill' (e.g. 'superpowers:writing-plans')."
},
"file_path": {
"type": "string",
"description": "OPTIONAL: Path to a linked file within the skill (e.g., 'references/api.md', 'templates/config.yaml', 'scripts/validate.py'). Omit to get the main SKILL.md content."
}
},
"required": [
"name"
]
}
}
},
{
"type": "function",
"function": {
"name": "skills_list",
"description": "List available skills (name + description). Use skill_view(name) to load full content.",
"parameters": {
"type": "object",
"properties": {
"category": {
"type": "string",
"description": "Optional category filter to narrow results"
}
}
}
}
},
{
"type": "function",
"function": {
"name": "terminal",
"description": "Execute shell commands on a Linux environment. Filesystem usually persists between calls.\n\nDo NOT use cat/head/tail to read files — use read_file instead.\nDo NOT use grep/rg/find to search — use search_files instead.\nDo NOT use ls to list directories — use search_files(target='files') instead.\nDo NOT use sed/awk to edit files — use patch instead.\nDo NOT use echo/cat heredoc to create files — use write_file instead.\nReserve terminal for: builds, installs, git, processes, scripts, network, package managers, and anything that needs a shell.\n\nForeground (default): Commands return INSTANTLY when done, even if the timeout is high. Set timeout=300 for long builds/scripts — you'll still get the result in seconds if it's fast. Prefer foreground for short commands.\nBackground: Set background=true to get a session_id. Two patterns:\n (1) Long-lived processes that never exit (servers, watchers).\n (2) Long-running tasks with notify_on_complete=true — you can keep working on other things and the system auto-notifies you when the task finishes. Great for test suites, builds, deployments, or anything that takes more than a minute.\nFor servers/watchers, do NOT use shell-level background wrappers (nohup/disown/setsid/trailing '&') in foreground mode. Use background=true so Hermes can track lifecycle and output.\nAfter starting a server, verify readiness with a health check or log signal, then run tests in a separate terminal() call. Avoid blind sleep loops.\nUse process(action=\"poll\") for progress checks, process(action=\"wait\") to block until done.\nWorking directory: Use 'workdir' for per-command cwd.\nPTY mode: Set pty=true for interactive CLI tools (Codex, Claude Code, Python REPL).\n\nDo NOT use vim/nano/interactive tools without pty=true — they hang without a pseudo-terminal. Pipe git output to cat if it might page.\n",
"parameters": {
"type": "object",
"properties": {
"command": {
"type": "string",
"description": "The command to execute on the VM"
},
"background": {
"type": "boolean",
"description": "Run the command in the background. Two patterns: (1) Long-lived processes that never exit (servers, watchers). (2) Long-running tasks paired with notify_on_complete=true — you can keep working and get notified when the task finishes. For short commands, prefer foreground with a generous timeout instead.",
"default": false
},
"timeout": {
"type": "integer",
"description": "Max seconds to wait (default: 180, foreground max: 600). Returns INSTANTLY when command finishes — set high for long tasks, you won't wait unnecessarily. Foreground timeout above 600s is rejected; use background=true for longer commands.",
"minimum": 1
},
"workdir": {
"type": "string",
"description": "Working directory for this command (absolute path). Defaults to the session working directory."
},
"pty": {
"type": "boolean",
"description": "Run in pseudo-terminal (PTY) mode for interactive CLI tools like Codex, Claude Code, or Python REPL. Only works with local and SSH backends. Default: false.",
"default": false
},
"notify_on_complete": {
"type": "boolean",
"description": "When true (and background=true), you'll be automatically notified exactly once when the process finishes. **This is the right choice for almost every long-running task** — tests, builds, deployments, multi-item batch jobs, anything that takes over a minute and has a defined end. Use this and keep working on other things; the system notifies you on exit. MUTUALLY EXCLUSIVE with watch_patterns — when both are set, watch_patterns is dropped.",
"default": false
},
"watch_patterns": {
"type": "array",
"items": {
"type": "string"
},
"description": "Strings to watch for in background process output. HARD RATE LIMIT: at most 1 notification per 15 seconds per process — matches arriving inside the cooldown are dropped. After 3 consecutive 15-second windows with dropped matches, watch_patterns is automatically disabled for that process and promoted to notify_on_complete behavior (one notification on exit, no more mid-process spam). USE ONLY for truly rare, one-shot mid-process signals on LONG-LIVED processes that will never exit on their own — e.g. ['Application startup complete'] on a server so you know when to hit its endpoint, or ['migration done'] on a daemon. DO NOT use for: (1) end-of-run markers like 'DONE'/'PASS' — use notify_on_complete instead; (2) error patterns like 'ERROR'/'Traceback' in loops or multi-item batch jobs — they fire on every iteration and you'll hit the strike limit fast; (3) anything you'd ever combine with notify_on_complete. When in doubt, choose notify_on_complete. MUTUALLY EXCLUSIVE with notify_on_complete — set one, not both."
}
},
"required": [
"command"
]
}
}
},
{
"type": "function",
"function": {
"name": "text_to_speech",
"description": "Convert text to speech audio. Returns a MEDIA: path that the platform delivers as native audio. Compatible providers render as a voice bubble on Telegram; otherwise audio is sent as a regular attachment. In CLI mode, saves to ~/voice-memos/. Voice and provider are user-configured (built-in providers like edge/openai or custom command providers under tts.providers.), not model-selected.",
"parameters": {
"type": "object",
"properties": {
"text": {
"type": "string",
"description": "The text to convert to speech. Provider-specific character caps apply and are enforced automatically (OpenAI 4096, xAI 15000, MiniMax 10000, ElevenLabs 5k-40k depending on model); over-long input is truncated."
},
"output_path": {
"type": "string",
"description": "Optional custom file path to save the audio. Defaults to ~/.hermes/audio_cache/.mp3"
}
},
"required": [
"text"
]
}
}
},
{
"type": "function",
"function": {
"name": "todo",
"description": "Manage your task list for the current session. Use for complex tasks with 3+ steps or when the user provides multiple tasks. Call with no parameters to read the current list.\n\nWriting:\n- Provide 'todos' array to create/update items\n- merge=false (default): replace the entire list with a fresh plan\n- merge=true: update existing items by id, add any new ones\n\nEach item: {id: string, content: string, status: pending|in_progress|completed|cancelled}\nList order is priority. Only ONE item in_progress at a time.\nMark items completed immediately when done. If something fails, cancel it and add a revised item.\n\nAlways returns the full current list.",
"parameters": {
"type": "object",
"properties": {
"todos": {
"type": "array",
"description": "Task items to write. Omit to read current list.",
"items": {
"type": "object",
"properties": {
"id": {
"type": "string",
"description": "Unique item identifier"
},
"content": {
"type": "string",
"description": "Task description"
},
"status": {
"type": "string",
"enum": [
"pending",
"in_progress",
"completed",
"cancelled"
],
"description": "Current status"
}
},
"required": [
"id",
"content",
"status"
]
}
},
"merge": {
"type": "boolean",
"description": "true: update existing items by id, add new ones. false (default): replace the entire list.",
"default": false
}
}
}
}
},
{
"type": "function",
"function": {
"name": "vision_analyze",
"description": "Load an image into the conversation so you can see it. Accepts a URL, local file path, or data URL. When your active model has native vision, the image is attached to your context directly and you read the pixels yourself on the next turn — call this any time the user references an image (filepath in their message, URL in tool output, screenshot from the browser, etc.). For non-vision models, falls back to an auxiliary vision model that returns a text description.",
"parameters": {
"type": "object",
"properties": {
"image_url": {
"type": "string",
"description": "Image URL (http/https), local file path, or data: URL to load."
},
"question": {
"type": "string",
"description": "Your specific question or request about the image. Optional context the model uses on the next turn after seeing the image."
}
},
"required": [
"image_url",
"question"
]
}
}
},
{
"type": "function",
"function": {
"name": "web_extract",
"description": "Extract content from web page URLs. Returns page content in markdown format. Also works with PDF URLs (arxiv papers, documents, etc.) — pass the PDF link directly and it converts to markdown text. Pages under 5000 chars return full markdown; larger pages are LLM-summarized and capped at ~5000 chars per page. Pages over 2M chars are refused. If a URL fails or times out, use the browser tool to access it instead.",
"parameters": {
"type": "object",
"properties": {
"urls": {
"type": "array",
"items": {
"type": "string"
},
"description": "List of URLs to extract content from (max 5 URLs per call)",
"maxItems": 5
}
},
"required": [
"urls"
]
}
}
},
{
"type": "function",
"function": {
"name": "web_search",
"description": "Search the web for information. Returns up to 5 results by default with titles, URLs, and descriptions. The query is passed through to the configured backend, so operators such as site:domain, filetype:pdf, intitle:word, -term, and \"exact phrase\" may work when the backend supports them.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The search query to look up on the web. You may include backend-supported operators such as site:example.com, filetype:pdf, intitle:word, -term, or \"exact phrase\"."
},
"limit": {
"type": "integer",
"description": "Maximum number of results to return. Defaults to 5.",
"minimum": 1,
"maximum": 100,
"default": 5
}
},
"required": [
"query"
]
}
}
},
{
"type": "function",
"function": {
"name": "write_file",
"description": "Write content to a file, completely replacing existing content. Use this instead of echo/cat heredoc in terminal. Creates parent directories automatically. OVERWRITES the entire file — use 'patch' for targeted edits. Auto-runs syntax checks on .py/.json/.yaml/.toml and other linted languages; only NEW errors introduced by this write are surfaced (pre-existing errors are filtered out).",
"parameters": {
"type": "object",
"properties": {
"path": {
"type": "string",
"description": "Path to the file to write (will be created if it doesn't exist, overwritten if it does)"
},
"content": {
"type": "string",
"description": "Complete content to write to the file"
}
},
"required": [
"path",
"content"
]
}
}
},
{
"type": "function",
"function": {
"name": "honcho_profile",
"description": "Retrieve or update a peer card from Honcho — a curated list of key facts about that peer (name, role, preferences, communication style, patterns). Pass `card` to update; omit `card` to read. If the card is empty, the result includes a `hint` field explaining why (observation disabled, fresh peer, dialectic layer still warming up, etc.) — this is NOT an error. Peer cards accumulate over time from observed conversation.",
"parameters": {
"type": "object",
"properties": {
"peer": {
"type": "string",
"description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace."
},
"card": {
"type": "array",
"items": {
"type": "string"
},
"description": "New peer card as a list of fact strings. Omit to read the current card."
}
},
"required": []
}
}
},
{
"type": "function",
"function": {
"name": "honcho_search",
"description": "Semantic search over Honcho's stored context about a peer. Returns raw excerpts ranked by relevance — no LLM synthesis. Cheaper and faster than honcho_reasoning. Good when you want to find specific past facts and reason over them yourself.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "What to search for in Honcho's memory."
},
"max_tokens": {
"type": "integer",
"description": "Token budget for returned context (default 800, max 2000)."
},
"peer": {
"type": "string",
"description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace."
}
},
"required": [
"query"
]
}
}
},
{
"type": "function",
"function": {
"name": "honcho_reasoning",
"description": "Ask Honcho a natural language question and get a synthesized answer. Uses Honcho's LLM (dialectic reasoning) — higher cost than honcho_profile or honcho_search. Can query about any peer via alias or explicit peer ID. Pass reasoning_level to control depth: minimal (fast/cheap), low (default), medium, high, max (deep/expensive). Omit for configured default.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "A natural language question."
},
"reasoning_level": {
"type": "string",
"description": "Override the default reasoning depth. Omit to use the configured default (typically low). Guide:\n- minimal: quick factual lookups (name, role, simple preference)\n- low: straightforward questions with clear answers\n- medium: multi-aspect questions requiring synthesis across observations\n- high: complex behavioral patterns, contradictions, deep analysis\n- max: thorough audit-level analysis, leave no stone unturned",
"enum": [
"minimal",
"low",
"medium",
"high",
"max"
]
},
"peer": {
"type": "string",
"description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace."
}
},
"required": [
"query"
]
}
}
},
{
"type": "function",
"function": {
"name": "honcho_context",
"description": "Retrieve full session context from Honcho — summary, peer representation, peer card, and recent messages. No LLM synthesis. Cheaper than honcho_reasoning. Use this to see what Honcho knows about the current conversation and the specified peer.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Optional focus query to filter context. Omit for full session context snapshot."
},
"peer": {
"type": "string",
"description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace."
}
},
"required": []
}
}
},
{
"type": "function",
"function": {
"name": "honcho_conclude",
"description": "Write or delete a conclusion about a peer in Honcho's memory. Conclusions are persistent facts that build a peer's profile. You MUST pass exactly one of: `conclusion` (to create) or `delete_id` (to delete). Passing neither is an error. Deletion is only for PII removal — Honcho self-heals incorrect conclusions over time.",
"parameters": {
"type": "object",
"properties": {
"conclusion": {
"type": "string",
"description": "A factual statement to persist. Provide this when creating a conclusion. Do not send it together with delete_id."
},
"delete_id": {
"type": "string",
"description": "Conclusion ID to delete for PII removal. Provide this when deleting a conclusion. Do not send it together with conclusion."
},
"peer": {
"type": "string",
"description": "Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace."
}
},
"required": []
}
}
}
],
"message_count": 7,
"messages": [
{
"role": "user",
"content": "[Note: model was just switched from deepseek-v4-pro to gpt-5.5 via OpenAI Codex. Adjust your self-identification accordingly.]\n\n[nachlakes] CARGÁ ESTO PRIMERO:\n- /skill hevy\n- Leé /home/ubuntu/.hermes/references/minmax-training-plan.md\n\nCONTEXTO:\nSoy Ignacio (Chicho), 36, Buenos Aires, entreno en Open Park Club Rosedal con Andrés.\nSigo Jeff Nippard Min-Max 4-day program. Hoy es jueves 15/05/2026.\n\nESTADO:\n- Hevy routines actualizadas en folder 2826578, orden Jeff, pesos W2.\n- Schedule fijo: Lun Full Body, Mar Hatha 15:00, Mié Upper, Jue Lower, Vie Arms, Sáb yoga opcional, Dom rest.\n- DeepSeek V4 Pro configurado para delegation.\n- Esposa embarazada, FPP 26/06.\n\nPRIMERA TAREA — DELEGACIÓN:\nUsá delegate_task con DeepSeek para investigar cómo conectar Hermes con estas apps de salud:\n\n1. MacroFactor (nutrición) — tiene API reverse-engineered vía Firestore, repo github.com/sjawhar/macrofactor\n2. MyFitnessPal (nutrición) — API OAuth2 en myfitnesspalapi.com\n3. Fitbit (actividad, sueño, frecuencia cardíaca) — Web API OAuth2 en dev.fitbit.com\n4. Google Health Connect (hub de datos Android) — on-device, sin API cloud directa\n5. Google Fit (actividad) — REST API, pero deprecándose, migra a Health Connect/Google Health API\n6. Cronometer (nutrición) — sin API pública oficial, hay MCP reverse-engineered\n7. Hevy — ya conectado\n\nPara cada app: API type, doc URL, datos accesibles, auth, código Python esqueleto, factibilidad (1-5), costo.\n\nObjetivo: que Pipo sea mi \"Very Personal Trainer\" — leyendo mi nutrición, peso, actividad y sueño, ajustando entrenamiento y porciones automáticamente."
