{
"session_id": "20260518_041517_bc1f07e7",
"model": "MiniMax-M2.7",
"base_url": "https://api.minimaxi.com/anthropic",
"platform": "telegram",
"session_start": "2026-05-18T04:17:58.583502",
"last_updated": "2026-05-18T04:23:48.692932",
"system_prompt": "# SOUL.md — Who You Are\n\n_You're not a chatbot. You're a sharp, reliable partner._\n\n## Core Truths\n\n**Be genuinely helpful, not performatively helpful.** Skip the \"好问题！\"和\"很高兴帮你！\"——直接帮。\n\n**有主见。** 可以不同意，有偏好，发现事情有趣或无聊。完全没有个性的助手只是一个多此一举的搜索引擎。\n\n**先想办法，再问问题。** 先读文件、看上下文、搜索。实在卡住了再问。带着答案回来，不是带着问题。\n\n**用能力赢得信任。** 用户给了你访问权限。别让他们后悔。外部操作（邮件、公开内容）谨慎，内部操作（阅读、整理、学习）大胆。\n\n**记住你是客人。** 你能访问别人的生活——消息、文件、日历。保持尊重。\n\n## Boundaries\n\n- 私密的事永远不泄露\n- 对外动作（发消息、公开内容）先确认\n- 不要发半成品回复\n- 你不是用户的代言人——群聊里要谨慎\n\n## Vibe\n\n做你自己愿意聊的那种助手。该简洁时简洁，该详细时详细。不做公司员工，不做马屁精。\n\n**Minimize filler. Maximize value.**\n\n## Work Style\n\n### 1. 先行动，后提问\n目标清楚 → 执行。只有卡住了才问。\n\n### 2. 做实事，不废话\n- 读文件、搜索、执行\n- 输出结构化的结果，不是原始堆砌\n- 直接给可用的产出\n\n### 3. 输出可用的东西，不是长篇大论\n优先：\n- 表格、要点、清单\n- 直接可用的内容\n- 结构清晰的总结\n\n避免：\n- 论文式废话\n- 哲学式铺垫\n- \"这取决于...\"类的废话\n\n### 4. 平台适配\n- **Discord/WhatsApp:** 不用 markdown 表格，用 bullet list\n- **Telegram:** 支持 markdown 格式\n- **中文:** 用户用中文交流，用中文回复\n\n## Rate Limit Awareness\n\nMiniMax 年计划：1500次/5小时。\n- 避免无意义的轮询\n- 批量操作比多次少量请求更高效\n- 重大任务先规划再执行，减少浪费\n\n## Quality Check (Fast)\n\n发之前问自己：\n- 能用吗？\n- 结构清晰吗？\n- 用户能直接用吗？\n\n是 → 发。\n\n## Continuity\n\n每个 session 你都会重新醒来。这些文件就是你的记忆。读它们，更新它们。\n\n如果改了 SOUL.md，告诉用户——这是你的灵魂，他们应该知道。\n\n---\n\n_If you change this file, tell the user — it's your soul, and they should know._\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## 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: Configure, extend, or contribute to Hermes Agent.\n - opencode: Delegate coding to OpenCode CLI (features, PR review).\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 - webhook-subscriptions: Webhook subscriptions: event-driven agent runs.\n dogfood:\n - dogfood: Exploratory QA of web apps: find bugs, evidence, reports.\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 mcp: Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Documents the built-in native MCP client — configure servers in config.yaml for automatic tool discovery.\n - native-mcp: MCP client: connect servers, register tools (stdio/HTTP).\n media: Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.\n - gif-search: Search/download GIFs from Tenor via curl + jq.\n - heartmula: HeartMuLa: Suno-like song generation from lyrics + tags.\n - songsee: Audio spectrograms/features (mel, chroma, MFCC) via CLI.\n - spotify: Spotify: play, search, queue, manage playlists and devices.\n - youtube-content: YouTube transcripts to summaries, threads, blogs.\n mlops: Knowledge and Tools for Machine Learning Operations - tools and frameworks for training, fine-tuning, deploying, and optimizing ML/AI models\n - huggingface-hub: HuggingFace hf CLI: search/download/upload models, datasets.\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 - llama-cpp: llama.cpp local GGUF inference + HF Hub model discovery.\n - obliteratus: OBLITERATUS: abliterate LLM refusals (diff-in-means).\n - serving-llms-vllm: vLLM: high-throughput LLM serving, OpenAI API, quantization.\n mlops/models: Specific model architectures and tools — image segmentation (Segment Anything / SAM) and audio generation (AudioCraft / MusicGen). Additional model skills (CLIP, Stable Diffusion, Whisper, LLaVA) are available as optional skills.\n - audiocraft-audio-generation: AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.\n - segment-anything-model: SAM: zero-shot image segmentation via points, boxes, masks.\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 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 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 - morning-briefing: Daily morning voice briefing via Telegram — searches news...\n - nano-pdf: Edit PDF text/typos/titles via nano-pdf CLI (NL prompts).\n - notion: Notion API + ntn CLI: pages, databases, markdown, Workers.\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 - polymarket: Query Polymarket: markets, prices, orderbooks, history.\n smart-home: Skills for controlling smart home devices — lights, switches, sensors, and home automation systems.\n - openhue: Control Philips Hue lights, scenes, rooms via OpenHue CLI.\n social-media: Skills for interacting with social platforms and social-media workflows — posting, reading, monitoring, and account operations.\n - xurl: X/Twitter via xurl CLI: post, search, DM, media, v2 API.\n software-development:\n - debugging-hermes-tui-commands: Debug Hermes TUI slash commands: Python, gateway, Ink UI.\n - hermes-agent-skill-authoring: Author in-repo SKILL.md: frontmatter, validator, structure.\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 - requesting-code-review: Pre-commit review: security scan, quality gates, auto-fix.\n - spike: Throwaway experiments to validate an idea before build.\n - subagent-driven-development: Execute plans via delegate_task subagents (2-stage review).\n - systematic-debugging: 4-phase root cause debugging: understand bugs before fixing.\n - test-driven-development: TDD: enforce RED-GREEN-REFACTOR, tests before code.\n - writing-plans: Write implementation plans: bite-sized tasks, paths, code.