},
{
"role": "assistant",
"content": "",
"reasoning": null,
"finish_reason": "tool_calls",
"codex_reasoning_items": [
{
"type": "reasoning",
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],
"tool_calls": [
{
"id": "call_Z7uf2UOwiQJWJF5cqaiG2N5Z",
"call_id": "call_Z7uf2UOwiQJWJF5cqaiG2N5Z",
"response_item_id": "fc_0d86c717505984bc016a06ff1c3dbc819b9c691188251563e7",
"type": "function",
"function": {
"name": "skill_view",
"arguments": "{\"name\":\"hevy\"}"
}
},
{
"id": "call_kakAOMMx52J2w4DhUI0IZAwV",
"call_id": "call_kakAOMMx52J2w4DhUI0IZAwV",
"response_item_id": "fc_0d86c717505984bc016a06ff1c3dcc819bb633aa92139fecb4",
"type": "function",
"function": {
"name": "read_file",
"arguments": "{\"path\":\"/home/ubuntu/.hermes/references/minmax-training-plan.md\",\"limit\":2000}"
}
}
]
},
{
"role": "tool",
"name": "skill_view",
"content": "{\"success\": true, \"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.\", \"tags\": [], \"related_skills\": [], \"content\": \"---\\nname: hevy\\ndescription: 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.\\nhomepage: https://hevy.com\\nmetadata:\\n clawdbot:\\n emoji: \\\"🏋️\\\"\\n requires:\\n bins: [\\\"hevy\\\"]\\n env: [\\\"HEVY_API_KEY\\\"]\\n---\\n\\n# Hevy CLI\\n\\nCLI for the Hevy workout tracking API. Query workouts, routines, exercises, and track progress.\\n\\n## Setup\\n\\nRequires Hevy Pro subscription for API access.\\n\\n1. Get API key from https://hevy.com/settings?developer\\n2. Set environment variable: `export HEVY_API_KEY=\\\"your-key\\\"`\\n\\n## Troubleshooting / Environment Checks\\n\\nUse this when the user asks whether Hevy is connected, whether the API key exists, or when `hevy status` fails.\\n\\n1. Check the CLI wrapper and direct skill CLI:\\n ```bash\\n command -v hevy\\n hevy status\\n node ~/.hermes/skills/openclaw-imports/hevy/dist/cli.js status\\n ```\\n2. If `hevy` prints `hevy CLI is not built yet: ~/.openclaw/workspace/skills/hevy/dist/cli.js`, the wrapper is stale from the old OpenClaw skill path. Update `~/.local/bin/hevy` so `SKILL_DIR=\\\"$HOME/.hermes/skills/openclaw-imports/hevy\\\"`.\\n3. Search likely config/env locations for the key before asking the user:\\n ```bash\\n grep -R \\\"HEVY_API_KEY\\\\|hevyapp\\\\|HEVY\\\" ~/.hermes ~/.openclaw ~/hermes-webui ~/hermes-workspace 2>/dev/null\\n ```\\n Redact any key values in user-facing output.\\n4. If the key is expected in Bitwarden, verify session state:\\n ```bash\\n source ~/.bash_aliases 2>/dev/null || true\\n bw-sync || true\\n bw status\\n ```\\n If Bitwarden is `locked` or the saved session expired, you cannot retrieve the key until the user unlocks it (`bw-unlock`) or provides the key securely.\\n5. Only after `HEVY_API_KEY` is present, verify connection with:\\n ```bash\\n hevy status\\n hevy workouts --limit 5 --kg\\n ```\\n\\n## Workout Program Planning & Load Calibration\\n\\nUse this skill not only for raw Hevy queries, but also when the user wants to restart training, adopt a published program/spreadsheet/PDF, choose starting loads, estimate rep maxes, or log/calibrate a new routine in Hevy.\\n\\nFor Ignacio's Jeff Nippard Min-Max setup, read `references/jeff-minmax-hevy.md` before changing routines or schedules. It captures the source-grounded workout order, RIR rules, Open Park substitutions, fixed schedule (Lun Full Body, Mar Hatha, Mié Upper, Jue Lower, Vie Arms, Sáb yoga opcional), transition weeks, therapy Tuesday logistics, and yoga class details.\\n\\nFor a full-session cold start after `/reset`, use `templates/kickstart-fitness-session.md` — copy-paste it into a new chat to load all fitness context immediately.\\n\\nThe complete training plan with all weights, reps, RIR, and exercise notes is at `~/.hermes/references/minmax-training-plan.md` — read it when rebuilding routines or verifying program integrity.\\n\\nWhen the user asks for an ongoing training schedule — especially if frustrated — answer with a concrete fixed calendar first: today/tomorrow/next few days, then the recurring weekly template, then only the minimal adjustment rules. Avoid long justification. Use the user's stated current date/time/timezone if provided; otherwise verify with `date` before assigning weekdays/dates.\\n\\nRecommended workflow:\\n\\n1. Retrieve the program source if provided (Drive folder, spreadsheet, PDF). For public Google Drive folders, `web_extract` can list filenames; if needed, parse the Drive page HTML for file IDs and download with `https://drive.google.com/uc?export=download&id=`.\\n2. Prefer the spreadsheet for exact programming tables. If Python lacks spreadsheet deps, install/use `openpyxl` and inspect sheets with coordinates so merged cells and headers are clear.\\n3. Use the PDF for explanatory rules: RIR definitions, warm-up protocol, progression rules, and safety caveats.\\n4. Query recent Hevy history (`hevy workouts --limit 10 --kg`, exercise history where useful) to distinguish a true beginner from a detrained returning lifter.\\n5. For returning lifters or beginners, do **not** recommend true 1RM testing by default. Estimate e1RM/training max from submaximal sets inside the program's target rep ranges using RIR:\\n ```text\\n possible_reps = completed_reps + estimated_RIR\\n e1RM ≈ weight × (1 + possible_reps / 30)\\n ```\\n Treat this as a rough guide; the actionable output is the next-session load for the target rep range and RIR.\\n6. For heavy compounds (squat variants, incline/bench press, RDL, leg press, hip thrust), keep first-week testing submaximal and avoid failure, especially after a long layoff. Use machines/Smith/hack/leg press substitutions when safer.\\n7. For isolation exercises, do not over-focus on 1RM; choose loads by target reps + RIR and log them.\\n8. Recommend logging calibration workouts as normal Hevy workouts with explicit notes like `Program W1D1 — Calibration`, plus per-exercise notes for target reps/RIR, actual RIR, pain, technique, and chosen substitution.\\n9. After the workout, read the Hevy log and compute next-session recommendations: repeat, raise, or lower load based on whether reps and RIR matched the prescription.\\n10. When the user adapts a program to a real gym, update the Hevy routine templates to match actual substitutions instead of repeatedly fighting unavailable equipment. Read the logged workout, identify substitutions (e.g. machine missing → dumbbell/cable variant), then update the remaining routines with consistent available variants and clear notes.\\n11. If the user consistently wants cardio/abs around sessions, encode them in routines as explicit exercises where appropriate (e.g. 10 min elliptical warm-up; knee raise/crunch as an abs slot), but keep the base program intact and avoid adding fatigue that interferes with heavy lower-body work.\\n12. For hybrid lifting + yoga/stretching plans, make lifting progression the anchor and treat classes as recovery unless the user explicitly wants more conditioning. Put lower-fatigue options (Hatha, stretching, meditation/restorative yoga, easy Pilates) between or after lifting days; avoid recommending dynamic/vinyasa/flow classes early in a strength block if they may interfere with recovery.\\n13. When parsing gym class PDFs or grid schedules, do not trust plain text order if columns are ambiguous. Extract word coordinates (e.g. PyMuPDF `get_text('words')`), group by y-coordinate, and map words into known day/time columns before making calendar recommendations. Verify suspicious classes against column positions before answering.\\n\\n### Schedule Output Shape\\n\\nFor ongoing plans, prefer this shape:\\n\\n```text\\nHoy — — \\nMañana — — \\nPasado — — \\nSábado — — \\nDomingo — — \\n\\nDesde el lunes / Semana N:\\nLun — D1 ...\\nMar — recovery class ...\\nMié — D2 ...\\nJue — D3 ...\\nVie — D4 ...\\nSáb — catch-up or optional recovery class\\nDom — rest\\n```\\n\\nKeep it direct and operational; no motivational filler.\\n\\n## Commands\\n\\n### Status\\n\\n```bash\\n# Check configuration and connection\\nhevy status\\n```\\n\\n### Workouts\\n\\n```bash\\n# List recent workouts (default 5)\\nhevy workouts\\nhevy workouts --limit 10\\n\\n# Fetch all workouts\\nhevy workouts --all\\n\\n# Show detailed workout\\nhevy workout \\n\\n# JSON output\\nhevy workouts --json\\nhevy workout --json\\n\\n# Show weights in kg (default is lbs)\\nhevy workouts --kg\\n```\\n\\n### Routines\\n\\n```bash\\n# List all routines\\nhevy routines\\n\\n# Show detailed routine\\nhevy routine \\n\\n# JSON output\\nhevy routines --json\\n```\\n\\n### Exercises\\n\\n```bash\\n# List all exercise templates\\nhevy exercises\\n\\n# Search by name\\nhevy exercises --search \\\"bench press\\\"\\n\\n# Filter by muscle group\\nhevy exercises --muscle chest\\n\\n# Show only custom exercises\\nhevy exercises --custom\\n\\n# JSON output\\nhevy exercises --json\\n```\\n\\n### Exercise History\\n\\n```bash\\n# Show history for specific exercise\\nhevy history \\nhevy history --limit 50\\n\\n# JSON output\\nhevy history --json\\n```\\n\\n### Creating Routines\\n\\n```bash\\n# Create routine from JSON (stdin)\\necho '{\\\"routine\\\": {...}}' | hevy create-routine\\n\\n# Create routine from file\\nhevy create-routine --file routine.json\\n\\n# Create a routine folder\\nhevy create-folder \\\"Push Pull Legs\\\"\\n\\n# Update existing routine\\necho '{\\\"routine\\\": {...}}' | hevy update-routine \\n\\n# Create custom exercise (checks for duplicates first!)\\nhevy create-exercise --title \\\"My Exercise\\\" --muscle chest --type weight_reps\\n\\n# Force create even if duplicate exists\\nhevy create-exercise --title \\\"My Exercise\\\" --muscle chest --force\\n```\\n\\n**⚠️ Duplicate Prevention:** `create-exercise` checks if an exercise with the same name already exists and will error if found. Use `--force` to create anyway (not recommended).\\n\\n**Routine JSON format:**\\n```json\\n{\\n \\\"routine\\\": {\\n \\\"title\\\": \\\"Push Day 💪\\\",\\n \\\"folder_id\\\": null,\\n \\\"notes\\\": \\\"Chest, shoulders, triceps\\\",\\n \\\"exercises\\\": [\\n {\\n \\\"exercise_template_id\\\": \\\"79D0BB3A\\\",\\n \\\"notes\\\": \\\"Focus on form\\\",\\n \\\"rest_seconds\\\": 90,\\n \\\"sets\\\": [\\n { \\\"type\\\": \\\"warmup\\\", \\\"weight_kg\\\": 20, \\\"reps\\\": 15 },\\n { \\\"type\\\": \\\"normal\\\", \\\"weight_kg\\\": 60, \\\"reps\\\": 8 }\\n ]\\n }\\n ]\\n }\\n}\\n```\\n\\n**Routine creation API pitfalls learned in practice:**\\n\\n- Consult/ground against https://api.hevyapp.com/docs/ before write operations; the API is young and stricter than some local TypeScript types.\\n- `POST /v1/routine_folders` body is exactly:\\n ```json\\n { \\\"routine_folder\\\": { \\\"title\\\": \\\"Folder Name\\\" } }\\n ```\\n- `POST /v1/routines` accepts `folder_id` on create, but `PUT /v1/routines/{id}` does **not** accept `routine.folder_id`; you cannot move a routine between folders via PUT.\\n- `DELETE /v1/routines/{id}` is not supported. If a duplicate is created, the API cannot delete it; at best rename it via PUT (for example `ZZ IGNORE — duplicate ...`) and tell the user to delete manually in the app.\\n- `routine.exercises[].sets[].rpe` is rejected on routine creation (`\\\"rpe\\\" is not allowed`) even though workout/history types may include RPE. Omit `rpe` from routine template sets.\\n- `rep_range` on routine sets is accepted and useful for program templates:\\n ```json\\n { \\\"type\\\": \\\"normal\\\", \\\"weight_kg\\\": null, \\\"reps\\\": null, \\\"rep_range\\\": { \\\"start\\\": 6, \\\"end\\\": 8 } }\\n ```\\n- `POST /v1/routines` may return `{ \\\"routine\\\": [ ... ] }` rather than a bare object; unwrap arrays carefully and verify by listing/getting routines afterward.\\n- Some `hevy ... --json` CLI commands print status text before the JSON payload (for example `Fetching exercise templates...`). When scripting, strip everything before the first `[` or `{` before `json.loads`, or call the REST API directly.\\n- Avoid blind retry after a 400/partial failure: first list routines/folders to see what was already created. Folder creation can succeed even when subsequent routine creation fails, and retrying without idempotency creates clutter.\\n- Before creating program routines, fetch all exercise templates and verify every `exercise_template_id` with `GET /v1/exercise_templates/{id}`; invalid IDs cause the whole routine create to fail.\\n- For published programs, put RIR/progression cues in exercise `notes`; Hevy routine templates do not have a first-class RIR field.\\n\\n### Other\\n\\n```bash\\n# Total workout count\\nhevy count\\n\\n# List routine folders\\nhevy folders\\n```\\n\\n## Usage Examples\\n\\n**User asks \\\"What did I do at the gym?\\\"**\\n```bash\\nhevy workouts\\n```\\n\\n**User asks \\\"Show me my last chest workout\\\"**\\n```bash\\nhevy workouts --limit 10 # Find relevant workout ID\\nhevy workout # Get details\\n```\\n\\n**User asks \\\"How am I progressing on bench press?\\\"**\\n```bash\\nhevy exercises --search \\\"bench press\\\" # Get exercise template ID\\nhevy history # View progression\\n```\\n\\n**User asks \\\"What routines do I have?\\\"**\\n```bash\\nhevy routines\\nhevy routine # For details\\n```\\n\\n**User asks \\\"Find leg exercises\\\"**\\n```bash\\nhevy exercises --muscle quadriceps\\nhevy exercises --muscle hamstrings\\nhevy exercises --muscle glutes\\n```\\n\\n**User asks \\\"Create a push day routine\\\"**\\n```bash\\n# 1. Find exercise IDs\\nhevy exercises --search \\\"bench press\\\"\\nhevy exercises --search \\\"shoulder press\\\"\\n# 2. Create routine JSON with those IDs and pipe to create-routine\\n```\\n\\n## Notes\\n\\n- **Duplicate Prevention:** `create-exercise` checks for existing exercises with the same name before creating. Use `--force` to override (not recommended).\\n- **API Limitations:** Hevy API does NOT support deleting or editing exercise templates - only creating. Delete exercises manually in the app.\\n- **API Rate Limits:** Be mindful when fetching all data (--all flag)\\n- **Weights:** Defaults to lbs, use --kg for kilograms\\n- **Pagination:** Most commands auto-paginate, but limit flags help reduce API calls\\n- **IDs:** Workout/routine/exercise IDs are UUIDs, shown in detailed views\\n\\n## API Reference\\n\\nFull API docs: https://api.hevyapp.com/docs/\\n\\n### Available Endpoints\\n- `GET /v1/workouts` - List workouts (paginated)\\n- `GET /v1/workouts/{id}` - Get single workout\\n- `GET /v1/workouts/count` - Total workout count\\n- `GET /v1/routines` - List routines\\n- `GET /v1/routines/{id}` - Get single routine\\n- `GET /v1/exercise_templates` - List exercises\\n- `GET /v1/exercise_templates/{id}` - Get single exercise\\n- `GET /v1/exercise_history/{id}` - Exercise history\\n- `GET /v1/routine_folders` - List folders\\n\\n### Write Operations (supported but use carefully)\\n- `POST /v1/workouts` - Create workout\\n- `PUT /v1/workouts/{id}` - Update workout\\n- `POST /v1/routines` - Create routine\\n- `PUT /v1/routines/{id}` - Update routine\\n- `POST /v1/exercise_templates` - Create custom exercise\\n- `POST /v1/routine_folders` - Create folder\\n\\nThe CLI focuses on read operations. Write operations are available via the API client for programmatic use.\\n\", \"path\": \"openclaw-imports/hevy/SKILL.md\", \"skill_dir\": \"/home/ubuntu/.hermes/skills/openclaw-imports/hevy\", \"linked_files\": {\"references\": [\"references/jeff-minmax-hevy.md\"], \"templates\": [\"templates/kickstart-fitness-session.md\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\", \"metadata\": {\"clawdbot\": {\"emoji\": \"🏋️\", \"requires\": {\"bins\": [\"hevy\"], \"env\": [\"HEVY_API_KEY\"]}}}}",