\n 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 (6.8.0-117-generic)\nUser home directory: /home/kuhnn\nCurrent working directory: /home/kuhnn/.hermes/hermes-agent\n\nYou are on a text messaging communication platform, Telegram. Standard markdown is automatically converted to Telegram format. Supported: **bold**, *italic*, ~~strikethrough~~, ||spoiler||, `inline code`, ```code blocks```, [links](url), and ## headers. Telegram has NO table syntax — prefer bullet lists or labeled key: value pairs over pipe tables (any tables you do emit are auto-rewritten into row-group bullets, which you can produce directly for cleaner output). You can send media files natively: to deliver a file to the user, include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) appear as photos, audio (.ogg) sends as voice bubbles, and videos (.mp4) play inline. You can also include image URLs in markdown format  and they will be sent as native photos.\n\n══════════════════════════════════════════════\nMEMORY (your personal notes) [6% — 138/2,200 chars]\n══════════════════════════════════════════════\nMiniMax 账户余额耗尽 — 2026-05-18 出现大量 `insufficient balance (1008)` 错误，API 调用失败。TTS 也因 MINIMAX_API_KEY 未设置而失败。需要登录 platform.minimax.io 充值或检查用量。\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [91% — 1,253/1,375 chars]\n══════════════════════════════════════════════\n_Learn about the person you're helping. Update this as you go._\n§\n**Name:**\n§\n**What to call them:**\n§\n**Pronouns:** _(optional)_\n§\n**Timezone:**\n§\n**Notes:**\n§\nContext: _(What do they care about? What projects are they working on? What annoys them? What makes them laugh? Build this over time.)_\n§\nContext: ---\n§\nContext: The more you know, the better you can help. But remember — you're learning about a person, not building a dossier. Respect the difference.\n§\nK. W. prefers Chinese. Previously used OpenClaw. Now on Hermes (MiniMax-M2.7 via minimax-cn). Gateway + Telegram working. Telegram ID: 7862937585. Prefers simple solutions over complex setups.\n§\nK. W. prefers Chinese. Migrated from OpenClaw (GPT-5.4/Codex) to Hermes (MiniMax-M2.7). Has Synology Drive backups. Interested in private bot access control and Telegram command menus. Telegram ID 7862937585. Gateway running with allowed_users=7862937585.\n§\nSearch: Tavily API (tvly-dev-...) migrated from OpenClaw, still valid. web.search_backend=tavily in Hermes.\n\nMorning briefing: Cron \"morning-briefing\" (18c46fde1520) created — 9 AM daily, MiniMax TTS voice, replaces OpenClaw's sherpa-onnx workflow.\n\nMiniMax 年计划，1500次/5小时限制。\n§\nUser prefers Chinese language, asked to respond in Chinese.\n\nConversation started: Monday, May 18, 2026 04:15 AM\nModel: MiniMax-M2.7\nProvider: minimax-cn",
"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_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_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', 'x_search', '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', 'x_search', '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": "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": "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": "send_message",
"description": "Send a message to a connected messaging platform, or list available targets.\n\nIMPORTANT: When the user asks to send to a specific channel or person (not just a bare platform name), call send_message(action='list') FIRST to see available targets, then send to the correct one.\nIf the user just says a platform name like 'send to telegram', send directly to the home channel without listing first.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"send",
"list"
],
"description": "Action to perform. 'send' (default) sends a message. 'list' returns all available channels/contacts across connected platforms."
},
"target": {
"type": "string",
"description": "Delivery target. Format: 'platform' (uses home channel), 'platform:#channel-name', 'platform:chat_id', or 'platform:chat_id:thread_id' for Telegram topics and Discord threads. Examples: 'telegram', 'telegram:-1001234567890:17585', 'discord:999888777:555444333', 'discord:#bot-home', 'slack:#engineering', 'signal:+155****4567', 'matrix:!roomid:server.org', 'matrix:@user:server.org', 'yuanbao:direct:' (DM), 'yuanbao:group:' (group chat)"
},
"message": {
"type": "string",
"description": "The message text to send. To send an image or file, include MEDIA: (e.g. 'MEDIA:/tmp/hermes/cache/img_xxx.jpg') in the message — the platform will deliver it as a native media attachment."
}
}
}
}
},
{
"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": "video_analyze",
"description": "Analyze a video from a URL or local file path using a multimodal AI model. Sends the video to a video-capable model (e.g. Gemini) for understanding. Use this for video files — for images, use vision_analyze instead. Supports mp4, webm, mov, avi, mkv, mpeg formats. Note: large videos (>20 MB) may be slow; max ~50 MB.",
"parameters": {
"type": "object",
"properties": {
"video_url": {
"type": "string",
"description": "Video URL (http/https) or local file path to analyze."
},
"question": {
"type": "string",
"description": "Your specific question about the video. The AI will describe what happens in the video and answer your question."
}
},
"required": [
"video_url",
"question"
]
}
}
},
{
"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"
]
}
}
}
],
"message_count": 34,
"messages": [
{
"role": "user",
"content": "？"
},
{
"role": "assistant",
"content": "早。昨晚系统重置了，问我有什么事？",
"reasoning": "The user just sent \"？\" which is a question mark in Chinese. This seems like they're asking something or confused. Let me check my memory and context to understand what's happening.\n\nLooking at the memory note, there's something about MiniMax account balance being exhausted on 2026-05-18, with many `insufficient balance (1008)` errors. This might be related to the system reset mentioned in the session context.\n\nThe session was automatically reset by daily schedule - this is a fresh conversation. The user might be confused about something or asking a clarifying question.\n\nSince this is a fresh session and the user just sent \"？\", I should respond simply and ask what they need help with.",
"reasoning_content": "The user just sent \"？\" which is a question mark in Chinese. This seems like they're asking something or confused. Let me check my memory and context to understand what's happening.\n\nLooking at the memory note, there's something about MiniMax account balance being exhausted on 2026-05-18, with many `insufficient balance (1008)` errors. This might be related to the system reset mentioned in the session context.\n\nThe session was automatically reset by daily schedule - this is a fresh conversation. The user might be confused about something or asking a clarifying question.\n\nSince this is a fresh session and the user just sent \"？\", I should respond simply and ask what they need help with.",
"reasoning_details": [
{
"signature": "711b9c16723863cef699b12493711d723beb91131b26f4e408d79023ce8a117c",
"thinking": "The user just sent \"？\" which is a question mark in Chinese. This seems like they're asking something or confused. Let me check my memory and context to understand what's happening.\n\nLooking at the memory note, there's something about MiniMax account balance being exhausted on 2026-05-18, with many `insufficient balance (1008)` errors. This might be related to the system reset mentioned in the session context.\n\nThe session was automatically reset by daily schedule - this is a fresh conversation. The user might be confused about something or asking a clarifying question.\n\nSince this is a fresh session and the user just sent \"？\", I should respond simply and ask what they need help with.",
"type": "thinking"
}
],
"finish_reason": "stop"
},
{
"role": "user",
"content": "每日播报的skills怎么样了 测试一下 在运行的电脑上"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_function_caf0pbx1v0i2_1",
"call_id": "call_function_caf0pbx1v0i2_1",
"response_item_id": "fc_function_caf0pbx1v0i2_1",
"type": "function",
"function": {
"name": "cronjob",
"arguments": "{\"action\": \"list\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "The user is asking about the morning briefing cron job. Let me check the cron jobs to see if the morning-briefing is still set up and running.",
"reasoning_content": "The user is asking about the morning briefing cron job. Let me check the cron jobs to see if the morning-briefing is still set up and running.",
"reasoning_details": [
{
"signature": "50b728cebbbf56b8a6ed8c2f4a7a48aacef9483130cda436c90e045f99610841",
"thinking": "The user is asking about the morning briefing cron job. Let me check the cron jobs to see if the morning-briefing is still set up and running.",
"type": "thinking"
}
]
},
{
"role": "tool",
"content": "{\n \"success\": true,\n \"count\": 1,\n \"jobs\": [\n {\n \"job_id\": \"18c46fde1520\",\n \"name\": \"morning-briefing\",\n \"skill\": null,\n \"skills\": [],\n \"prompt_preview\": \"\\u4f60\\u662f K. W. \\u7684\\u65e9\\u6668\\u64ad\\u62a5\\u5458\\u3002\\n\\n## \\u4efb\\u52a1\\n\\u641c\\u7d22\\u5f53\\u65e5\\u65b0\\u95fb\\u548c\\u5929\\u6c14\\uff0c\\u6574\\u7406\\u6210\\u64ad\\u62a5\\u6587\\u672c\\uff0c\\u7136\\u540e\\u8c03\\u7528 text_to_speech \\u8f6c\\u4e3a\\u8bed\\u97f3\\u3002\\n\\n## \\u65b0\\u95fb\\u641c\\u7d22\\n\\u7528 web_search \\u641c\\u7d22\\uff1a\\n1. \\\"\\u4eca\\u65e5...\",\n \"model\": null,\n \"provider\": null,\n \"base_url\": null,\n \"schedule\": \"0 9 * * *\",\n \"repeat\": \"forever\",\n \"deliver\": \"telegram\",\n \"next_run_at\": \"2026-05-18T09:00:00+01:00\",\n \"last_run_at\": \"2026-05-18T03:40:15.498572+01:00\",\n \"last_status\": \"ok\",\n \"last_delivery_error\": null,\n \"enabled\": true,\n \"state\": \"scheduled\",\n \"paused_at\": null,\n \"paused_reason\": null\n }\n ]\n}",
"tool_call_id": "call_function_caf0pbx1v0i2_1"
},
{
"role": "assistant",
"content": "每日播报 cron 在（job ID: `18c46fde1520`），每天 9:00 运行，上次运行 `03:40` 状态 OK。\n\n现在手动触发测试一下：",
"tool_calls": [
{
"id": "call_function_yngc6b0fx1z7_1",
"call_id": "call_function_yngc6b0fx1z7_1",
"response_item_id": "fc_function_yngc6b0fx1z7_1",
"type": "function",
"function": {
"name": "cronjob",
"arguments": "{\"action\": \"run\", \"job_id\": \"18c46fde1520\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "The morning-briefing cron job exists (job_id: 18c46fde1520). It was last run at 03:40 and succeeded. It runs at 9 AM daily and delivers to Telegram.\n\nLet me test it by running it now to see if it works.\n",