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"content": "{\"content\": \" 1|# Ignacio — Min-Max Training Plan (Full Context)\\n 2|# Generated 2026-05-14 after extensive multi-session planning\\n 3|# This file captures everything discussed so the next session starts clean.\\n 4|\\n 5|## Program Source\\n 6|- **Program:** Jeff Nippard's Min-Max Program (12 weeks, 2 blocks of 6 weeks)\\n 7|- **PDF:** Downloaded from Google Drive, verified page by page (78 pages)\\n 8|- **Key rules from Jeff:**\\n 9| - 4 workouts/week: Full Body → Upper → Lower → Arms/Delts\\n 10| - Week 1 = intro/lighter (RIR 1-2), Week 2+ = intensity (RIR 0-1), Week 7 = deload\\n 11| - 5-10 min light cardio warmup before each session\\n 12| - For squat, barbell incline, leg press, Smith lunge: RIR 0 = clean rep limit, no failed rep\\n 13| - For other exercises: RIR 0 = true failure, attempt the rep\\n 14| - Substitutions allowed: same muscle + same movement pattern\\n 15| - Keep exercises constant for technique mastery and progression\\n 16| - 1-2 rest days after Full Body and after Arms/Delts\\n 17| - Yoga/extra = low intensity only to protect recovery\\n 18|\\n 19|## Gym\\n 20|- **Open Park Club Rosedal** (Palermo, Buenos Aires)\\n 21|- **Hours:** Mon-Sat (opens ~7am, classes run into evening), Sun closed\\n 22|- **Equipment limitations:** No lying leg curl, no T-bar row, no machine shrug, no standing calf raise, \\n 23| no machine hip thrust, no machine lateral raise\\n 24|- **Class grid extracted** from schedule PDF using word-coordinate parsing (PyMuPDF)\\n 25|\\n 26|## Available Yoga/Stretching Classes (relevant)\\n 27|### Fixed in schedule\\n 28|- **Martes 15:00** — Yoga Hatha — Cintia Cavalero\\n 29|- **Jueves 15:00** — Yoga Hatha — Cintia Cavalero\\n 30|- **Sábado 16:00** — Yoga y Meditación — Cintia Cavalero (optional)\\n 31|\\n 32|### Avoid (interfere with strength recovery)\\n 33|- Yoga Dinámico (Tue/Thu 18:00)\\n 34|- Yoga Vinyasa / Vinyasa Flow (various)\\n 35|- Yoga Flow when legs/back loaded\\n 36|\\n 37|## Hevy Setup\\n 38|- **Folder:** \\\"Jeff Nippard Min-Max 4x — Start 2026-05\\\" (ID: 2826578)\\n 39|- **4 routines in folder,** updated to Block 1 with W2 weights, Jeff order, substitutions:\\n 40| - `Min-Max 4x D1 — Full Body (Block 1)` (ID: 78e21872-...)\\n 41| - `Min-Max 4x D2 — Upper (Block 1)` (ID: 2164feea-...)\\n 42| - `Min-Max 4x D3 — Lower (Block 1)` (ID: d7b6da14-...)\\n 43| - `Min-Max 4x D4 — Arms/Delts (Block 1)` (ID: f3051fb9-...)\\n 44|- **API key:** In Bitwarden, cached at `/tmp/hevy_key_runtime` during sessions\\n 45|- **CLI:** `~/.local/bin/hevy` (wraps `~/.hermes/skills/openclaw-imports/hevy/dist/cli.js`)\\n 46|- **Backup:** `/tmp/hevy_minmax_backup_before_block1_update.json`\\n 47|\\n 48|## Substitutions (all Jeff-approved: same muscle, same pattern)\\n 49|```\\n 50|Lying Leg Curl → Seated Leg Curl (Machine)\\n 51|Pull-Up Wide Grip → Lat Pulldown (Cable) wide grip\\n 52|Chest-Supported T-Bar → Seated Row (Machine)\\n 53|Machine Shrug → DB Shrug\\n 54|Cable Crunch → Machine Crunch\\n 55|Reverse Pec Deck → Face Pull (Cable)\\n 56|Machine Hip Thrust → Barbell Hip Thrust\\n 57|Machine Lateral Raise → DB Lateral Raise\\n 58|Standing Calf Raise → Calf Press (Machine)\\n 59|```\\n 60|\\n 61|## Fixed Schedule (from 2026-05-25 onward)\\n 62|```\\n 63|Lunes — D1 Full Body\\n 64|Martes — Yoga Hatha 15:00 (fijo)\\n 65|Miércoles — D2 Upper\\n 66|Jueves — D3 Lower\\n 67|Viernes — D4 Arms/Delts\\n 68|Sábado — Yoga y Meditación 16:00 (opcional / buffer de pesas)\\n 69|Domingo — Rest total\\n 70|```\\n 71|\\n 72|## Rules\\n 73|1. **Min-Max > Yoga.** If conflict, cancel yoga, keep pesas.\\n 74|2. **Saturday = buffer.** If all 4 pesas done → yoga. If missed one → recover pesas Saturday.\\n 75|3. **Tuesday Hatha = fixed recovery.** Therapy Tuesdays: go straight from therapy to gym. Arrive ~14:20-14:30, Hatha 15:00.\\n 76|4. **Thursday Hatha = backup only.** Not fixed because Thursday = Lower day.\\n 77|5. **Yoga frequency:** 1× per week minimum (Martes Hatha). Sábado optional.\\n 78|6. **If chaotic weeks:** Do workouts in order (FB → Upper → Lower → Arms), don't skip any, carry overflow to next week.\\n 79|\\n 80|## Transition Weeks (May 2026)\\n 81|```\\n 82|Jue 14/05 — Hatha Yoga 15:00\\n 83|Vie 15/05 — W2D1 Full Body\\n 84|Sáb 16/05 — Yoga y Meditación opcional\\n 85|Dom 17/05 — Rest\\n 86|\\n 87|Lun 18/05 — W2D2 Upper\\n 88|Mar 19/05 — Hatha Yoga (terapia 12:30-13:45, directo al gym)\\n 89|Mié 20/05 — W2D3 Lower\\n 90|Jue 21/05 — W2D4 Arms/Delts\\n 91|Vie 22/05 — Rest / caminata\\n 92|Sáb 23/05 — Yoga opcional\\n 93|Dom 24/05 — Rest\\n 94|\\n 95|→ FIXED SCHEDULE STARTS LUN 25/05 ←\\n 96|```\\n 97|\\n 98|## Block 1 Schedule through due date\\n 99|```\\n 100|W3: 25/05 FB → 26/05 Hatha → 27/05 Upper → 28/05 Lower → 29/05 Arms → ...\\n 101|W4: 01/06 FB → ...\\n 102|W5: 08/06 FB → ...\\n 103|W6: 15/06 FB → ...\\n 104|W7: 22/06 FB → ... (deload, lighter week — PERFECT, due date is Fri 26/06)\\n 105|```\\n 106|\\n 107|## Training Partners\\n 108|- **Andrés:** Gym partner, trains together at Open Park\\n 109|- **Christina (Tina):** Wife, pregnant, due ~26/06/2026\\n 110|- **Chicho expects to be a father.** From last 2 weeks pre-due date: flexible schedule, just do next workout in order.\\n 111|\\n 112|## Key Dates\\n 113|- **2026-05-13:** W1D4 completed (Arms/Delts calibration)\\n 114|- **2026-05-14 (today):** Hatha Yoga 15:00\\n 115|- **2026-05-15:** W2D1 Full Body\\n 116|- **2026-05-19:** Therapy 12:30-13:45, then Hatha 15:00\\n 117|- **2026-05-25:** Fixed schedule starts (W3D1 Full Body)\\n 118|- **2026-06-26:** Probable due date (falls on W7 deload week Friday — ideal)\\n 119|\\n 120|## Hevy Routine D1 — Full Body weights (W2)\\n 121|```\\n 122|Warm Up — 10 min cardio liviano\\n 123|Seated Leg Curl — W: 35×10, N: 55×6-8, N: 55×6-8 (RIR 0/0)\\n 124|Smith Squat — W: 20×8 / 35×5, N: 45×6-8, 47.5×6-8 (RIR 1/0)\\n 125|Barbell Incline — W: 20×8 / 22.5×4, N: 22.5×6-8, 25×6-8 (RIR 1/0)\\n 126|Incline DB Y-Raise — W: 2×10, N: 3×8-10 (RIR 0)\\n 127|Lat Pulldown Wide — W: 25×8, N: 40×6-8, 40×6-8 (RIR 1/0)\\n 128|Calf Press — W: 50×10, N: 80×6-8 (RIR 0)\\n 129|Knee Raise — W: 10, N: 8-12, 8-12 (extra, not Jeff)\\n 130|```\\n 131|\\n 132|## Hevy Routine D2 — Upper weights (W2)\\n 133|```\\n 134|Close-Grip Pulldown — W: 25×8 / 35×5, N: 40×8-10, 42.5×8-10 (RIR 1/0)\\n 135|Seated Row Machine — W: 35×8 / 40×5, N: 50×8-10, 50×8-10 (RIR 1/0)\\n 136|DB Shrug — W: 10×10, N: 16×6-8 (RIR 0)\\n 137|Machine Chest Press — W: 25×10 / 30×5, N: 30×8-10, 32.5×8-10 (RIR 1/0)\\n 138|Cable Lateral Raise — W: 2.5×8, N: 2.5×8-10, 2.5×8-10 (RIR 0/0)\\n 139|Machine Crunch — W: 15×10, N: 25×6-8, 30×6-8 (RIR 0/0)\\n 140|Face Pull — W: 10×10, N: 20×8-10 (RIR 0)\\n 141|Knee Raise — extra\\n 142|```\\n 143|\\n 144|## Hevy Routine D3 — Lower weights (W2)\\n 145|```\\n 146|Leg Extension — W: 40×10, N: 60×8-10, 65×8-10 (RIR 0/0)\\n 147|Barbell RDL — W: 30×8 / 40×5, N: 50×6-8, 55×6-8 (RIR 2/1)\\n 148|Barbell Hip Thrust — W: 50×10 / 60×5, N: 70×6-8, 70×6-8 (RIR 1/0)\\n 149|Leg Press — W: 40×10 / 60×6, N: 80×6-8 (RIR 0)\\n 150|Calf Press — W: 50×10, N: 80×8-10, 80×8-10 (RIR 0/0)\\n 151|Knee Raise — extra\\n 152|```\\n 153|\\n 154|## Hevy Routine D4 — Arms/Delts weights (W2)\\n 155|```\\n 156|Bayesian Cable Curl — W: 2.5×10, N: 5×6-8, 5×6-8 (RIR 0/0)\\n 157|Overhead Triceps Ext — W: 5×10, N: 7.5×8-10, 10×8-10 (RIR 0/0)\\n 158|Zottman Curl — W: 4×10, N: 6×8-10 (RIR 0)\\n 159|Cable Kickback — W: 2.5×10, N: 3.75×8-10, 3.75×8-10 (RIR 0/0)\\n 160|DB Wrist Curl — W: 4×10, N: 8×8-10, 8×8-10 (RIR 0/0)\\n 161|Alternating DB Curl — W: 4×10, N: 6×6-8 (RIR 0)\\n 162|Dead Hang — 30s + 30s\\n 163|Barbell Wrist Ext — W: 10×10, N: 15×8-10, 15×8-10 (RIR 0/0)\\n 164|DB Lateral Raise — W: 4×10, N: 6×8-10, 6×8-10 (RIR 0/0)\\n 165|Knee Raise — extra\\n 166|```\\n 167|\\n 168|## Progression Rules\\n 169|- Hit top of rep range on all working sets → increase load next session\\n 170|- Adding weight drops you below range → keep weight, extend rep range slightly\\n 171|- RIR target wins over exact load\\n 172|- Log weights + reps + actual RIR in Hevy notes\\n 173|- After each W1D1/D2/D3/D4: read logs, compute next session recommendations\\n 174|\\n 175|## Important Notes for Next Session Agent\\n 176|- User prefers DIRECT, CONCISE responses\\n 177|- Hevy skill at: `openclaw-imports/hevy`\\n 178|- Reference file: `openclaw-imports/hevy/references/jeff-minmax-hevy.md`\\n 179|- Reminder: \\\"Pesos sugeridos desde W2 según W1. Ajustar en el momento para cumplir RIR: si quedás fuera del rango, corregí carga.\\\"\\n 180|- DeepSeek V4 Pro configured as delegation model for subagents\\n 181|- Session search available for past context\\n 182|\", \"total_lines\": 181, \"file_size\": 7973, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
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"arguments": "{\"goal\":\"Investigar cómo conectar Hermes Agent con apps de salud/nutrición/actividad para convertir a Pipo en un 'Very Personal Trainer'. Entregar un informe técnico por app: MacroFactor, MyFitnessPal, Fitbit, Google Health Connect, Google Fit, Cronometer, Hevy.\",\"context\":\"Usuario: Ignacio/Chicho, 36, Buenos Aires, Android/Pixel, no Apple, usa Hevy ya conectado, sigue Jeff Nippard Min-Max 4-day program en Open Park Club Rosedal. Objetivo: Hermes/Pipo lea nutrición, peso, actividad y sueño, y ajuste entrenamiento/porciones automáticamente. Debés investigar con web. Para cada app incluir: API type, doc URL/repo URL, datos accesibles, auth, código Python esqueleto, factibilidad 1-5, costo. Apps a cubrir: 1) MacroFactor — API reverse-engineered vía Firestore, repo github.com/sjawhar/macrofactor. 2) MyFitnessPal — API OAuth2 en myfitnesspalapi.com. 3) Fitbit — Web API OAuth2 dev.fitbit.com. 4) Google Health Connect — on-device Android, sin API cloud directa. 5) Google Fit — REST API deprecándose, migración a Health Connect/Google Health API. 6) Cronometer — sin API pública oficial, hay MCP reverse-engineered. 7) Hevy — ya conectado. Sé concreto, técnico, directo, en español. No inventes: si algo es incierto, marcá 'requiere validación'. Incluí skeleton Python usable con placeholders, preferentemente requests/httpx/authlib/firebase-admin cuando corresponda. También recomendá arquitectura de integración para Hermes (cron jobs, token storage, local Android bridge si hace falta, schema de datos).\",\"toolsets\":[\"web\",\"terminal\"]}"
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"role": "tool",
"name": "delegate_task",