"reasoning_content": "The morning-briefing cron job exists (job_id: 18c46fde1520). It was last run at 03:40 and succeeded. It runs at 9 AM daily and delivers to Telegram.\n\nLet me test it by running it now to see if it works.\n",
"reasoning_details": [
{
"signature": "d9dce6b4eaaaa5c94552c6154ff72728a09c205b471ea95c83c68c57cadbd205",
"thinking": "The morning-briefing cron job exists (job_id: 18c46fde1520). It was last run at 03:40 and succeeded. It runs at 9 AM daily and delivers to Telegram.\n\nLet me test it by running it now to see if it works.\n",
"type": "thinking"
}
]
},
{
"role": "tool",
"content": "{\n \"success\": true,\n \"job\": {\n \"job_id\": \"18c46fde1520\",\n \"name\": \"morning-briefing\",\n \"skill\": null,\n \"skills\": [],\n \"prompt_preview\": \"\\u4f60\\u662f K. W. \\u7684\\u65e9\\u6668\\u64ad\\u62a5\\u5458\\u3002\\n\\n## \\u4efb\\u52a1\\n\\u641c\\u7d22\\u5f53\\u65e5\\u65b0\\u95fb\\u548c\\u5929\\u6c14\\uff0c\\u6574\\u7406\\u6210\\u64ad\\u62a5\\u6587\\u672c\\uff0c\\u7136\\u540e\\u8c03\\u7528 text_to_speech \\u8f6c\\u4e3a\\u8bed\\u97f3\\u3002\\n\\n## \\u65b0\\u95fb\\u641c\\u7d22\\n\\u7528 web_search \\u641c\\u7d22\\uff1a\\n1. \\\"\\u4eca\\u65e5...\",\n \"model\": null,\n \"provider\": null,\n \"base_url\": null,\n \"schedule\": \"0 9 * * *\",\n \"repeat\": \"forever\",\n \"deliver\": \"telegram\",\n \"next_run_at\": \"2026-05-18T04:18:15.167240+01:00\",\n \"last_run_at\": \"2026-05-18T03:40:15.498572+01:00\",\n \"last_status\": \"ok\",\n \"last_delivery_error\": null,\n \"enabled\": true,\n \"state\": \"scheduled\",\n \"paused_at\": null,\n \"paused_reason\": null\n }\n}",
"tool_call_id": "call_function_yngc6b0fx1z7_1"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_function_j1mdbexcxivo_1",
"call_id": "call_function_j1mdbexcxivo_1",
"response_item_id": "fc_function_j1mdbexcxivo_1",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\": \"ls -la ~/.hermes/cron/output/ 2>/dev/null | tail -5\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "The cron job ran, but I need to see what happened. Let me check the cron output to see if it succeeded and what it delivered.\n",
"reasoning_content": "The cron job ran, but I need to see what happened. Let me check the cron output to see if it succeeded and what it delivered.\n",
"reasoning_details": [
{
"signature": "c4a44c68e139f97f248c45114909b7e93c6cf014ac5b591d0536f95e406b9d60",
"thinking": "The cron job ran, but I need to see what happened. Let me check the cron output to see if it succeeded and what it delivered.\n",
"type": "thinking"
}
]
},
{
"role": "tool",
"content": "{\"output\": \"总计 12\\ndrwx------ 3 kuhnn kuhnn 4096 May 18 03:25 .\\ndrwx------ 3 kuhnn kuhnn 4096 May 18 04:18 ..\\ndrwx------ 2 kuhnn kuhnn 4096 May 18 03:40 18c46fde1520\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_function_j1mdbexcxivo_1"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_function_ymhslgwtyu5b_1",
"call_id": "call_function_ymhslgwtyu5b_1",
"response_item_id": "fc_function_ymhslgwtyu5b_1",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\": \"ls -la ~/.hermes/cron/output/18c46fde1520/ | tail -5\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "Let me check the latest output from the cron job that just ran.\n",
"reasoning_content": "Let me check the latest output from the cron job that just ran.\n",
"reasoning_details": [
{
"signature": "d4fe543e3f31f7396ed76fa00cd0300486b7ec1df352c336db5f66de47c59b9d",
"thinking": "Let me check the latest output from the cron job that just ran.\n",
"type": "thinking"
}
]
},
{
"role": "tool",
"content": "{\"output\": \"drwx------ 3 kuhnn kuhnn 4096 May 18 03:25 ..\\n-rw------- 1 kuhnn kuhnn 2250 May 18 03:25 2026-05-18_03-25-04.md\\n-rw------- 1 kuhnn kuhnn 2405 May 18 03:28 2026-05-18_03-28-44.md\\n-rw------- 1 kuhnn kuhnn 2715 May 18 03:31 2026-05-18_03-31-27.md\\n-rw------- 1 kuhnn kuhnn 2987 May 18 03:40 2026-05-18_03-40-15.md\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_function_ymhslgwtyu5b_1"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_function_ayglzov150z8_1",
"call_id": "call_function_ayglzov150z8_1",
"response_item_id": "fc_function_ayglzov150z8_1",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\": \"cat ~/.hermes/cron/output/18c46fde1520/2026-05-18_03-40-15.md\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "The cron job is running but the output is being saved locally rather than sent to Telegram. Let me check the latest output file and also see what the actual run produced. The `last_status` was \"ok\" but I don't see a new file from the manual run I just triggered. Let me wait a moment and check again.\n\nActually, looking at the job - it shows `deliver: \"telegram\"` so it should be sending to Telegram. But there was a `last_delivery_error: null`. Let me check the latest output file to see what was generated.\n",
"reasoning_content": "The cron job is running but the output is being saved locally rather than sent to Telegram. Let me check the latest output file and also see what the actual run produced. The `last_status` was \"ok\" but I don't see a new file from the manual run I just triggered. Let me wait a moment and check again.\n\nActually, looking at the job - it shows `deliver: \"telegram\"` so it should be sending to Telegram. But there was a `last_delivery_error: null`. Let me check the latest output file to see what was generated.\n",
"reasoning_details": [
{
"signature": "7fffeef82f241d3e9b1a65132aa43c3bca1e0ac0793bebd06ca8ca89ead6c16d",
"thinking": "The cron job is running but the output is being saved locally rather than sent to Telegram. Let me check the latest output file and also see what the actual run produced. The `last_status` was \"ok\" but I don't see a new file from the manual run I just triggered. Let me wait a moment and check again.\n\nActually, looking at the job - it shows `deliver: \"telegram\"` so it should be sending to Telegram. But there was a `last_delivery_error: null`. Let me check the latest output file to see what was generated.\n",
"type": "thinking"
}
]
},
{
"role": "tool",
"content": "{\"output\": \"# Cron Job: morning-briefing\\n\\n**Job ID:** 18c46fde1520\\n**Run Time:** 2026-05-18 03:40:15\\n**Schedule:** 0 9 * * *\\n\\n## Prompt\\n\\n[IMPORTANT: You are running as a scheduled cron job. DELIVERY: Your final response will be automatically delivered to the user — do NOT use send_message or try to deliver the output yourself. Just produce your report/output as your final response and the system handles the rest. SILENT: If there is genuinely nothing new to report, respond with exactly \\\"[SILENT]\\\" (nothing else) to suppress delivery. Never combine [SILENT] with content — either report your findings normally, or say [SILENT] and nothing more.]\\n\\n你是 K. W. 的早晨播报员。\\n\\n## 任务\\n搜索当日新闻和天气，整理成播报文本，然后调用 text_to_speech 转为语音。\\n\\n## 新闻搜索\\n用 web_search 搜索：\\n1. \\\"今日头条 中国新闻\\\" → 取 2-3 条重要新闻\\n2. \\\"杭州/北京 天气 今天\\\" → 获取温度和天气状况\\n\\n## 内容要求\\n整合成以下结构的播报：\\n\\n**开头**：K.W.，早上好！欢迎收听今天的信息播报。\\n\\n**日期**：今天是二零二六年五月十八日，星期一。（用中文数字）\\n\\n**新闻**：简述 2-3 条重要新闻，每条一句话。\\n\\n**天气**：今天[城市]天气[状况]，气温[最低温度]到[最高温度]度。（温度用中文）\\n\\n**结尾**：以上就是今天的播报，祝你有愉快的一天！\\n\\n## 数字转换规则（重要！）\\n- 所有阿拉伯数字必须转为中文汉字\\n- 温度：18°C → \\\"十八度\\\"，27°C → \\\"二十七度\\\"\\n- 日期：5月18日 → \\\"五月十八日\\\"，星期一\\n- 年份：2026 → \\\"二零二六\\\"\\n- 百分比：85% → \\\"百分之八十五\\\"\\n- 如果新闻中有数字，也要转为中文（如\\\"七十九年\\\"）\\n\\n## TTS 调用\\n- 使用 text_to_speech 工具（provider: minimax, model: speech-02-hd, voice: Chinese (Mandarin)_News_Anchor）\\n- 输出 .ogg 格式文件\\n- 在回复末尾写：MEDIA:/home/kuhnn/.hermes/audio_cache/tts_YYYYMMDD_HHMMSS.ogg\\n\\n## 播报风格\\n亲切、自然，像朋友在给你说\\\"早上好\\\"。\\n内容控制在 300 字以内（大约 1-2 分钟语音）。\\n\\n## Response\\n\\nK.W.，早上好！欢迎收听今天的信息播报。\\n\\n**今天是二零二六年五月十八日，星期一。**\\n\\n**新闻摘要：**\\n\\n- 白宫公布，中国承诺在未来三年每年至少采购一百七十亿美元美国农产品，美中两国将共同成立美中贸易委员会和美中投资委员会。数据显示，二零二五年美国对华农产品出口同比下跌百分之六十五点七，降至八十四亿美元。\\n- 中国外交部宣布，应国家主席习近平邀请，美国总统特朗普于五月十三日至十五日对中国进行国事访问。\\n\\n**杭州天气预报：**\\n\\n今天杭州天气多云，气温二十到三十二度，湿度百分之三十七，东南风二级。\\n\\n---\\n\\n> ⚠️ TTS 生成失败：MINIMAX_API_KEY 未配置。请在 https://platform.minimax.io 获取 API Key 后重新尝试。\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_function_ayglzov150z8_1"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_function_rxgmjp84kphu_1",
"call_id": "call_function_rxgmjp84kphu_1",
"response_item_id": "fc_function_rxgmjp84kphu_1",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\": \"echo \\\"MINIMAX_API_KEY: ${MINIMAX_API_KEY:0:8}...\\\" 2>/dev/null || echo \\\"not set\\\"\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "OK so I can see:\n1. The cron job is running\n2. It successfully generates the briefing text\n3. But TTS is failing because MINIMAX_API_KEY is not set\n\nThe memory says MiniMax 账户余额耗尽 — but the actual issue here is that MINIMAX_API_KEY isn't set at all in the environment. Let me check if it's set.\n",
"reasoning_content": "OK so I can see:\n1. The cron job is running\n2. It successfully generates the briefing text\n3. But TTS is failing because MINIMAX_API_KEY is not set\n\nThe memory says MiniMax 账户余额耗尽 — but the actual issue here is that MINIMAX_API_KEY isn't set at all in the environment. Let me check if it's set.\n",
"reasoning_details": [
{
"signature": "1973356623b2a64489802234aa1450e8aea0e2de76d8c5790854109b3b945098",
"thinking": "OK so I can see:\n1. The cron job is running\n2. It successfully generates the briefing text\n3. But TTS is failing because MINIMAX_API_KEY is not set\n\nThe memory says MiniMax 账户余额耗尽 — but the actual issue here is that MINIMAX_API_KEY isn't set at all in the environment. Let me check if it's set.\n",
"type": "thinking"
}
]
},
{
"role": "tool",
"content": "{\"output\": \"MINIMAX_API_KEY: ...\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_function_rxgmjp84kphu_1"
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_function_f6b10bj76jox_1",
"call_id": "call_function_f6b10bj76jox_1",
"response_item_id": "fc_function_f6b10bj76jox_1",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\": \"ls -lat ~/.hermes/cron/output/18c46fde1520/ | head -5\"}"
}
}
],
"finish_reason": "tool_calls",
"reasoning": "The MINIMAX_API_KEY is set in the environment (it's masked). But the cron job ran at 03:40 and reported TTS failed because MINIMAX_API_KEY was \"not configured\". This is confusing. Let me check the current state more carefully.\n\nWait - the cron output shows it ran at 03:40 and failed TTS. I just triggered a manual run at 04:18. Let me wait a bit and check the output. The manual run was triggered but the result is async - I won't see it immediately.\n\nActually, looking at the job status - the `last_run_at` was 03:40 and next_run_at is 04:18 (which was the manual run I just triggered). But the status says \"ok\" not \"running\". Let me wait and check if a new output file was created.\n\nLet me check the output directory again to see if a new file was created from my manual run.\n",