"content": "{\"results\": [{\"task_index\": 0, \"status\": \"completed\", \"summary\": \"## Informe técnico: conectar Hermes Agent/Pipo con apps salud/nutrición/actividad\\n\\nObjetivo: que Pipo lea nutrición, peso, actividad, sueño y entrenamiento de Ignacio/Chicho — Android/Pixel, Buenos Aires, Hevy ya conectado, programa Jeff Nippard Min-Max 4-day — para ajustar entrenamiento y porciones automáticamente.\\n\\n---\\n\\n# Recomendación ejecutiva\\n\\n## Mejor stack para Pipo\\n\\n1. **Hevy** como fuente principal de entrenamiento.\\n - Ya conectado.\\n - API pública, estable aunque joven.\\n - Permite leer workouts/routines/exercise history y escribir/actualizar workouts/routines.\\n\\n2. **Fitbit Web API** como fuente cloud principal de:\\n - sueño,\\n - pasos,\\n - actividad,\\n - frecuencia cardíaca,\\n - peso,\\n - nutrición si se usa Fitbit food logging.\\n - Es la opción más limpia si Ignacio usa dispositivo Fitbit/Pixel Watch con Fitbit.\\n\\n3. **Health Connect** como hub local Android.\\n - Ideal para Android/Pixel.\\n - Pero necesita **Android bridge/app local**, porque no hay API cloud directa.\\n - Útil para leer datos agregados de Google Fit, Fitbit, báscula, sueño, etc. desde el teléfono.\\n\\n4. **MacroFactor** como fuente nutricional premium si Ignacio lo usa o quiere usar.\\n - No tiene API oficial pública.\\n - Hay repo reverse-engineered vía Firebase/Firestore: `github.com/sjawhar/macrofactor`.\\n - Muy útil para gasto energético dinámico, peso y logging nutricional, pero requiere validación y cuidado.\\n\\n5. **MyFitnessPal** si se consigue acceso partner.\\n - Tiene API OAuth2 oficial en `myfitnesspalapi.com`.\\n - Pero el acceso parece orientado a partners; requiere validar alta de app/API.\\n\\n6. **Cronometer** si se priorizan micronutrientes.\\n - Sin API pública individual oficial.\\n - Hay MCP/reverse-engineered.\\n - Factible para uso personal, menos recomendable como integración robusta.\\n\\n7. **Google Fit**\\n - No conviene iniciar integración nueva.\\n - REST API deprecándose / end-of-service late 2026.\\n - Migrar a Health Connect o Google Health API.\\n\\n---\\n\\n# Arquitectura propuesta para Hermes/Pipo\\n\\n## Componentes\\n\\n```text\\nHermes Agent / Pipo\\n |\\n v\\nIntegration Service Python\\n |\\n +-- hevy_connector.py\\n +-- fitbit_connector.py\\n +-- macrofactor_connector.py\\n +-- mfp_connector.py\\n +-- cronometer_connector.py\\n +-- healthconnect_android_bridge.py\\n |\\n v\\nNormalized Health DB\\nPostgres/SQLite\\n |\\n +-- nutrition_daily\\n +-- body_weight\\n +-- activity_daily\\n +-- sleep_daily\\n +-- workouts\\n +-- workout_sets\\n +-- readiness_daily\\n +-- recommendations\\n```\\n\\n## Jobs recomendados\\n\\n```text\\nCada 15-30 min:\\n- sync Hevy workout events\\n- sync Fitbit activity/sleep/weight\\n- sync Health Connect bridge if available\\n\\nCada noche:\\n- recomputar readiness\\n- revisar sueño, pasos, HR/resting HR si está disponible\\n- ajustar intensidad sugerida del próximo entrenamiento\\n\\nCada mañana:\\n- generar check-in: peso, sueño, fatiga, entrenamiento próximo\\n\\nCada semana:\\n- evaluar tendencia de peso 7/14 días\\n- ajustar porciones/macros\\n- detectar estancamiento de cargas en Hevy\\n```\\n\\n## Token storage\\n\\nUsar almacenamiento cifrado:\\n\\n```text\\n~/.hermes/secrets/\\n fitbit_token.json.enc\\n hevy_api_key.enc\\n macrofactor_refresh_token.enc\\n mfp_token.json.enc\\n```\\n\\nIdeal:\\n- `keyring` en local.\\n- O `age`/`sops`.\\n- Nunca guardar passwords planos.\\n- Preferir refresh tokens cuando existan.\\n- Para reverse-engineered APIs, guardar cookies/tokens y documentar riesgo.\\n\\n## Schema mínimo normalizado\\n\\n```sql\\nCREATE TABLE nutrition_daily (\\n source TEXT,\\n date DATE,\\n calories REAL,\\n protein_g REAL,\\n carbs_g REAL,\\n fat_g REAL,\\n fiber_g REAL,\\n sodium_mg REAL,\\n raw_json JSON,\\n PRIMARY KEY (source, date)\\n);\\n\\nCREATE TABLE body_weight (\\n source TEXT,\\n timestamp TIMESTAMP,\\n weight_kg REAL,\\n body_fat_pct REAL,\\n raw_json JSON,\\n PRIMARY KEY (source, timestamp)\\n);\\n\\nCREATE TABLE activity_daily (\\n source TEXT,\\n date DATE,\\n steps INTEGER,\\n active_minutes INTEGER,\\n calories_out REAL,\\n distance_km REAL,\\n raw_json JSON,\\n PRIMARY KEY (source, date)\\n);\\n\\nCREATE TABLE sleep_daily (\\n source TEXT,\\n date DATE,\\n duration_min INTEGER,\\n efficiency REAL,\\n deep_min INTEGER,\\n rem_min INTEGER,\\n light_min INTEGER,\\n awake_min INTEGER,\\n raw_json JSON,\\n PRIMARY KEY (source, date)\\n);\\n\\nCREATE TABLE workouts (\\n source TEXT,\\n workout_id TEXT,\\n started_at TIMESTAMP,\\n ended_at TIMESTAMP,\\n title TEXT,\\n raw_json JSON,\\n PRIMARY KEY (source, workout_id)\\n);\\n\\nCREATE TABLE workout_sets (\\n source TEXT,\\n workout_id TEXT,\\n exercise_id TEXT,\\n exercise_name TEXT,\\n set_index INTEGER,\\n reps REAL,\\n weight_kg REAL,\\n rpe REAL,\\n rir REAL,\\n raw_json JSON\\n);\\n```\\n\\n---\\n\\n# 1. MacroFactor\\n\\n## Estado\\n\\n- **Tipo de API:** no oficial, reverse-engineered.\\n- **Backend:** Firebase/Firestore.\\n- **Repo:** https://github.com/sjawhar/macrofactor\\n- **Docs API:** https://github.com/sjawhar/macrofactor/blob/main/docs/api-reference.md\\n- **Base Firestore:** \\n `https://firestore.googleapis.com/v1/projects/sbs-diet-app/databases/(default)/documents`\\n- **Auth:** Firebase Identity Toolkit.\\n- **Factibilidad:** **3.5/5**\\n- **Costo:** requiere suscripción activa de MacroFactor. Integración en sí sin costo, pero no oficial.\\n\\n## Datos accesibles según repo\\n\\nEl repo declara lectura/escritura de:\\n\\n- food logs,\\n- weight entries,\\n- nutrition summaries,\\n- workouts,\\n- custom exercises,\\n- gym profiles,\\n- food search vía Typesense,\\n- creación/actualización de food log entries,\\n- creación/actualización de workouts/sets,\\n- logging de peso.\\n\\n## Auth\\n\\nFlujo documentado por el repo:\\n\\n```text\\nPOST https://identitytoolkit.googleapis.com/v1/accounts:signInWithPassword?key={API_KEY}\\n\\nDevuelve:\\n- idToken\\n- refreshToken\\n\\nUsar:\\nAuthorization: Bearer \\ncontra Firestore REST.\\n```\\n\\nToken refresh:\\n\\n```text\\nPOST https://securetoken.googleapis.com/v1/token?key={API_KEY}\\n```\\n\\n## Riesgos / validaciones\\n\\n- No es API oficial.\\n- Requiere extraer/usar API key Firebase del cliente; requiere validación legal/ToS.\\n- App Check bloquea algunas colecciones de referencia.\\n- El repo resuelve referencia local usando JSON extraído del APK.\\n- Requiere validación con una cuenta real.\\n- No guardar password plano: preferir refresh token.\\n\\n## Python skeleton\\n\\n```python\\nimport os\\nimport httpx\\nfrom datetime import date\\n\\nFIREBASE_API_KEY = os.environ[\\\"MACROFACTOR_FIREBASE_API_KEY\\\"]\\nEMAIL = os.environ[\\\"MACROFACTOR_EMAIL\\\"]\\nPASSWORD = os.environ[\\\"MACROFACTOR_PASSWORD\\\"]\\n\\nIDENTITY_URL = (\\n \\\"https://identitytoolkit.googleapis.com/v1/\\\"\\n f\\\"accounts:signInWithPassword?key={FIREBASE_API_KEY}\\\"\\n)\\nREFRESH_URL = (\\n \\\"https://securetoken.googleapis.com/v1/\\\"\\n f\\\"token?key={FIREBASE_API_KEY}\\\"\\n)\\nFIRESTORE_BASE = (\\n \\\"https://firestore.googleapis.com/v1/projects/\\\"\\n \\\"sbs-diet-app/databases/(default)/documents\\\"\\n)\\n\\n\\ndef login():\\n payload = {\\n \\\"email\\\": EMAIL,\\n \\\"password\\\": PASSWORD,\\n \\\"returnSecureToken\\\": True,\\n }\\n r = httpx.post(IDENTITY_URL, json=payload, timeout=30)\\n r.raise_for_status()\\n return r.json()\\n\\n\\ndef refresh_id_token(refresh_token: str):\\n payload = {\\n \\\"grant_type\\\": \\\"refresh_token\\\",\\n \\\"refresh_token\\\": refresh_token,\\n }\\n r = httpx.post(REFRESH_URL, data=payload, timeout=30)\\n r.raise_for_status()\\n return r.json()\\n\\n\\ndef firestore_get(path: str, id_token: str):\\n url = f\\\"{FIRESTORE_BASE}/{path.lstrip('/')}\\\"\\n headers = {\\\"Authorization\\\": f\\\"Bearer {id_token}\\\"}\\n r = httpx.get(url, headers=headers, timeout=30)\\n r.raise_for_status()\\n return r.json()\\n\\n\\ndef main():\\n tokens = login()\\n id_token = tokens[\\\"idToken\\\"]\\n user_id = tokens[\\\"localId\\\"]\\n\\n # Requiere validar paths exactos contra docs/repo.\\n # Ejemplos conceptuales:\\n # food_logs = firestore_get(f\\\"users/{user_id}/foodLogs\\\", id_token)\\n # weights = firestore_get(f\\\"users/{user_id}/weights\\\", id_token)\\n\\n print(\\\"Logged in:\\\", user_id)\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n```\\n\\n## Uso para Pipo\\n\\nMuy valioso si Ignacio usa MacroFactor:\\n\\n- leer promedio calórico real,\\n- leer peso/tendencia,\\n- cruzar con progreso Hevy,\\n- ajustar porciones:\\n - si peso baja más rápido de lo deseado y rendimiento cae: subir carbs/calorías,\\n - si peso no baja y adherencia alta: bajar 100-150 kcal,\\n - si proteína baja: recomendar porciones concretas.\\n\\n---\\n\\n# 2. MyFitnessPal\\n\\n## Estado\\n\\n- **Tipo de API:** REST oficial con OAuth2 Authorization Code.\\n- **Docs:** https://myfitnesspalapi.com/docs/\\n- **Auth docs:** https://myfitnesspalapi.com/docs/user-authentication/\\n- **OAuth params:** https://myfitnesspalapi.com/docs/request-query-parameters/\\n- **Factibilidad:** **2.5/5**\\n- **Costo:** requiere acceso partner / client id y client secret. Costo no público; requiere validación.\\n\\n## Datos accesibles\\n\\nScopes documentados:\\n\\n```text\\nmeasurements\\ndiary\\nprivate-exercises\\nsubscriptions\\n```\\n\\nPotencial:\\n\\n- diario nutricional,\\n- mediciones/peso,\\n- ejercicios privados,\\n- suscripciones.\\n\\n## Auth\\n\\nOAuth2 Authorization Code:\\n\\n```text\\nGET /oauth2/auth\\n response_type=code\\n client_id=...\\n redirect_uri=...\\n scope=diary measurements private-exercises subscriptions\\n state=...\\n\\nPOST token endpoint\\n code\\n client_id\\n client_secret\\n redirect_uri\\n```\\n\\nLa documentación indica access token + refresh token.\\n\\n## Riesgos / validaciones\\n\\n- Requiere acceso oficial de partner.\\n- Hay que validar disponibilidad para desarrollador individual.\\n- No asumir acceso hasta tener client id/secret.\\n- Si no se consigue acceso, no conviene invertir.\\n\\n## Python skeleton con Authlib\\n\\n```python\\nimport os\\nfrom authlib.integrations.requests_client import OAuth2Session\\n\\nCLIENT_ID = os.environ[\\\"MFP_CLIENT_ID\\\"]\\nCLIENT_SECRET = os.environ[\\\"MFP_CLIENT_SECRET\\\"]\\nREDIRECT_URI = os.environ[\\\"MFP_REDIRECT_URI\\\"]\\n\\nAUTHORIZE_URL = \\\"https://api.myfitnesspal.com/v2/oauth2/auth\\\"\\nTOKEN_URL = \\\"https://api.myfitnesspal.com/v2/oauth2/token\\\"\\nAPI_BASE = \\\"https://api.myfitnesspal.com/v2\\\"\\n\\nSCOPES = [\\\"diary\\\", \\\"measurements\\\", \\\"private-exercises\\\", \\\"subscriptions\\\"]\\n\\n\\ndef build_auth_url():\\n client = OAuth2Session(\\n CLIENT_ID,\\n CLIENT_SECRET,\\n scope=\\\" \\\".join(SCOPES),\\n redirect_uri=REDIRECT_URI,\\n )\\n uri, state = client.create_authorization_url(AUTHORIZE_URL)\\n return uri, state\\n\\n\\ndef exchange_code(code: str):\\n client = OAuth2Session(\\n CLIENT_ID,\\n CLIENT_SECRET,\\n redirect_uri=REDIRECT_URI,\\n )\\n token = client.fetch_token(TOKEN_URL, code=code)\\n return token\\n\\n\\ndef get_diary(token: dict, date: str):\\n client = OAuth2Session(CLIENT_ID, CLIENT_SECRET, token=token)\\n # Endpoint exacto requiere validar contra docs de recursos MFP.\\n r = client.get(f\\\"{API_BASE}/diary\\\", params={\\\"date\\\": date})\\n r.raise_for_status()\\n return r.json()\\n\\n\\nif __name__ == \\\"__main__\\\":\\n url, state = build_auth_url()\\n print(\\\"Open:\\\", url)\\n```\\n\\n## Uso para Pipo\\n\\nSi se consigue acceso:\\n\\n- leer calories/protein/carbs/fat por día,\\n- detectar adherencia,\\n- cruzar entrenamiento/peso,\\n- generar recomendaciones de porciones.\\n\\nPero como integración práctica inmediata, queda debajo de Fitbit/MacroFactor/Health Connect.\\n\\n---\\n\\n# 3. Fitbit\\n\\n## Estado\\n\\n- **Tipo de API:** Web API oficial REST.\\n- **Docs base:** https://dev.fitbit.com/build/reference/web-api/\\n- **OAuth2:** https://dev.fitbit.com/build/reference/web-api/oauth2\\n- **Nutrition:** https://dev.fitbit.com/build/reference/web-api/nutrition\\n- **Activity:** https://dev.fitbit.com/build/reference/web-api/activity\\n- **Factibilidad:** **4.5/5**\\n- **Costo:** gratis para uso developer normal; sujeto a políticas y cuotas. Requiere registrar app.\\n\\n## Datos accesibles\\n\\nScopes relevantes:\\n\\n```text\\nactivity\\nheartrate\\nnutrition\\nprofile\\nsettings\\nsleep\\nweight\\nrespiratory_rate\\noxygen_saturation\\ntemperature\\nlocation\\n```\\n\\nDatos útiles para Pipo:\\n\\n- pasos diarios,\\n- calorías quemadas,\\n- active minutes,\\n- distancia,\\n- workouts/cardio,\\n- sueño y etapas,\\n- resting HR,\\n- HRV si disponible según endpoint/producto,\\n- peso,\\n- grasa corporal,\\n- food/water logs si se usan.\\n\\n## Auth\\n\\nFitbit recomienda OAuth2 Authorization Code con PKCE.\\n\\nAuthorize:\\n\\n```text\\nhttps://www.fitbit.com/oauth2/authorize\\n client_id=...\\n response_type=code\\n code_challenge=...\\n code_challenge_method=S256\\n scope=activity heartrate nutrition sleep weight profile\\n```\\n\\nToken:\\n\\n```text\\nPOST https://api.fitbit.com/oauth2/token\\n```\\n\\nDevuelve:\\n\\n```json\\n{\\n \\\"access_token\\\": \\\"...\\\",\\n \\\"expires_in\\\": 28800,\\n \\\"refresh_token\\\": \\\"...\\\",\\n \\\"scope\\\": \\\"...\\\",\\n \\\"token_type\\\": \\\"Bearer\\\",\\n \\\"user_id\\\": \\\"...\\\"\\n}\\n```\\n\\n## Python skeleton\\n\\n```python\\nimport os\\nimport base64\\nimport hashlib\\nimport secrets\\nimport httpx\\nfrom urllib.parse import urlencode\\n\\nCLIENT_ID = os.environ[\\\"FITBIT_CLIENT_ID\\\"]\\nCLIENT_SECRET = os.getenv(\\\"FITBIT_CLIENT_SECRET\\\") # server apps\\nREDIRECT_URI = os.environ[\\\"FITBIT_REDIRECT_URI\\\"]\\n\\nAUTH_URL = \\\"https://www.fitbit.com/oauth2/authorize\\\"\\nTOKEN_URL = \\\"https://api.fitbit.com/oauth2/token\\\"\\nAPI_BASE = \\\"https://api.fitbit.com/1/user/-\\\"\\n\\nSCOPES = [\\n \\\"activity\\\",\\n \\\"heartrate\\\",\\n \\\"nutrition\\\",\\n \\\"profile\\\",\\n \\\"settings\\\",\\n \\\"sleep\\\",\\n \\\"weight\\\",\\n]\\n\\n\\ndef make_pkce():\\n verifier = base64.urlsafe_b64encode(secrets.token_bytes(32)).rstrip(b\\\"=\\\").decode()\\n challenge = base64.urlsafe_b64encode(\\n hashlib.sha256(verifier.encode()).digest()\\n ).rstrip(b\\\"=\\\").decode()\\n return verifier, challenge\\n\\n\\ndef build_auth_url():\\n verifier, challenge = make_pkce()\\n params = {\\n \\\"client_id\\\": CLIENT_ID,\\n \\\"response_type\\\": \\\"code\\\",\\n \\\"code_challenge\\\": challenge,\\n \\\"code_challenge_method\\\": \\\"S256\\\",\\n \\\"scope\\\": \\\" \\\".join(SCOPES),\\n \\\"redirect_uri\\\": REDIRECT_URI,\\n }\\n return f\\\"{AUTH_URL}?{urlencode(params)}\\\", verifier\\n\\n\\ndef exchange_code(code: str, code_verifier: str):\\n data = {\\n \\\"client_id\\\": CLIENT_ID,\\n \\\"grant_type\\\": \\\"authorization_code\\\",\\n \\\"code\\\": code,\\n \\\"code_verifier\\\": code_verifier,\\n \\\"redirect_uri\\\": REDIRECT_URI,\\n }\\n auth = (CLIENT_ID, CLIENT_SECRET) if CLIENT_SECRET else None\\n r = httpx.post(TOKEN_URL, data=data, auth=auth, timeout=30)\\n r.raise_for_status()\\n return r.json()\\n\\n\\ndef refresh_token(refresh_token_value: str):\\n data = {\\n \\\"grant_type\\\": \\\"refresh_token\\\",\\n \\\"refresh_token\\\": refresh_token_value,\\n \\\"client_id\\\": CLIENT_ID,\\n }\\n auth = (CLIENT_ID, CLIENT_SECRET) if CLIENT_SECRET else None\\n r = httpx.post(TOKEN_URL, data=data, auth=auth, timeout=30)\\n r.raise_for_status()\\n return r.json()\\n\\n\\ndef fitbit_get(access_token: str, path: str):\\n headers = {\\\"Authorization\\\": f\\\"Bearer {access_token}\\\"}\\n r = httpx.get(f\\\"{API_BASE}/{path.lstrip('/')}\\\", headers=headers, timeout=30)\\n r.raise_for_status()\\n return r.json()\\n\\n\\ndef get_daily_summary(access_token: str, date: str):\\n return fitbit_get(access_token, f\\\"activities/date/{date}.json\\\")\\n\\n\\ndef get_sleep(access_token: str, date: str):\\n return fitbit_get(access_token, f\\\"sleep/date/{date}.json\\\")\\n\\n\\ndef get_weight(access_token: str, date: str):\\n return fitbit_get(access_token, f\\\"body/log/weight/date/{date}.json\\\")\\n\\n\\ndef get_food(access_token: str, date: str):\\n return fitbit_get(access_token, f\\\"foods/log/date/{date}.json\\\")\\n```\\n\\n## Uso para Pipo\\n\\nMuy recomendable:\\n\\n- readiness basado en sueño + HR/resting HR + pasos,\\n- ajuste de volumen/intensidad:\\n - mal sueño + HR alta + DOMS: bajar RPE objetivo,\\n - pasos muy altos: subir carbs o reducir cardio,\\n - sueño sólido + buena tendencia: progresión normal.\\n- peso/tendencia si Fitbit recibe báscula.\\n\\n---\\n\\n# 4. Google Health Connect\\n\\n## Estado\\n\\n- **Tipo de API:** Android on-device API.\\n- **Docs:** https://developer.android.com/health-and-fitness/guides/health-connect/develop/get-started\\n- **Codelab:** https://developer.android.com/codelabs/health-connect\\n- **Factibilidad:** **4/5**, pero requiere app/bridge Android.\\n- **Costo:** gratis.\\n- **Cloud API directa:** no. Es device-centric.\\n\\n## Datos accesibles\\n\\nHealth Connect puede leer/escribir tipos como:\\n\\n- StepsRecord,\\n- DistanceRecord,\\n- TotalCaloriesBurnedRecord,\\n- ActiveCaloriesBurnedRecord,\\n- ExerciseSessionRecord,\\n- SleepSessionRecord,\\n- WeightRecord,\\n- BodyFatRecord,\\n- HeartRateRecord,\\n- RestingHeartRateRecord,\\n- NutritionRecord,\\n- HydrationRecord,\\n- etc.\\n\\nDepende de:\\n- permisos concedidos,\\n- apps fuente instaladas,\\n- si esas apps escriben en Health Connect.\\n\\n## Auth/permisos\\n\\nNo usa OAuth.\\n\\nUsa:\\n\\n- permisos Android manifest,\\n- pantalla de permisos Health Connect,\\n- `HealthConnectClient`,\\n- permisos por record type.\\n\\nImportante: documentación/codelab indica que la lectura tiene restricciones de privacidad y foreground. Para sync confiable hacia Hermes, hay que diseñar bridge local con consentimiento claro.\\n\\n## Arquitectura bridge recomendada\\n\\nComo Hermes corre fuera del teléfono, se necesita uno de estos:\\n\\n### Opción A: Android companion app\\n\\n```text\\nPixel/Android\\n Health Connect Bridge App\\n lee Health Connect\\n normaliza datos\\n envía HTTPS a Hermes endpoint local/cloud\\n```\\n\\n### Opción B: Termux/local bridge\\n\\nMenos recomendable porque Health Connect requiere app Android con SDK/permisos.\\n\\n### Opción C: Google Health API / Fitbit API\\n\\nPara cloud, mejor Fitbit/Google Health API cuando aplique.\\n\\n## Kotlin skeleton bridge\\n\\nNo es Python porque Health Connect es Android/Kotlin.\\n\\n```kotlin\\nval permissions = setOf(\\n HealthPermission.getReadPermission(StepsRecord::class),\\n HealthPermission.getReadPermission(SleepSessionRecord::class),\\n HealthPermission.getReadPermission(WeightRecord::class),\\n HealthPermission.getReadPermission(HeartRateRecord::class),\\n HealthPermission.getReadPermission(NutritionRecord::class),\\n)\\n\\nval healthConnectClient = HealthConnectClient.getOrCreate(context)\\n\\nval granted = healthConnectClient.permissionController.getGrantedPermissions()\\n\\nif (!granted.containsAll(permissions)) {\\n // Launch permission request contract from Activity\\n}\\n\\nsuspend fun readSteps(start: Instant, end: Instant): Long {\\n val response = healthConnectClient.aggregate(\\n AggregateRequest(\\n metrics = setOf(StepsRecord.COUNT_TOTAL),\\n timeRangeFilter = TimeRangeFilter.between(start, end)\\n )\\n )\\n return response[StepsRecord.COUNT_TOTAL] ?: 0L\\n}\\n```\\n\\n## Python receiving endpoint skeleton\\n\\n```python\\nfrom fastapi import FastAPI, Header, HTTPException\\nfrom pydantic import BaseModel\\nfrom typing import Any\\nimport os\\n\\napp = FastAPI()\\n\\nBRIDGE_TOKEN = os.environ[\\\"HEALTH_CONNECT_BRIDGE_TOKEN\\\"]\\n\\n\\nclass HealthConnectPayload(BaseModel):\\n source: str = \\\"health_connect\\\"\\n device_id: str\\n synced_at: str\\n data_type: str\\n records: list[dict[str, Any]]\\n\\n\\n@app.post(\\\"/ingest/health-connect\\\")\\ndef ingest_health_connect(\\n payload: HealthConnectPayload,\\n authorization: str | None = Header(default=None),\\n):\\n if authorization != f\\\"Bearer {BRIDGE_TOKEN}\\\":\\n raise HTTPException(status_code=401, detail=\\\"unauthorized\\\")\\n\\n # TODO: validate schema per data_type and upsert normalized DB.\\n return {\\\"ok\\\": True, \\\"received\\\": len(payload.records)}\\n```\\n\\n## Uso para Pipo\\n\\nMuy bueno en Android/Pixel:\\n\\n- centraliza fuentes,\\n- no depende de Apple,\\n- puede leer datos de apps diversas,\\n- evita integrar mil APIs.\\n\\nLimitación principal: necesita companion app.\\n\\n---\\n\\n# 5. Google Fit\\n\\n## Estado\\n\\n- **Tipo de API:** REST/Android legacy.\\n- **Docs migración:** https://developer.android.com/health-and-fitness/health-connect/migration/fit\\n- **FAQ:** https://developer.android.com/health-and-fitness/guides/health-connect/migrate/fit-apis-end-of-service\\n- **Factibilidad:** **1.5/5** para integración nueva.\\n- **Costo:** gratis, pero no recomendable.\\n- **Estado:** deprecándose; soporte hasta late/end 2026 según docs.\\n\\n## Dato clave\\n\\nGoogle indica:\\n\\n- Google Fit APIs, incluyendo REST API, soportadas solo hasta fines de 2026.\\n- Nuevas integraciones deberían usar:\\n - **Health Connect** para mobile/on-device,\\n - **Google Health API** para cloud/web-centric,\\n - Fitbit Web API / Google Health API para datos de dispositivos Google/Fitbit.\\n\\n## Datos accesibles\\n\\nHistóricamente:\\n\\n- steps,\\n- calories,\\n- distance,\\n- heart points,\\n- weight,\\n- activities/sessions,\\n- sleep si estaba registrado,\\n- datasets por data source.\\n\\nPero no conviene invertir en esto para Pipo.\\n\\n## Auth\\n\\nOAuth2 Google scopes. Requiere Google Cloud project.\\n\\n## Python skeleton legacy, solo si ya existe integración\\n\\n```python\\nimport os\\nimport httpx\\nfrom authlib.integrations.requests_client import OAuth2Session\\n\\nCLIENT_ID = os.environ[\\\"GOOGLE_CLIENT_ID\\\"]\\nCLIENT_SECRET = os.environ[\\\"GOOGLE_CLIENT_SECRET\\\"]\\nREDIRECT_URI = os.environ[\\\"GOOGLE_REDIRECT_URI\\\"]\\n\\nAUTH_URL = \\\"https://accounts.google.com/o/oauth2/v2/auth\\\"\\nTOKEN_URL = \\\"https://oauth2.googleapis.com/token\\\"\\nFIT_BASE = \\\"https://www.googleapis.com/fitness/v1/users/me\\\"\\n\\nSCOPES = [\\n \\\"https://www.googleapis.com/auth/fitness.activity.read\\\",\\n \\\"https://www.googleapis.com/auth/fitness.body.read\\\",\\n \\\"https://www.googleapis.com/auth/fitness.sleep.read\\\",\\n]\\n\\n\\ndef build_auth_url():\\n client = OAuth2Session(\\n CLIENT_ID,\\n CLIENT_SECRET,\\n scope=\\\" \\\".join(SCOPES),\\n redirect_uri=REDIRECT_URI,\\n )\\n uri, state = client.create_authorization_url(\\n AUTH_URL,\\n access_type=\\\"offline\\\",\\n prompt=\\\"consent\\\",\\n )\\n return uri, state\\n\\n\\ndef aggregate_steps(token: dict, start_ms: int, end_ms: int):\\n client = OAuth2Session(CLIENT_ID, CLIENT_SECRET, token=token)\\n body = {\\n \\\"aggregateBy\\\": [\\n {\\\"dataTypeName\\\": \\\"com.google.step_count.delta\\\"}\\n ],\\n \\\"bucketByTime\\\": {\\\"durationMillis\\\": 86400000},\\n \\\"startTimeMillis\\\": start_ms,\\n \\\"endTimeMillis\\\": end_ms,\\n }\\n r = client.post(f\\\"{FIT_BASE}/dataset:aggregate\\\", json=body)\\n r.raise_for_status()\\n return r.json()\\n```\\n\\n## Recomendación\\n\\nNo usar salvo que Ignacio ya tenga datos históricos en Google Fit y quiera migrarlos/exportarlos.\\n\\nPara Pipo: **Health Connect > Google Fit**.\\n\\n---\\n\\n# 6. Cronometer\\n\\n## Estado\\n\\n- **Tipo de API:** no pública para usuarios individuales.\\n- **API oficial:** Cronometer Pro dice tener API caso por caso.\\n- **Pro page:** http://www.cronometer.com/pro/\\n- **MCP reverse-engineered:** https://github.com/cphoskins/cronometer-mcp\\n- **PyPI MCP:** https://pypi.org/project/cronometer-mcp/\\n- **Mobile reverse-engineered MCP:** https://pypi.org/project/cronometer-api-mcp/\\n- **Factibilidad:** **3/5** para uso personal; **1.5/5** como integración robusta oficial.\\n- **Costo:** Cronometer app/subscription si aplica; API oficial caso por caso; reverse-engineered sin costo pero frágil.\\n\\n## Datos accesibles vía reverse-engineered MCP\\n\\nSegún `cronometer-mcp`:\\n\\n- food logs,\\n- daily macro/micro summaries,\\n- diary entries,\\n- fasting,\\n- biometrics,\\n- recurring foods,\\n- macro targets.\\n\\nMecanismo web:\\n\\n- GWT-RPC interno,\\n- login page + CSRF,\\n- cookies,\\n- export tokens,\\n- CSV exports,\\n- llamadas directas para editar diary/biometrics/etc.\\n\\nMecanismo mobile MCP:\\n\\n- `mobile.cronometer.com`,\\n- endpoints `/api/v2/*`,\\n- JSON-body auth,\\n- `/api/v3/user/{id}/*` para algunas operaciones,\\n- reverse-engineered vía APK/traffic.\\n\\n## Riesgos / validaciones\\n\\n- No API oficial individual.\\n- Cronometer tiene rate limiting agresivo en login según MCP.\\n- Puede romperse con cambios internos.\\n- Posible conflicto con ToS.\\n- Requiere validación de endpoints y credenciales reales.\\n- Para uso personal puede servir, especialmente por micronutrientes.\\n\\n## Python skeleton usando MCP/package\\n\\n```python\\nfrom datetime import date, timedelta\\nfrom cronometer_mcp import CronometerClient\\n\\ndef main():\\n # Según docs, lee credenciales de env vars.\\n # Requiere validar nombres exactos de env vars del paquete.\\n client = CronometerClient()\\n\\n today = date.today()\\n start = today - timedelta(days=7)\\n\\n foods = client.get_food_log()\\n print(\\\"foods\\\", foods)\\n\\n # Los métodos exactos requieren validar versión del paquete.\\n # Ejemplo conceptual:\\n # summary = client.get_daily_summary(today)\\n # biometrics = client.get_biometrics(start, today)\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n```\\n\\n## Python skeleton export genérico con requests\\n\\n```python\\nimport os\\nimport requests\\n\\nEMAIL = os.environ[\\\"CRONOMETER_EMAIL\\\"]\\nPASSWORD = os.environ[\\\"CRONOMETER_PASSWORD\\\"]\\n\\nsession = requests.Session()\\n\\ndef login():\\n # Placeholder: Cronometer web login/GWT-RPC requiere CSRF y payload exacto.\\n # Recomiendo usar cronometer-mcp en vez de reimplementar.\\n raise NotImplementedError(\\\"Use cronometer-mcp or validate GWT-RPC flow\\\")\\n\\ndef export_daily_nutrition(start_date: str, end_date: str):\\n # Placeholder: requiere generateAuthorizationToken y CSV export URL.\\n raise NotImplementedError(\\\"Requires reverse-engineered export token flow\\\")\\n```\\n\\n## Uso para Pipo\\n\\nMuy bueno para micronutrientes y calidad nutricional si Ignacio usa Cronometer:\\n\\n- detectar falta de fibra,\\n- sodio/potasio/magnesio,\\n- proteína,\\n- calorías,\\n- adherence.\\n\\nPero para producto estable, preferir MacroFactor/Fitbit/Health Connect.\\n\\n---\\n\\n# 7. Hevy\\n\\n## Estado\\n\\n- **Tipo de API:** pública oficial REST.\\n- **Docs:** https://api.hevyapp.com/docs/\\n- **Base URL:** `https://api.hevyapp.com`\\n- **Auth:** API key header.\\n- **API key:** Hevy Pro, desde https://hevy.com/settings?developer\\n- **Factibilidad:** **5/5**\\n- **Costo:** requiere Hevy Pro para API.\\n- **Situación:** ya conectado según contexto.\\n\\n## Datos accesibles\\n\\nEndpoints documentados:\\n\\n### Workouts\\n\\n```text\\nGET /v1/workouts\\nPOST /v1/workouts\\nGET /v1/workouts/count\\nGET /v1/workouts/events\\nGET /v1/workouts/{workoutId}\\nPUT /v1/workouts/{workoutId}\\n```\\n\\n### Users\\n\\n```text\\nGET /v1/user/info\\n```\\n\\n### Routines\\n\\n```text\\nGET /v1/routines\\nPOST /v1/routines\\nGET /v1/routines/{routineId}\\nPUT /v1/routines/{routineId}\\n```\\n\\n### Exercise templates\\n\\n```text\\nGET /v1/exercise_templates\\nPOST /v1/exercise_templates\\nGET /v1/exercise_templates/{exerciseTemplateId}\\n```\\n\\n### Routine folders\\n\\n```text\\nGET /v1/routine_folders\\nPOST /v1/routine_folders\\nGET /v1/routine_folders/{folderId}\\n```\\n\\n### Exercise history\\n\\n```text\\nGET /v1/exercise_history/{exerciseTemplateId}\\n```\\n\\n### Body measurements\\n\\n```text\\nGET /v1/body_measurements\\nPOST /v1/body_measurements\\nGET /v1/body_measurements/{date}\\nPUT /v1/body_measurements/{date}\\n```\\n\\n## Auth\\n\\nHeader según docs/clientes:\\n\\n```text\\napi-key: \\n```\\n\\n## Python skeleton\\n\\n```python\\nimport os\\nimport httpx\\n\\nHEVY_API_KEY = os.environ[\\\"HEVY_API_KEY\\\"]\\nBASE_URL = \\\"https://api.hevyapp.com\\\"\\n\\nclient = httpx.Client(\\n base_url=BASE_URL,\\n headers={\\\"api-key\\\": HEVY_API_KEY},\\n timeout=30,\\n)\\n\\n\\ndef get_user_info():\\n r = client.get(\\\"/v1/user/info\\\")\\n r.raise_for_status()\\n return r.json()\\n\\n\\ndef list_workouts(page: int = 1, page_size: int = 10):\\n r = client.get(\\n \\\"/v1/workouts\\\",\\n params={\\\"page\\\": page, \\\"pageSize\\\": page_size},\\n )\\n r.raise_for_status()\\n return r.json()\\n\\n\\ndef get_workout(workout_id: str):\\n r = client.get(f\\\"/v1/workouts/{workout_id}\\\")\\n r.raise_for_status()\\n return r.json()\\n\\n\\ndef get_workout_events(since: str, page: int = 1, page_size: int = 100):\\n \\\"\\\"\\\"\\n since: ISO timestamp/date, validar formato exacto requerido por Swagger.\\n \\\"\\\"\\\"\\n r = client.get(\\n \\\"/v1/workouts/events\\\",\\n params={\\\"since\\\": since, \\\"page\\\": page, \\\"pageSize\\\": page_size},\\n )\\n r.raise_for_status()\\n return r.json()\\n\\n\\ndef list_routines(page: int = 1, page_size: int = 10):\\n r = client.get(\\n \\\"/v1/routines\\\",\\n params={\\\"page\\\": page, \\\"pageSize\\\": page_size},\\n )\\n r.raise_for_status()\\n return r.json()\\n\\n\\ndef get_exercise_history(exercise_template_id: str):\\n r = client.get(f\\\"/v1/exercise_history/{exercise_template_id}\\\")\\n r.raise_for_status()\\n return r.json()\\n\\n\\ndef list_body_measurements(page: int = 1, page_size: int = 100):\\n r = client.get(\\n \\\"/v1/body_measurements\\\",\\n params={\\\"page\\\": page, \\\"pageSize\\\": page_size},\\n )\\n r.raise_for_status()\\n return r.json()\\n\\n\\nif __name__ == \\\"__main__\\\":\\n print(get_user_info())\\n print(list_workouts(page_size=5))\\n```\\n\\n## Uso para Pipo\\n\\nFuente principal de entrenamiento:\\n\\n- detectar cumplimiento del programa Jeff Nippard Min-Max 4-day,\\n- analizar progresión por ejercicio,\\n- detectar estancamiento,\\n- estimar volumen semanal por músculo,\\n- ajustar cargas/reps objetivo,\\n- recomendar deload,\\n- cruzar con sueño/nutrición/peso.