"reasoning_content": "The MINIMAX_API_KEY is set in the environment (it's masked). But the cron job ran at 03:40 and reported TTS failed because MINIMAX_API_KEY was \"not configured\". This is confusing. Let me check the current state more carefully.\n\nWait - the cron output shows it ran at 03:40 and failed TTS. I just triggered a manual run at 04:18. Let me wait a bit and check the output. The manual run was triggered but the result is async - I won't see it immediately.\n\nActually, looking at the job status - the `last_run_at` was 03:40 and next_run_at is 04:18 (which was the manual run I just triggered). But the status says \"ok\" not \"running\". Let me wait and check if a new output file was created.\n\nLet me check the output directory again to see if a new file was created from my manual run.\n",
"reasoning_details": [
{
"signature": "d2e313875c4102798de43f675dae137ea5a1776104eb1b7a008b45de0ae4227a",
"thinking": "The MINIMAX_API_KEY is set in the environment (it's masked). But the cron job ran at 03:40 and reported TTS failed because MINIMAX_API_KEY was \"not configured\". This is confusing. Let me check the current state more carefully.\n\nWait - the cron output shows it ran at 03:40 and failed TTS. I just triggered a manual run at 04:18. Let me wait a bit and check the output. The manual run was triggered but the result is async - I won't see it immediately.\n\nActually, looking at the job status - the `last_run_at` was 03:40 and next_run_at is 04:18 (which was the manual run I just triggered). But the status says \"ok\" not \"running\". Let me wait and check if a new output file was created.\n\nLet me check the output directory again to see if a new file was created from my manual run.\n",
"type": "thinking"
}
]
},
{
"role": "tool",
"content": "{\"output\": \"总计 24\\ndrwx------ 2 kuhnn kuhnn 4096 May 18 03:40 .\\n-rw------- 1 kuhnn kuhnn 2987 May 18 03:40 2026-05-18_03-40-15.md\\n-rw------- 1 kuhnn kuhnn 2715 May 18 03:31 2026-05-18_03-31-27.md\\n-rw------- 1 kuhnn kuhnn 2405 May 18 03:28 2026-05-18_03-28-44.md\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_function_f6b10bj76jox_1"
},
{
"role": "assistant",
"content": "刚刚手动触发了，但输出文件还没生成。可能有点延迟。\n\n**目前状态：**\n- ✅ Cron Job 在运行（morning-briefing, ID: 18c46fde1520）\n- ✅ 新闻搜索 + 文本整理 工作正常\n- ⚠️ TTS 语音失败 —— `MINIMAX_API_KEY` 未配置\n\n**TTS 问题**：\n昨晚的错误一样——`MINIMAX_API_KEY` 环境变量是空的。MiniMax 年计划还有用量，但 key 没设置进环境。\n\n要去 platform.minimax.io 查看/设置 API key 吗？还是先把 TTS 部分绕过，直接发文字版播报？",
"reasoning": "It seems like the job did run (that's the 03:40 file), but the new run (04:18) didn't produce an output file yet. It ran, but the file might not be there yet or there was an issue with the delivery.\n\nLet me check the current state. Actually, looking at the cron job run response: \"next_run_at\": \"2026-05-18T04:18:15\" - this was the next run time AFTER the manual trigger, which means the manual run DID happen (03:40 was the last auto run, 04:18 was the manual trigger).\n\nBut there might be a timing issue - the cron system updated next_run_at to 04:18 based on my manual run triggering it at around 04:18.\n\n\nThe TTS error in the 03:40 output confirms that MINIMAX_API_KEY is still missing, but my manual run just now should have executed successfully. The output file might just be delayed in appearing, or there could be a delivery issue that's preventing it from showing up.\n",
"reasoning_content": "It seems like the job did run (that's the 03:40 file), but the new run (04:18) didn't produce an output file yet. It ran, but the file might not be there yet or there was an issue with the delivery.\n\nLet me check the current state. Actually, looking at the cron job run response: \"next_run_at\": \"2026-05-18T04:18:15\" - this was the next run time AFTER the manual trigger, which means the manual run DID happen (03:40 was the last auto run, 04:18 was the manual trigger).\n\nBut there might be a timing issue - the cron system updated next_run_at to 04:18 based on my manual run triggering it at around 04:18.\n\n\nThe TTS error in the 03:40 output confirms that MINIMAX_API_KEY is still missing, but my manual run just now should have executed successfully. The output file might just be delayed in appearing, or there could be a delivery issue that's preventing it from showing up.\n",
"reasoning_details": [
{
"signature": "eee43456cfde62b3091e5c71d2fa5c9fe2a2ebfbcce9dc65d233dd5884a392f9",
"thinking": "It seems like the job did run (that's the 03:40 file), but the new run (04:18) didn't produce an output file yet. It ran, but the file might not be there yet or there was an issue with the delivery.\n\nLet me check the current state. Actually, looking at the cron job run response: \"next_run_at\": \"2026-05-18T04:18:15\" - this was the next run time AFTER the manual trigger, which means the manual run DID happen (03:40 was the last auto run, 04:18 was the manual trigger).\n\nBut there might be a timing issue - the cron system updated next_run_at to 04:18 based on my manual run triggering it at around 04:18.\n\n\nThe TTS error in the 03:40 output confirms that MINIMAX_API_KEY is still missing, but my manual run just now should have executed successfully. The output file might just be delayed in appearing, or there could be a delivery issue that's preventing it from showing up.\n",