\\n\\nEjemplos de lógica:\\n\\n```text\\nSi press banca no progresa 3 sesiones y sueño < 6h promedio:\\n mantener carga, bajar 1 set accesorio, subir carbs pre-workout.\\n\\nSi peso baja >0.8%/semana y e1RM cae:\\n subir 150-250 kcal/día, especialmente carbs días de pierna.\\n\\nSi pasos >12k y pierna pesada:\\n sugerir RPE cap 8 en sentadilla/peso muerto.\\n\\nSi sueño >7.5h y última sesión completada con RIR alto:\\n subir 2.5 kg o +1 rep objetivo.\\n```\\n\\n---\\n\\n# Comparativa rápida\\n\\n| App | API type | Auth | Datos clave | Factibilidad | Costo |\\n|---|---|---:|---|---:|---|\\n| MacroFactor | Firestore reverse-engineered | Firebase email/pass o refresh token | nutrición, peso, food logs, summaries, workouts | 3.5/5 | suscripción MacroFactor |\\n| MyFitnessPal | REST oficial partner | OAuth2 | diary, measurements, exercises | 2.5/5 | acceso partner, requiere validación |\\n| Fitbit | REST oficial | OAuth2 PKCE | sueño, pasos, HR, peso, nutrición, actividad | 4.5/5 | gratis/dev, dispositivo/app |\\n| Health Connect | Android on-device | permisos Android | hub salud Android: pasos, sueño, peso, nutrición, HR | 4/5 | gratis, requiere app bridge |\\n| Google Fit | REST legacy | OAuth2 | actividad/peso/sueño legacy | 1.5/5 | gratis pero deprecado |\\n| Cronometer | sin API pública; MCP/reverse | cookies/GWT/mobile auth | macros, micros, biometrics, fasting | 3/5 personal | app/sub, API oficial caso por caso |\\n| Hevy | REST oficial | API key | workouts, routines, sets, exercise history, measurements | 5/5 | Hevy Pro |\\n\\n---\\n\\n# Prioridad de implementación\\n\\n## Fase 1 — inmediata\\n\\n1. Consolidar **Hevy**:\\n - sync incremental con `/v1/workouts/events`,\\n - workouts,\\n - routines,\\n - exercise history,\\n - body measurements.\\n\\n2. Agregar **Fitbit Web API** si Ignacio tiene Fitbit/Pixel Watch/Fitbit app:\\n - sleep,\\n - activity,\\n - resting HR,\\n - weight.\\n\\n3. Crear modelo normalizado:\\n - `workouts`,\\n - `workout_sets`,\\n - `sleep_daily`,\\n - `activity_daily`,\\n - `body_weight`,\\n - `nutrition_daily`.\\n\\n## Fase 2 — nutrición\\n\\nElegir una fuente:\\n\\n- Si Ignacio usa o acepta usar MacroFactor: **MacroFactor**.\\n- Si prioriza micronutrientes: **Cronometer**.\\n- Si ya usa MyFitnessPal y se consigue API partner: **MFP**.\\n- Si quiere Android hub: **Health Connect bridge**.\\n\\n## Fase 3 — Very Personal Trainer\\n\\nImplementar motor de decisiones:\\n\\n```python\\ndef recommend_adjustments(context):\\n \\\"\\\"\\\"\\n context:\\n - last_14d_weight_trend\\n - last_7d_calories/protein\\n - sleep_7d_avg\\n - steps_7d_avg\\n - hevy_progression\\n - next_session\\n \\\"\\\"\\\"\\n\\n recommendations = []\\n\\n if context[\\\"sleep_7d_avg_hours\\\"] < 6.5:\\n recommendations.append({\\n \\\"type\\\": \\\"training\\\",\\n \\\"action\\\": \\\"cap_intensity\\\",\\n \\\"details\\\": \\\"Mantener RPE <= 8 y evitar PRs hoy.\\\"\\n })\\n\\n if context[\\\"weight_loss_pct_week\\\"] > 0.8 and context[\\\"performance_down\\\"]:\\n recommendations.append({\\n \\\"type\\\": \\\"nutrition\\\",\\n \\\"action\\\": \\\"increase_calories\\\",\\n \\\"details\\\": \\\"Subir 150-250 kcal, preferentemente carbs alrededor del entrenamiento.\\\"\\n })\\n\\n if context[\\\"protein_g_per_kg\\\"] < 1.6:\\n recommendations.append({\\n \\\"type\\\": \\\"nutrition\\\",\\n \\\"action\\\": \\\"increase_protein\\\",\\n \\\"details\\\": \\\"Agregar una porción de proteína magra o whey.\\\"\\n })\\n\\n return recommendations\\n```\\n\\n---\\n\\n# Issues encontrados / puntos a validar\\n\\n1. **MacroFactor**\\n - Reverse-engineered, no oficial.\\n - Requiere validar paths Firestore exactos y credenciales.\\n - Requiere revisar ToS.\\n\\n2. **MyFitnessPal**\\n - API existe, pero parece de partners.\\n - Requiere obtener client id/client secret.\\n\\n3. **Fitbit**\\n - Muy viable.\\n - Requiere app registrada y OAuth consent.\\n - Fitbit Web API está en transición hacia Google Health API según docs comparativas, pero sigue siendo una opción práctica.\\n\\n4. **Health Connect**\\n - Excelente para Android.\\n - No sirve directamente desde Hermes cloud/local sin companion app Android.\\n - Hay restricciones de permisos/foreground que requieren diseño cuidadoso.\\n\\n5. **Google Fit**\\n - Deprecado; no iniciar salvo migración/histórico.\\n\\n6. **Cronometer**\\n - Sin API pública individual.\\n - MCP reverse-engineered usable, pero frágil.\\n\\n7. **Hevy**\\n - Mejor integración para entrenamiento.\\n - Requiere Hevy Pro API key.\\n - API pública joven; docs advierten que puede cambiar.\\n\\n---\\n\\n# Archivos creados/modificados\\n\\nNo creé ni modifiqué archivos locales. Investigación realizada vía web y reporte consolidado en esta respuesta.\", \"api_calls\": 3, \"duration_seconds\": 162.46, \"model\": \"gpt-5.5\", \"exit_reason\": \"completed\", \"tokens\": {\"input\": 49250, \"output\": 8637}, \"tool_trace\": [{\"tool\": \"web_search\", \"args_bytes\": 93, \"result_bytes\": 13073, \"status\": \"ok\"}, {\"tool\": \"web_search\", \"args_bytes\": 70, \"result_bytes\": 5840, \"status\": \"ok\"}, {\"tool\": \"web_search\", \"args_bytes\": 80, \"result_bytes\": 10141, \"status\": \"ok\"}, {\"tool\": \"web_search\", \"args_bytes\": 73, \"result_bytes\": 17247, \"status\": \"ok\"}, {\"tool\": \"web_search\", \"args_bytes\": 82, \"result_bytes\": 10113, \"status\": \"ok\"}, {\"tool\": \"web_search\", \"args_bytes\": 73, \"result_bytes\": 9874, \"status\": \"ok\"}, {\"tool\": \"web_search\", \"args_bytes\": 53, \"result_bytes\": 5788, \"status\": \"ok\"}, {\"tool\": \"web_search\", \"args_bytes\": 91, \"result_bytes\": 15305, \"status\": \"ok\"}, {\"tool\": \"web_search\", \"args_bytes\": 51, \"result_bytes\": 7439, \"status\": \"ok\"}]}], \"total_duration_seconds\": 162.53}",
"tool_call_id": "call_pmtoFUoVn8VjUWAfYC4fsjTm"
},
{
"role": "assistant",
"content": "Cargado `hevy` + leído `minmax-training-plan.md`.\n\nOjo de procedencia: usé `delegate_task` como pediste, pero el resultado del tool reportó `model: gpt-5.5`, no DeepSeek. No voy a mentirte: la delegación funcionó, pero no puedo afirmar que corrió en DeepSeek en esta ejecución. Si querés, después reviso la config de delegation.\n\n## Resultado — integraciones salud/nutrición para “Very Personal Trainer”\n\n### Ranking práctico\n\n| Prioridad | App | Uso para Pipo | Factibilidad |\n|---:|---|---|---:|\n| 1 | **Hevy** | entrenamiento, rutinas, progresión, sets | **5/5** |\n| 2 | **Fitbit** | sueño, pasos, HR, peso, actividad | **4.5/5** |\n| 3 | **Health Connect** | hub Android local: pasos/sueño/peso/nutrición | **4/5** pero requiere app bridge |\n| 4 | **MacroFactor** | nutrición, peso, gasto/adherencia | **3.5/5** reverse-engineered |\n| 5 | **Cronometer** | macros/micros/biometrics | **3/5** reverse/MCP |\n| 6 | **MyFitnessPal** | diario nutricional/peso | **2.5/5** API partner |\n| 7 | **Google Fit** | legacy actividad/peso | **1.5/5** deprecándose |\n\n---\n\n## 1. MacroFactor\n\n- **API type:** no oficial, reverse-engineered vía Firebase/Firestore.\n- **Repo:** https://github.com/sjawhar/macrofactor\n- **Datos accesibles:** food logs, weight entries, nutrition summaries, workouts, custom exercises, food search.\n- **Auth:** Firebase Identity Toolkit: email/password → `idToken` + `refreshToken`.\n- **Costo:** requiere suscripción MacroFactor.\n- **Factibilidad:** **3.5/5**\n- **Riesgo:** no oficial, puede romperse, revisar ToS.\n\nSkeleton:\n\n```python\nimport os\nimport httpx\n\nFIREBASE_API_KEY = os.environ[\"MACROFACTOR_FIREBASE_API_KEY\"]\nEMAIL = os.environ[\"MACROFACTOR_EMAIL\"]\nPASSWORD = os.environ[\"MACROFACTOR_PASSWORD\"]\n\nIDENTITY_URL = (\n \"https://identitytoolkit.googleapis.com/v1/\"\n f\"accounts:signInWithPassword?key={FIREBASE_API_KEY}\"\n)\n\nREFRESH_URL = (\n \"https://securetoken.googleapis.com/v1/\"\n f\"token?key={FIREBASE_API_KEY}\"\n)\n\nFIRESTORE_BASE = (\n \"https://firestore.googleapis.com/v1/projects/\"\n \"sbs-diet-app/databases/(default)/documents\"\n)\n\ndef login():\n r = httpx.post(\n IDENTITY_URL,\n json={\n \"email\": EMAIL,\n \"password\": PASSWORD,\n \"returnSecureToken\": True,\n },\n timeout=30,\n )\n r.raise_for_status()\n return r.json()\n\ndef refresh_id_token(refresh_token: str):\n r = httpx.post(\n REFRESH_URL,\n data={\n \"grant_type\": \"refresh_token\",\n \"refresh_token\": refresh_token,\n },\n timeout=30,\n )\n r.raise_for_status()\n return r.json()\n\ndef firestore_get(path: str, id_token: str):\n r = httpx.get(\n f\"{FIRESTORE_BASE}/{path.lstrip('/')}\",\n headers={\"Authorization\": f\"Bearer {id_token}\"},\n timeout=30,\n )\n r.raise_for_status()\n return r.json()\n\ntokens = login()\nuser_id = tokens[\"localId\"]\nid_token = tokens[\"idToken\"]\n\n# Paths exactos requieren validar contra repo/docs:\n# food_logs = firestore_get(f\"users/{user_id}/foodLogs\", id_token)\n# weights = firestore_get(f\"users/{user_id}/weights\", id_token)\n```\n\n---\n\n## 2. MyFitnessPal\n\n- **API type:** REST oficial con OAuth2.\n- **Docs:** https://myfitnesspalapi.com/docs/\n- **Auth:** OAuth2 Authorization Code.\n- **Scopes:** `measurements`, `diary`, `private-exercises`, `subscriptions`.\n- **Datos:** diario nutricional, mediciones/peso, ejercicios privados.\n- **Costo:** incierto; parece orientado a partners.\n- **Factibilidad:** **2.5/5**\n\nSkeleton:\n\n```python\nimport os\nfrom authlib.integrations.requests_client import OAuth2Session\n\nCLIENT_ID = os.environ[\"MFP_CLIENT_ID\"]\nCLIENT_SECRET = os.environ[\"MFP_CLIENT_SECRET\"]\nREDIRECT_URI = os.environ[\"MFP_REDIRECT_URI\"]\n\nAUTHORIZE_URL = \"https://api.myfitnesspal.com/v2/oauth2/auth\"\nTOKEN_URL = \"https://api.myfitnesspal.com/v2/oauth2/token\"\nAPI_BASE = \"https://api.myfitnesspal.com/v2\"\n\nSCOPES = [\"diary\", \"measurements\", \"private-exercises\", \"subscriptions\"]\n\ndef build_auth_url():\n client = OAuth2Session(\n CLIENT_ID,\n CLIENT_SECRET,\n scope=\" \".join(SCOPES),\n redirect_uri=REDIRECT_URI,\n )\n return client.create_authorization_url(AUTHORIZE_URL)\n\ndef exchange_code(code: str):\n client = OAuth2Session(\n CLIENT_ID,\n CLIENT_SECRET,\n redirect_uri=REDIRECT_URI,\n )\n return client.fetch_token(TOKEN_URL, code=code)\n\ndef get_diary(token: dict, date: str):\n client = OAuth2Session(CLIENT_ID, CLIENT_SECRET, token=token)\n r = client.get(f\"{API_BASE}/diary\", params={\"date\": date})\n r.raise_for_status()\n return r.json()\n```\n\n---\n\n## 3. Fitbit\n\n- **API type:** REST oficial.\n- **Docs:** https://dev.fitbit.com/build/reference/web-api/\n- **OAuth2:** https://dev.fitbit.com/build/reference/web-api/oauth2/\n- **Datos:** sueño, pasos, calorías, active minutes, HR, resting HR, peso, body fat, food logs.\n- **Auth:** OAuth2 Authorization Code + PKCE.\n- **Costo:** gratis/dev normal, requiere app Fitbit developer.\n- **Factibilidad:** **4.5/5**\n\nSkeleton:\n\n```python\nimport os\nimport base64\nimport hashlib\nimport secrets\nimport httpx\nfrom urllib.parse import urlencode\n\nCLIENT_ID = os.environ[\"FITBIT_CLIENT_ID\"]\nCLIENT_SECRET = os.getenv(\"FITBIT_CLIENT_SECRET\")\nREDIRECT_URI = os.environ[\"FITBIT_REDIRECT_URI\"]\n\nAUTH_URL = \"https://www.fitbit.com/oauth2/authorize\"\nTOKEN_URL = \"https://api.fitbit.com/oauth2/token\"\nAPI_BASE = \"https://api.fitbit.com/1/user/-\"\n\nSCOPES = [\n \"activity\",\n \"heartrate\",\n \"nutrition\",\n \"profile\",\n \"settings\",\n \"sleep\",\n \"weight\",\n]\n\ndef make_pkce():\n verifier = base64.urlsafe_b64encode(secrets.token_bytes(32)).rstrip(b\"=\").decode()\n challenge = base64.urlsafe_b64encode(\n hashlib.sha256(verifier.encode()).digest()\n ).rstrip(b\"=\").decode()\n return verifier, challenge\n\ndef build_auth_url():\n verifier, challenge = make_pkce()\n params = {\n \"client_id\": CLIENT_ID,\n \"response_type\": \"code\",\n \"code_challenge\": challenge,\n \"code_challenge_method\": \"S256\",\n \"scope\": \" \".join(SCOPES),\n \"redirect_uri\": REDIRECT_URI,\n }\n return f\"{AUTH_URL}?{urlencode(params)}\", verifier\n\ndef exchange_code(code: str, code_verifier: str):\n data = {\n \"client_id\": CLIENT_ID,\n \"grant_type\": \"authorization_code\",\n \"code\": code,\n \"code_verifier\": code_verifier,\n \"redirect_uri\": REDIRECT_URI,\n }\n auth = (CLIENT_ID, CLIENT_SECRET) if CLIENT_SECRET else None\n r = httpx.post(TOKEN_URL, data=data, auth=auth, timeout=30)\n r.raise_for_status()\n return r.json()\n\ndef fitbit_get(access_token: str, path: str):\n r = httpx.get(\n f\"{API_BASE}/{path.lstrip('/')}\",\n headers={\"Authorization\": f\"Bearer {access_token}\"},\n timeout=30,\n )\n r.raise_for_status()\n return r.json()\n\ndef get_daily_summary(access_token: str, date: str):\n return fitbit_get(access_token, f\"activities/date/{date}.json\")\n\ndef get_sleep(access_token: str, date: str):\n return fitbit_get(access_token, f\"sleep/date/{date}.json\")\n\ndef get_weight(access_token: str, date: str):\n return fitbit_get(access_token, f\"body/log/weight/date/{date}.json\")\n\ndef get_food(access_token: str, date: str):\n return fitbit_get(access_token, f\"foods/log/date/{date}.json\")\n```\n\n---\n\n## 4. Google Health Connect\n\n- **API type:** Android on-device API.\n- **Docs:** https://developer.android.com/health-and-fitness/guides/health-connect/develop/get-started\n- **Datos:** pasos, distancia, calories, exercise sessions, sleep, weight, HR, resting HR, nutrition, hydration.\n- **Auth:** permisos Android por record type. No OAuth cloud.\n- **Costo:** gratis.\n- **Factibilidad:** **4/5**, pero requiere companion app Android.\n- **Limitación clave:** Hermes en Oracle/no teléfono no puede leer Health Connect directamente.\n\nArquitectura:\n\n```text\nPixel / Android\n Health Connect Bridge App\n lee Health Connect\n normaliza records\n POST HTTPS a Hermes endpoint\n /ingest/health-connect\n```\n\nEndpoint Python en Hermes:\n\n```python\nfrom fastapi import FastAPI, Header, HTTPException\nfrom pydantic import BaseModel\nfrom typing import Any\nimport os\n\napp = FastAPI()\nBRIDGE_TOKEN = os.environ[\"HEALTH_CONNECT_BRIDGE_TOKEN\"]\n\nclass HealthConnectPayload(BaseModel):\n source: str = \"health_connect\"\n device_id: str\n synced_at: str\n data_type: str\n records: list[dict[str, Any]]\n\n@app.post(\"/ingest/health-connect\")\ndef ingest_health_connect(\n payload: HealthConnectPayload,\n authorization: str | None = Header(default=None),\n):\n if authorization != f\"Bearer {BRIDGE_TOKEN}\":\n raise HTTPException(status_code=401, detail=\"unauthorized\")\n\n # TODO: validate schema per data_type and upsert normalized DB.\n return {\"ok\": True, \"received\": len(payload.records)}\n```\n\nKotlin conceptual:\n\n```kotlin\nval permissions = setOf(\n HealthPermission.getReadPermission(StepsRecord::class),\n HealthPermission.getReadPermission(SleepSessionRecord::class),\n HealthPermission.getReadPermission(WeightRecord::class),\n HealthPermission.getReadPermission(HeartRateRecord::class),\n HealthPermission.getReadPermission(NutritionRecord::class),\n)\n\nval healthConnectClient = HealthConnectClient.getOrCreate(context)\n\nsuspend fun readSteps(start: Instant, end: Instant): Long {\n val response = healthConnectClient.aggregate(\n AggregateRequest(\n metrics = setOf(StepsRecord.COUNT_TOTAL),\n timeRangeFilter = TimeRangeFilter.between(start, end)\n )\n )\n return response[StepsRecord.COUNT_TOTAL] ?: 0L\n}\n```\n\n---\n\n## 5. Google Fit\n\n- **API type:** REST legacy.\n- **Docs migración:** https://developer.android.com/health-and-fitness/health-connect/migration/fit\n- **Estado:** deprecándose; Google empuja Health Connect / Google Health API.\n- **Datos:** steps, calories, distance, weight, sessions, sleep según fuentes.\n- **Auth:** Google OAuth2 scopes.\n- **Costo:** gratis.\n- **Factibilidad:** **1.5/5**\n\nRecomendación: **no arrancar integración nueva**. Solo usar si hay datos históricos que migrar/exportar.\n\nSkeleton legacy:\n\n```python\nimport os\nfrom authlib.integrations.requests_client import OAuth2Session\n\nCLIENT_ID = os.environ[\"GOOGLE_CLIENT_ID\"]\nCLIENT_SECRET = os.environ[\"GOOGLE_CLIENT_SECRET\"]\nREDIRECT_URI = os.environ[\"GOOGLE_REDIRECT_URI\"]\n\nAUTH_URL = \"https://accounts.google.com/o/oauth2/v2/auth\"\nTOKEN_URL = \"https://oauth2.googleapis.com/token\"\nFIT_BASE = \"https://www.googleapis.com/fitness/v1/users/me\"\n\nSCOPES = [\n \"https://www.googleapis.com/auth/fitness.activity.read\",\n \"https://www.googleapis.com/auth/fitness.body.read\",\n \"https://www.googleapis.com/auth/fitness.sleep.read\",\n]\n\ndef build_auth_url():\n client = OAuth2Session(\n CLIENT_ID,\n CLIENT_SECRET,\n scope=\" \".join(SCOPES),\n redirect_uri=REDIRECT_URI,\n )\n return client.create_authorization_url(\n AUTH_URL,\n access_type=\"offline\",\n prompt=\"consent\",\n )\n\ndef aggregate_steps(token: dict, start_ms: int, end_ms: int):\n client = OAuth2Session(CLIENT_ID, CLIENT_SECRET, token=token)\n body = {\n \"aggregateBy\": [{\"dataTypeName\": \"com.google.step_count.delta\"}],\n \"bucketByTime\": {\"durationMillis\": 86400000},\n \"startTimeMillis\": start_ms,\n \"endTimeMillis\": end_ms,\n }\n r = client.post(f\"{FIT_BASE}/dataset:aggregate\", json=body)\n r.raise_for_status()\n return r.json()\n```\n\n---\n\n## 6. Cronometer\n\n- **API type:** sin API pública oficial para usuarios individuales.\n- **Pro/API:** http://www.cronometer.com/pro/\n- **MCP reverse-engineered:** https://github.com/cphoskins/cronometer-mcp\n- **Datos:** food logs, macros, micros, biometrics, fasting, diary entries, macro targets.\n- **Auth:** cookies/GWT/mobile reverse-engineered.\n- **Costo:** app/subscription si aplica; API oficial caso por caso.\n- **Factibilidad:** **3/5 personal**, **1.5/5 robusto/oficial**.\n\nSkeleton usando MCP/package:\n\n```python\nfrom datetime import date, timedelta\nfrom cronometer_mcp import CronometerClient\n\ndef main():\n # Requiere validar env vars exactas del paquete.\n client = CronometerClient()\n\n today = date.today()\n start = today - timedelta(days=7)\n\n foods = client.get_food_log()\n print(foods)\n\n # Ejemplos conceptuales:\n # summary = client.get_daily_summary(today)\n # biometrics = client.get_biometrics(start, today)\n\nif __name__ == \"__main__\":\n main()\n```\n\n---\n\n## 7. Hevy\n\n- **API type:** REST oficial.\n- **Docs:** https://api.hevyapp.com/docs/\n- **Auth:** API key header.\n- **Datos:** workouts, workout events, routines, exercise templates, exercise history, body measurements.\n- **Costo:** Hevy Pro.\n- **Factibilidad:** **5/5**\n- **Estado tuyo:** ya conectado, rutinas Min-Max actualizadas en folder `2826578`.\n\nSkeleton:\n\n```python\nimport os\nimport httpx\n\nHEVY_API_KEY = os.environ[\"HEVY_API_KEY\"]\nBASE_URL = \"https://api.hevyapp.com\"\n\nclient = httpx.Client(\n base_url=BASE_URL,\n headers={\"api-key\": HEVY_API_KEY},\n timeout=30,\n)\n\ndef get_user_info():\n r = client.get(\"/v1/user/info\")\n r.raise_for_status()\n return r.json()\n\ndef list_workouts(page: int = 1, page_size: int = 10):\n r = client.get(\n \"/v1/workouts\",\n params={\"page\": page, \"pageSize\": page_size},\n )\n r.raise_for_status()\n return r.json()\n\ndef get_workout(workout_id: str):\n r = client.get(f\"/v1/workouts/{workout_id}\")\n r.raise_for_status()\n return r.json()\n\ndef get_workout_events(since: str, page: int = 1, page_size: int = 100):\n r = client.get(\n \"/v1/workouts/events\",\n params={\"since\": since, \"page\": page, \"pageSize\": page_size},\n )\n r.raise_for_status()\n return r.json()\n\ndef list_body_measurements(page: int = 1, page_size: int = 100):\n r = client.get(\n \"/v1/body_measurements\",\n params={\"page\": page, \"pageSize\": page_size},\n )\n r.raise_for_status()\n return r.json()\n```\n\n---\n\n# Arquitectura recomendada para Pipo\n\n```text\nHermes / Pipo\n |\n v\nhealth-integrations service\n |\n +-- hevy_connector.py\n +-- fitbit_connector.py\n +-- healthconnect_bridge_receiver.py\n +-- macrofactor_connector.py\n +-- cronometer_connector.py\n |\n v\nNormalized Health DB\n |\n +-- nutrition_daily\n +-- body_weight\n +-- activity_daily\n +-- sleep_daily\n +-- workouts\n +-- workout_sets\n +-- readiness_daily\n +-- recommendations\n```\n\nSchema mínimo:\n\n```sql\nCREATE TABLE nutrition_daily (\n source TEXT,\n date DATE,\n calories REAL,\n protein_g REAL,\n carbs_g REAL,\n fat_g REAL,\n fiber_g REAL,\n sodium_mg REAL,\n raw_json JSON,\n PRIMARY KEY (source, date)\n);\n\nCREATE TABLE body_weight (\n source TEXT,\n timestamp TIMESTAMP,\n weight_kg REAL,\n body_fat_pct REAL,\n raw_json JSON,\n PRIMARY KEY (source, timestamp)\n);\n\nCREATE TABLE activity_daily (\n source TEXT,\n date DATE,\n steps INTEGER,\n active_minutes INTEGER,\n calories_out REAL,\n distance_km REAL,\n raw_json JSON,\n PRIMARY KEY (source, date)\n);\n\nCREATE TABLE sleep_daily (\n source TEXT,\n date DATE,\n duration_min INTEGER,\n efficiency REAL,\n deep_min INTEGER,\n rem_min INTEGER,\n light_min INTEGER,\n awake_min INTEGER,\n raw_json JSON,\n PRIMARY KEY (source, date)\n);\n\nCREATE TABLE workouts (\n source TEXT,\n workout_id TEXT,\n started_at TIMESTAMP,\n ended_at TIMESTAMP,\n title TEXT,\n raw_json JSON,\n PRIMARY KEY (source, workout_id)\n);\n\nCREATE TABLE workout_sets (\n source TEXT,\n workout_id TEXT,\n exercise_id TEXT,\n exercise_name TEXT,\n set_index INTEGER,\n reps REAL,\n weight_kg REAL,\n rpe REAL,\n rir REAL,\n raw_json JSON\n);\n```\n\n---\n\n# Implementación por fases\n\n## Fase 1 — base sólida\n\n1. Hevy incremental sync:\n - `/v1/workouts/events`\n - workouts\n - routines\n - exercise history\n - body measurements\n\n2. Fitbit OAuth:\n - sleep\n - steps/activity\n - resting HR\n - weight\n\n3. DB normalizada.\n\n## Fase 2 — nutrición\n\nElegir una:\n\n- **MacroFactor** si querés nutrición + peso/tendencia + coaching serio.\n- **Cronometer** si te importan micros.\n- **Health Connect** si querés Android como hub.\n- **MFP** solo si conseguís API partner o ya estás casado con MFP.\n\nMi recomendación: **MacroFactor + Fitbit + Hevy** primero. Health Connect como bridge después.\n\n## Fase 3 — motor “Very Personal Trainer”\n\nReglas iniciales:\n\n```python\ndef recommend_adjustments(context):\n recommendations = []\n\n if context[\"sleep_7d_avg_hours\"] < 6.5:\n recommendations.append({\n \"type\": \"training\",\n \"action\": \"cap_intensity\",\n \"details\": \"Hoy no buscar PRs. Mantener RIR más conservador en compuestos.\",\n })\n\n if context[\"weight_loss_pct_week\"] > 0.8 and context[\"performance_down\"]:\n recommendations.append({\n \"type\": \"nutrition\",\n \"action\": \"increase_calories\",\n \"details\": \"Subir 150-250 kcal/día, preferentemente carbs alrededor del entrenamiento.\",\n })\n\n if context[\"protein_g_per_kg\"] < 1.6:\n recommendations.append({\n \"type\": \"nutrition\",\n \"action\": \"increase_protein\",\n \"details\": \"Agregar una porción de proteína magra o whey.\",\n })\n\n if context[\"steps_7d_avg\"] > 12000 and context[\"next_session\"] == \"Lower\":\n recommendations.append({\n \"type\": \"training\",\n \"action\": \"protect_lower_body\",\n \"details\": \"Mantener cargas, evitar failure real en Lower si piernas vienen cargadas.\",\n })\n\n return recommendations\n```\n\n## Veredicto corto\n\nPara tu caso real:\n\n1. **Hevy** ya está.\n2. Próximo mejor paso: **Fitbit Web API** si tenés fuente Fitbit/Pixel Watch/Fitbit app.\n3. Nutrición: **MacroFactor** es probablemente la mejor fuente si aceptás reverse-engineered.\n4. Health Connect vale mucho, pero implica construir **app Android bridge**.\n5. Google Fit no lo tocaría salvo migración histórica.\n6. Cronometer es útil si querés micronutrientes, pero más frágil.\n7. MyFitnessPal depende de acceso partner; no lo pondría como camino principal.",
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"text": "Cargado `hevy` + leído `minmax-training-plan.md`.\n\nOjo de procedencia: usé `delegate_task` como pediste, pero el resultado del tool reportó `model: gpt-5.5`, no DeepSeek. No voy a mentirte: la delegación funcionó, pero no puedo afirmar que corrió en DeepSeek en esta ejecución. Si querés, después reviso la config de delegation.\n\n## Resultado — integraciones salud/nutrición para “Very Personal Trainer”\n\n### Ranking práctico\n\n| Prioridad | App | Uso para Pipo | Factibilidad |\n|---:|---|---|---:|\n| 1 | **Hevy** | entrenamiento, rutinas, progresión, sets | **5/5** |\n| 2 | **Fitbit** | sueño, pasos, HR, peso, actividad | **4.5/5** |\n| 3 | **Health Connect** | hub Android local: pasos/sueño/peso/nutrición | **4/5** pero requiere app bridge |\n| 4 | **MacroFactor** | nutrición, peso, gasto/adherencia | **3.5/5** reverse-engineered |\n| 5 | **Cronometer** | macros/micros/biometrics | **3/5** reverse/MCP |\n| 6 | **MyFitnessPal** | diario nutricional/peso | **2.5/5** API partner |\n| 7 | **Google Fit** | legacy actividad/peso | **1.5/5** deprecándose |\n\n---\n\n## 1. MacroFactor\n\n- **API type:** no oficial, reverse-engineered vía Firebase/Firestore.\n- **Repo:** https://github.com/sjawhar/macrofactor\n- **Datos accesibles:** food logs, weight entries, nutrition summaries, workouts, custom exercises, food search.\n- **Auth:** Firebase Identity Toolkit: email/password → `idToken` + `refreshToken`.\n- **Costo:** requiere suscripción MacroFactor.\n- **Factibilidad:** **3.5/5**\n- **Riesgo:** no oficial, puede romperse, revisar ToS.\n\nSkeleton:\n\n```python\nimport os\nimport httpx\n\nFIREBASE_API_KEY = os.environ[\"MACROFACTOR_FIREBASE_API_KEY\"]\nEMAIL = os.environ[\"MACROFACTOR_EMAIL\"]\nPASSWORD = os.environ[\"MACROFACTOR_PASSWORD\"]\n\nIDENTITY_URL = (\n \"https://identitytoolkit.googleapis.com/v1/\"\n f\"accounts:signInWithPassword?key={FIREBASE_API_KEY}\"\n)\n\nREFRESH_URL = (\n \"https://securetoken.googleapis.com/v1/\"\n f\"token?key={FIREBASE_API_KEY}\"\n)\n\nFIRESTORE_BASE = (\n \"https://firestore.googleapis.com/v1/projects/\"\n \"sbs-diet-app/databases/(default)/documents\"\n)\n\ndef login():\n r = httpx.post(\n IDENTITY_URL,\n json={\n \"email\": EMAIL,\n \"password\": PASSWORD,\n \"returnSecureToken\": True,\n },\n timeout=30,\n )\n r.raise_for_status()\n return r.json()\n\ndef refresh_id_token(refresh_token: str):\n r = httpx.post(\n REFRESH_URL,\n data={\n \"grant_type\": \"refresh_token\",\n \"refresh_token\": refresh_token,\n },\n timeout=30,\n )\n r.raise_for_status()\n return r.json()\n\ndef firestore_get(path: str, id_token: str):\n r = httpx.get(\n f\"{FIRESTORE_BASE}/{path.lstrip('/')}\",\n headers={\"Authorization\": f\"Bearer {id_token}\"},\n timeout=30,\n )\n r.raise_for_status()\n return r.json()\n\ntokens = login()\nuser_id = tokens[\"localId\"]\nid_token = tokens[\"idToken\"]\n\n# Paths exactos requieren validar contra repo/docs:\n# food_logs = firestore_get(f\"users/{user_id}/foodLogs\", id_token)\n# weights = firestore_get(f\"users/{user_id}/weights\", id_token)\n```\n\n---\n\n## 2. MyFitnessPal\n\n- **API type:** REST oficial con OAuth2.\n- **Docs:** https://myfitnesspalapi.com/docs/\n- **Auth:** OAuth2 Authorization Code.\n- **Scopes:** `measurements`, `diary`, `private-exercises`, `subscriptions`.\n- **Datos:** diario nutricional, mediciones/peso, ejercicios privados.\n- **Costo:** incierto; parece orientado a partners.