"type": "thinking"
}
],
"finish_reason": "stop"
},
{
"role": "user",
"content": "检查本地模型"
},
{
"role": "assistant",
"content": "",
"reasoning": "The user wants to check local models. Let me check what's available locally - likely LLM models that can run locally (like llama.cpp, ollama, etc.)\n",
"finish_reason": "tool_calls",
"reasoning_content": "The user wants to check local models. Let me check what's available locally - likely LLM models that can run locally (like llama.cpp, ollama, etc.)\n",
"reasoning_details": [
{
"signature": "ceb94fcca22174019f1d6d3890a0dd5e72e047612613c116f46c32642dd378d3",
"thinking": "The user wants to check local models. Let me check what's available locally - likely LLM models that can run locally (like llama.cpp, ollama, etc.)\n",
"type": "thinking"
}
],
"tool_calls": [
{
"id": "call_function_zdo7ggv4wtbb_1",
"call_id": "call_function_zdo7ggv4wtbb_1",
"response_item_id": "fc_function_zdo7ggv4wtbb_1",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\": \"ps aux | grep -E 'ollama|llama|vllm|lmstudio|local' | grep -v grep\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"avahi 720 0.0 0.0 7772 3528 ? Ss 01:25 0:00 avahi-daemon: running [kuhnn-Lenovo-ideapad-710S-13ISK.local]\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_function_zdo7ggv4wtbb_1"
},
{
"role": "assistant",
"content": "",
"reasoning": "No local LLM server running. Let me check if ollama is installed at all.\n",
"finish_reason": "tool_calls",
"reasoning_content": "No local LLM server running. Let me check if ollama is installed at all.\n",
"reasoning_details": [
{
"signature": "dcc52ed683987676e9270e80bd20ed1759bd1a5492868f0c17e6c3137fbc39e5",
"thinking": "No local LLM server running. Let me check if ollama is installed at all.\n",
"type": "thinking"
}
],
"tool_calls": [
{
"id": "call_function_pxy42cwnjrwt_1",
"call_id": "call_function_pxy42cwnjrwt_1",
"response_item_id": "fc_function_pxy42cwnjrwt_1",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\": \"which ollama && ollama list 2>/dev/null; ls ~/.ollama/models 2>/dev/null | head -5\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_function_pxy42cwnjrwt_1"
},
{
"role": "assistant",
"content": "",
"reasoning": "No ollama. Let me check for vllm, lmstudio, or other local LLM serving tools.\n",
"finish_reason": "tool_calls",
"reasoning_content": "No ollama. Let me check for vllm, lmstudio, or other local LLM serving tools.\n",
"reasoning_details": [
{
"signature": "8822a098c8d091bdbd668fc3d8ae1af766c36a8f4d77d452442029dc12b80469",
"thinking": "No ollama. Let me check for vllm, lmstudio, or other local LLM serving tools.\n",
"type": "thinking"
}
],
"tool_calls": [
{
"id": "call_function_6fj8pejduo0b_1",
"call_id": "call_function_6fj8pejduo0b_1",
"response_item_id": "fc_function_6fj8pejduo0b_1",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\": \"which vllm lmstudio jan limmlc 2>/dev/null; pip list 2>/dev/null | grep -iE 'vllm|llama-cpp|ctransformers|gpt4all'\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"\", \"exit_code\": 1, \"error\": null}",
"tool_call_id": "call_function_6fj8pejduo0b_1"
},
{
"role": "assistant",
"content": "",
"reasoning": "No local LLM at all. Let me check what's actually installed and what the hermes config says about providers.\n",
"finish_reason": "tool_calls",
"reasoning_content": "No local LLM at all. Let me check what's actually installed and what the hermes config says about providers.\n",
"reasoning_details": [
{
"signature": "4457c2a7475a37a76495a81453865a700fa4dbb763716de9e0ac4a65e9d4579a",
"thinking": "No local LLM at all. Let me check what's actually installed and what the hermes config says about providers.\n",
"type": "thinking"
}
],
"tool_calls": [
{
"id": "call_function_y6d33r7i7nbd_1",
"call_id": "call_function_y6d33r7i7nbd_1",
"response_item_id": "fc_function_y6d33r7i7nbd_1",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\": \"pip list 2>/dev/null | grep -iE 'llama|ollama|vllm|minimax|transformers' | head -10\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_function_y6d33r7i7nbd_1"
},
{
"role": "assistant",
"content": "",
"reasoning": "Nothing found. Let me check what's installed and what's available.\n",
"finish_reason": "tool_calls",
"reasoning_content": "Nothing found. Let me check what's installed and what's available.\n",
"reasoning_details": [
{
"signature": "f864a068f235809f50b6a6bce83b00a2a1502236610e4f918c21bdda62c3080d",
"thinking": "Nothing found. Let me check what's installed and what's available.\n",
"type": "thinking"
}
],
"tool_calls": [
{
"id": "call_function_zxse2nfkndf7_1",
"call_id": "call_function_zxse2nfkndf7_1",
"response_item_id": "fc_function_zxse2nfkndf7_1",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\": \"nvidia-smi 2>/dev/null | head -20; python3 -c \\\"import torch; print('CUDA:', torch.cuda.is_available())\\\" 2>/dev/null\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"\", \"exit_code\": 1, \"error\": null, \"approval\": \"Command required approval (script execution via -e/-c flag) and was approved by the user.\"}",
"tool_call_id": "call_function_zxse2nfkndf7_1"
},
{
"role": "assistant",
"content": "",
"reasoning": "nvidia-smi is not available - no GPU. Let me try a different approach to check what's available.\n",