\n- **Factibilidad:** **2.5/5**\n\nSkeleton:\n\n```python\nimport os\nfrom authlib.integrations.requests_client import OAuth2Session\n\nCLIENT_ID = os.environ[\"MFP_CLIENT_ID\"]\nCLIENT_SECRET = os.environ[\"MFP_CLIENT_SECRET\"]\nREDIRECT_URI = os.environ[\"MFP_REDIRECT_URI\"]\n\nAUTHORIZE_URL = \"https://api.myfitnesspal.com/v2/oauth2/auth\"\nTOKEN_URL = \"https://api.myfitnesspal.com/v2/oauth2/token\"\nAPI_BASE = \"https://api.myfitnesspal.com/v2\"\n\nSCOPES = [\"diary\", \"measurements\", \"private-exercises\", \"subscriptions\"]\n\ndef build_auth_url():\n client = OAuth2Session(\n CLIENT_ID,\n CLIENT_SECRET,\n scope=\" \".join(SCOPES),\n redirect_uri=REDIRECT_URI,\n )\n return client.create_authorization_url(AUTHORIZE_URL)\n\ndef exchange_code(code: str):\n client = OAuth2Session(\n CLIENT_ID,\n CLIENT_SECRET,\n redirect_uri=REDIRECT_URI,\n )\n return client.fetch_token(TOKEN_URL, code=code)\n\ndef get_diary(token: dict, date: str):\n client = OAuth2Session(CLIENT_ID, CLIENT_SECRET, token=token)\n r = client.get(f\"{API_BASE}/diary\", params={\"date\": date})\n r.raise_for_status()\n return r.json()\n```\n\n---\n\n## 3. Fitbit\n\n- **API type:** REST oficial.\n- **Docs:** https://dev.fitbit.com/build/reference/web-api/\n- **OAuth2:** https://dev.fitbit.com/build/reference/web-api/oauth2/\n- **Datos:** sueño, pasos, calorías, active minutes, HR, resting HR, peso, body fat, food logs.\n- **Auth:** OAuth2 Authorization Code + PKCE.\n- **Costo:** gratis/dev normal, requiere app Fitbit developer.\n- **Factibilidad:** **4.5/5**\n\nSkeleton:\n\n```python\nimport os\nimport base64\nimport hashlib\nimport secrets\nimport httpx\nfrom urllib.parse import urlencode\n\nCLIENT_ID = os.environ[\"FITBIT_CLIENT_ID\"]\nCLIENT_SECRET = os.getenv(\"FITBIT_CLIENT_SECRET\")\nREDIRECT_URI = os.environ[\"FITBIT_REDIRECT_URI\"]\n\nAUTH_URL = \"https://www.fitbit.com/oauth2/authorize\"\nTOKEN_URL = \"https://api.fitbit.com/oauth2/token\"\nAPI_BASE = \"https://api.fitbit.com/1/user/-\"\n\nSCOPES = [\n \"activity\",\n \"heartrate\",\n \"nutrition\",\n \"profile\",\n \"settings\",\n \"sleep\",\n \"weight\",\n]\n\ndef make_pkce():\n verifier = base64.urlsafe_b64encode(secrets.token_bytes(32)).rstrip(b\"=\").decode()\n challenge = base64.urlsafe_b64encode(\n hashlib.sha256(verifier.encode()).digest()\n ).rstrip(b\"=\").decode()\n return verifier, challenge\n\ndef build_auth_url():\n verifier, challenge = make_pkce()\n params = {\n \"client_id\": CLIENT_ID,\n \"response_type\": \"code\",\n \"code_challenge\": challenge,\n \"code_challenge_method\": \"S256\",\n \"scope\": \" \".join(SCOPES),\n \"redirect_uri\": REDIRECT_URI,\n }\n return f\"{AUTH_URL}?{urlencode(params)}\", verifier\n\ndef exchange_code(code: str, code_verifier: str):\n data = {\n \"client_id\": CLIENT_ID,\n \"grant_type\": \"authorization_code\",\n \"code\": code,\n \"code_verifier\": code_verifier,\n \"redirect_uri\": REDIRECT_URI,\n }\n auth = (CLIENT_ID, CLIENT_SECRET) if CLIENT_SECRET else None\n r = httpx.post(TOKEN_URL, data=data, auth=auth, timeout=30)\n r.raise_for_status()\n return r.json()\n\ndef fitbit_get(access_token: str, path: str):\n r = httpx.get(\n f\"{API_BASE}/{path.lstrip('/')}\",\n headers={\"Authorization\": f\"Bearer {access_token}\"},\n timeout=30,\n )\n r.raise_for_status()\n return r.json()\n\ndef get_daily_summary(access_token: str, date: str):\n return fitbit_get(access_token, f\"activities/date/{date}.json\")\n\ndef get_sleep(access_token: str, date: str):\n return fitbit_get(access_token, f\"sleep/date/{date}.json\")\n\ndef get_weight(access_token: str, date: str):\n return fitbit_get(access_token, f\"body/log/weight/date/{date}.json\")\n\ndef get_food(access_token: str, date: str):\n return fitbit_get(access_token, f\"foods/log/date/{date}.json\")\n```\n\n---\n\n## 4. Google Health Connect\n\n- **API type:** Android on-device API.\n- **Docs:** https://developer.android.com/health-and-fitness/guides/health-connect/develop/get-started\n- **Datos:** pasos, distancia, calories, exercise sessions, sleep, weight, HR, resting HR, nutrition, hydration.\n- **Auth:** permisos Android por record type. No OAuth cloud.\n- **Costo:** gratis.\n- **Factibilidad:** **4/5**, pero requiere companion app Android.\n- **Limitación clave:** Hermes en Oracle/no teléfono no puede leer Health Connect directamente.\n\nArquitectura:\n\n```text\nPixel / Android\n Health Connect Bridge App\n lee Health Connect\n normaliza records\n POST HTTPS a Hermes endpoint\n /ingest/health-connect\n```\n\nEndpoint Python en Hermes:\n\n```python\nfrom fastapi import FastAPI, Header, HTTPException\nfrom pydantic import BaseModel\nfrom typing import Any\nimport os\n\napp = FastAPI()\nBRIDGE_TOKEN = os.environ[\"HEALTH_CONNECT_BRIDGE_TOKEN\"]\n\nclass HealthConnectPayload(BaseModel):\n source: str = \"health_connect\"\n device_id: str\n synced_at: str\n data_type: str\n records: list[dict[str, Any]]\n\n@app.post(\"/ingest/health-connect\")\ndef ingest_health_connect(\n payload: HealthConnectPayload,\n authorization: str | None = Header(default=None),\n):\n if authorization != f\"Bearer {BRIDGE_TOKEN}\":\n raise HTTPException(status_code=401, detail=\"unauthorized\")\n\n # TODO: validate schema per data_type and upsert normalized DB.\n return {\"ok\": True, \"received\": len(payload.records)}\n```\n\nKotlin conceptual:\n\n```kotlin\nval permissions = setOf(\n HealthPermission.getReadPermission(StepsRecord::class),\n HealthPermission.getReadPermission(SleepSessionRecord::class),\n HealthPermission.getReadPermission(WeightRecord::class),\n HealthPermission.getReadPermission(HeartRateRecord::class),\n HealthPermission.getReadPermission(NutritionRecord::class),\n)\n\nval healthConnectClient = HealthConnectClient.getOrCreate(context)\n\nsuspend fun readSteps(start: Instant, end: Instant): Long {\n val response = healthConnectClient.aggregate(\n AggregateRequest(\n metrics = setOf(StepsRecord.COUNT_TOTAL),\n timeRangeFilter = TimeRangeFilter.between(start, end)\n )\n )\n return response[StepsRecord.COUNT_TOTAL] ?: 0L\n}\n```\n\n---\n\n## 5. Google Fit\n\n- **API type:** REST legacy.\n- **Docs migración:** https://developer.android.com/health-and-fitness/health-connect/migration/fit\n- **Estado:** deprecándose; Google empuja Health Connect / Google Health API.\n- **Datos:** steps, calories, distance, weight, sessions, sleep según fuentes.\n- **Auth:** Google OAuth2 scopes.\n- **Costo:** gratis.\n- **Factibilidad:** **1.5/5**\n\nRecomendación: **no arrancar integración nueva**. Solo usar si hay datos históricos que migrar/exportar.\n\nSkeleton legacy:\n\n```python\nimport os\nfrom authlib.integrations.requests_client import OAuth2Session\n\nCLIENT_ID = os.environ[\"GOOGLE_CLIENT_ID\"]\nCLIENT_SECRET = os.environ[\"GOOGLE_CLIENT_SECRET\"]\nREDIRECT_URI = os.environ[\"GOOGLE_REDIRECT_URI\"]\n\nAUTH_URL = \"https://accounts.google.com/o/oauth2/v2/auth\"\nTOKEN_URL = \"https://oauth2.googleapis.com/token\"\nFIT_BASE = \"https://www.googleapis.com/fitness/v1/users/me\"\n\nSCOPES = [\n \"https://www.googleapis.com/auth/fitness.activity.read\",\n \"https://www.googleapis.com/auth/fitness.body.read\",\n \"https://www.googleapis.com/auth/fitness.sleep.read\",\n]\n\ndef build_auth_url():\n client = OAuth2Session(\n CLIENT_ID,\n CLIENT_SECRET,\n scope=\" \".join(SCOPES),\n redirect_uri=REDIRECT_URI,\n )\n return client.create_authorization_url(\n AUTH_URL,\n access_type=\"offline\",\n prompt=\"consent\",\n )\n\ndef aggregate_steps(token: dict, start_ms: int, end_ms: int):\n client = OAuth2Session(CLIENT_ID, CLIENT_SECRET, token=token)\n body = {\n \"aggregateBy\": [{\"dataTypeName\": \"com.google.step_count.delta\"}],\n \"bucketByTime\": {\"durationMillis\": 86400000},\n \"startTimeMillis\": start_ms,\n \"endTimeMillis\": end_ms,\n }\n r = client.post(f\"{FIT_BASE}/dataset:aggregate\", json=body)\n r.raise_for_status()\n return r.json()\n```\n\n---\n\n## 6. Cronometer\n\n- **API type:** sin API pública oficial para usuarios individuales.\n- **Pro/API:** http://www.cronometer.com/pro/\n- **MCP reverse-engineered:** https://github.com/cphoskins/cronometer-mcp\n- **Datos:** food logs, macros, micros, biometrics, fasting, diary entries, macro targets.\n- **Auth:** cookies/GWT/mobile reverse-engineered.\n- **Costo:** app/subscription si aplica; API oficial caso por caso.\n- **Factibilidad:** **3/5 personal**, **1.5/5 robusto/oficial**.\n\nSkeleton usando MCP/package:\n\n```python\nfrom datetime import date, timedelta\nfrom cronometer_mcp import CronometerClient\n\ndef main():\n # Requiere validar env vars exactas del paquete.\n client = CronometerClient()\n\n today = date.today()\n start = today - timedelta(days=7)\n\n foods = client.get_food_log()\n print(foods)\n\n # Ejemplos conceptuales:\n # summary = client.get_daily_summary(today)\n # biometrics = client.get_biometrics(start, today)\n\nif __name__ == \"__main__\":\n main()\n```\n\n---\n\n## 7. Hevy\n\n- **API type:** REST oficial.\n- **Docs:** https://api.hevyapp.com/docs/\n- **Auth:** API key header.\n- **Datos:** workouts, workout events, routines, exercise templates, exercise history, body measurements.\n- **Costo:** Hevy Pro.\n- **Factibilidad:** **5/5**\n- **Estado tuyo:** ya conectado, rutinas Min-Max actualizadas en folder `2826578`.\n\nSkeleton:\n\n```python\nimport os\nimport httpx\n\nHEVY_API_KEY = os.environ[\"HEVY_API_KEY\"]\nBASE_URL = \"https://api.hevyapp.com\"\n\nclient = httpx.Client(\n base_url=BASE_URL,\n headers={\"api-key\": HEVY_API_KEY},\n timeout=30,\n)\n\ndef get_user_info():\n r = client.get(\"/v1/user/info\")\n r.raise_for_status()\n return r.json()\n\ndef list_workouts(page: int = 1, page_size: int = 10):\n r = client.get(\n \"/v1/workouts\",\n params={\"page\": page, \"pageSize\": page_size},\n )\n r.raise_for_status()\n return r.json()\n\ndef get_workout(workout_id: str):\n r = client.get(f\"/v1/workouts/{workout_id}\")\n r.raise_for_status()\n return r.json()\n\ndef get_workout_events(since: str, page: int = 1, page_size: int = 100):\n r = client.get(\n \"/v1/workouts/events\",\n params={\"since\": since, \"page\": page, \"pageSize\": page_size},\n )\n r.raise_for_status()\n return r.json()\n\ndef list_body_measurements(page: int = 1, page_size: int = 100):\n r = client.get(\n \"/v1/body_measurements\",\n params={\"page\": page, \"pageSize\": page_size},\n )\n r.raise_for_status()\n return r.json()\n```\n\n---\n\n# Arquitectura recomendada para Pipo\n\n```text\nHermes / Pipo\n |\n v\nhealth-integrations service\n |\n +-- hevy_connector.py\n +-- fitbit_connector.py\n +-- healthconnect_bridge_receiver.py\n +-- macrofactor_connector.py\n +-- cronometer_connector.py\n |\n v\nNormalized Health DB\n |\n +-- nutrition_daily\n +-- body_weight\n +-- activity_daily\n +-- sleep_daily\n +-- workouts\n +-- workout_sets\n +-- readiness_daily\n +-- recommendations\n```\n\nSchema mínimo:\n\n```sql\nCREATE TABLE nutrition_daily (\n source TEXT,\n date DATE,\n calories REAL,\n protein_g REAL,\n carbs_g REAL,\n fat_g REAL,\n fiber_g REAL,\n sodium_mg REAL,\n raw_json JSON,\n PRIMARY KEY (source, date)\n);\n\nCREATE TABLE body_weight (\n source TEXT,\n timestamp TIMESTAMP,\n weight_kg REAL,\n body_fat_pct REAL,\n raw_json JSON,\n PRIMARY KEY (source, timestamp)\n);\n\nCREATE TABLE activity_daily (\n source TEXT,\n date DATE,\n steps INTEGER,\n active_minutes INTEGER,\n calories_out REAL,\n distance_km REAL,\n raw_json JSON,\n PRIMARY KEY (source, date)\n);\n\nCREATE TABLE sleep_daily (\n source TEXT,\n date DATE,\n duration_min INTEGER,\n efficiency REAL,\n deep_min INTEGER,\n rem_min INTEGER,\n light_min INTEGER,\n awake_min INTEGER,\n raw_json JSON,\n PRIMARY KEY (source, date)\n);\n\nCREATE TABLE workouts (\n source TEXT,\n workout_id TEXT,\n started_at TIMESTAMP,\n ended_at TIMESTAMP,\n title TEXT,\n raw_json JSON,\n PRIMARY KEY (source, workout_id)\n);\n\nCREATE TABLE workout_sets (\n source TEXT,\n workout_id TEXT,\n exercise_id TEXT,\n exercise_name TEXT,\n set_index INTEGER,\n reps REAL,\n weight_kg REAL,\n rpe REAL,\n rir REAL,\n raw_json JSON\n);\n```\n\n---\n\n# Implementación por fases\n\n## Fase 1 — base sólida\n\n1. Hevy incremental sync:\n - `/v1/workouts/events`\n - workouts\n - routines\n - exercise history\n - body measurements\n\n2. Fitbit OAuth:\n - sleep\n - steps/activity\n - resting HR\n - weight\n\n3. DB normalizada.\n\n## Fase 2 — nutrición\n\nElegir una:\n\n- **MacroFactor** si querés nutrición + peso/tendencia + coaching serio.\n- **Cronometer** si te importan micros.\n- **Health Connect** si querés Android como hub.\n- **MFP** solo si conseguís API partner o ya estás casado con MFP.\n\nMi recomendación: **MacroFactor + Fitbit + Hevy** primero. Health Connect como bridge después.\n\n## Fase 3 — motor “Very Personal Trainer”\n\nReglas iniciales:\n\n```python\ndef recommend_adjustments(context):\n recommendations = []\n\n if context[\"sleep_7d_avg_hours\"] < 6.5:\n recommendations.append({\n \"type\": \"training\",\n \"action\": \"cap_intensity\",\n \"details\": \"Hoy no buscar PRs. Mantener RIR más conservador en compuestos.\",\n })\n\n if context[\"weight_loss_pct_week\"] > 0.8 and context[\"performance_down\"]:\n recommendations.append({\n \"type\": \"nutrition\",\n \"action\": \"increase_calories\",\n \"details\": \"Subir 150-250 kcal/día, preferentemente carbs alrededor del entrenamiento.\",\n })\n\n if context[\"protein_g_per_kg\"] < 1.6:\n recommendations.append({\n \"type\": \"nutrition\",\n \"action\": \"increase_protein\",\n \"details\": \"Agregar una porción de proteína magra o whey.\",\n })\n\n if context[\"steps_7d_avg\"] > 12000 and context[\"next_session\"] == \"Lower\":\n recommendations.append({\n \"type\": \"training\",\n \"action\": \"protect_lower_body\",\n \"details\": \"Mantener cargas, evitar failure real en Lower si piernas vienen cargadas.\",\n })\n\n return recommendations\n```\n\n## Veredicto corto\n\nPara tu caso real:\n\n1. **Hevy** ya está.\n2. Próximo mejor paso: **Fitbit Web API** si tenés fuente Fitbit/Pixel Watch/Fitbit app.\n3. Nutrición: **MacroFactor** es probablemente la mejor fuente si aceptás reverse-engineered.\n4. Health Connect vale mucho, pero implica construir **app Android bridge**.\n5. Google Fit no lo tocaría salvo migración histórica.\n6. Cronometer es útil si querés micronutrientes, pero más frágil.\n7. MyFitnessPal depende de acceso partner; no lo pondría como camino principal."
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