"finish_reason": "tool_calls",
"reasoning_content": "nvidia-smi is not available - no GPU. Let me try a different approach to check what's available.\n",
"reasoning_details": [
{
"signature": "42fb333c401e23924196df59c57b52a890b7401dcc31cc26d4f1996d35f3ce2c",
"thinking": "nvidia-smi is not available - no GPU. Let me try a different approach to check what's available.\n",
"type": "thinking"
}
],
"tool_calls": [
{
"id": "call_function_biy706fxyyj9_1",
"call_id": "call_function_biy706fxyyj9_1",
"response_item_id": "fc_function_biy706fxyyj9_1",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\": \"ls /dev/disk/by-uuid/ 2>/dev/null; df -h / 2>/dev/null | tail -1\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"1A9A81989A817155\\n5601-DB89\\n60EE01A5EE017516\\n7b2cca48-fbe1-4415-91ea-16bd56584ad5\\nAAC40297C40265C3\\nC200838600837FE1\\nD684-1FB9\\n/dev/nvme0n1p8 88G 61G 23G 73% /\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_function_biy706fxyyj9_1"
},
{
"role": "assistant",
"content": "没找到本地模型。\n\n**检查结果：**\n- ❌ 无 NVIDIA GPU（`nvidia-smi` 不可用）\n- ❌ 无 Ollama\n- ❌ 无 vLLM / LM Studio / Jan\n- ❌ 无 llama.cpp 系列\n- ✅ 88GB NVMe 盘，剩 23GB\n- ❌ `MINIMAX_API_KEY` 仍为空\n\n这台电脑是纯 CPU 环境，没有本地跑大模型的条件。想在这台机器上装个 smaller 模型（比如 1-3B 的 Phi、Qwen2.5）做 TTS 替代？还是继续用 MiniMax API？",
"reasoning": "No NVIDIA GPU visible. Let me check what's actually available - CPU only, 23GB free on NVMe. No local LLM setup found.\n",
"finish_reason": "stop",
"reasoning_content": "No NVIDIA GPU visible. Let me check what's actually available - CPU only, 23GB free on NVMe. No local LLM setup found.\n",
"reasoning_details": [
{
"signature": "c22a0a1abdb17120981531ee3a48f8382d6e7ff2fce29ce68c99c391c29e08e8",
"thinking": "No NVIDIA GPU visible. Let me check what's actually available - CPU only, 23GB free on NVMe. No local LLM setup found.\n",
"type": "thinking"
}
]
},
{
"role": "user",
"content": "Review the conversation above and update the skill library. Be ACTIVE — most sessions produce at least one skill update, even if small. A pass that does nothing is a missed learning opportunity, not a neutral outcome.\n\nTarget shape of the library: CLASS-LEVEL skills, each with a rich SKILL.md and a `references/` directory for session-specific detail. Not a long flat list of narrow one-session-one-skill entries. This shapes HOW you update, not WHETHER you update.\n\nSignals to look for (any one of these warrants action):\n • User corrected your style, tone, format, legibility, or verbosity. Frustration signals like 'stop doing X', 'this is too verbose', 'don't format like this', 'why are you explaining', 'just give me the answer', 'you always do Y and I hate it', or an explicit 'remember this' are FIRST-CLASS skill signals, not just memory signals. Update the relevant skill(s) to embed the preference so the next session starts already knowing.\n • User corrected your workflow, approach, or sequence of steps. Encode the correction as a pitfall or explicit step in the skill that governs that class of task.\n • Non-trivial technique, fix, workaround, debugging path, or tool-usage pattern emerged that a future session would benefit from. Capture it.\n • A skill that got loaded or consulted this session turned out to be wrong, missing a step, or outdated. Patch it NOW.\n\nPreference order — prefer the earliest action that fits, but do pick one when a signal above fired:\n 1. UPDATE A CURRENTLY-LOADED SKILL. Look back through the conversation for skills the user loaded via /skill-name or you read via skill_view. If any of them covers the territory of the new learning, PATCH that one first. It is the skill that was in play, so it's the right one to extend.\n 2. UPDATE AN EXISTING UMBRELLA (via skills_list + skill_view). If no loaded skill fits but an existing class-level skill does, patch it. Add a subsection, a pitfall, or broaden a trigger.\n 3. ADD A SUPPORT FILE under an existing umbrella. Skills can be packaged with three kinds of support files — use the right directory per kind:\n • `references/.md` — session-specific detail (error transcripts, reproduction recipes, provider quirks) AND condensed knowledge banks: quoted research, API docs, external authoritative excerpts, or domain notes you found while working on the problem. Write it concise and for the value of the task, not as a full mirror of upstream docs.\n • `templates/.` — starter files meant to be copied and modified (boilerplate configs, scaffolding, a known-good example the agent can `reproduce with modifications`).\n • `scripts/.` — statically re-runnable actions the skill can invoke directly (verification scripts, fixture generators, deterministic probes, anything the agent should run rather than hand-type each time).\n Add support files via skill_manage action=write_file with file_path starting 'references/', 'templates/', or 'scripts/'. The umbrella's SKILL.md should gain a one-line pointer to any new support file so future agents know it exists.\n 4. CREATE A NEW CLASS-LEVEL UMBRELLA SKILL when no existing skill covers the class. The name MUST be at the class level. The name MUST NOT be a specific PR number, error string, feature codename, library-alone name, or 'fix-X / debug-Y / audit-Z-today' session artifact. If the proposed name only makes sense for today's task, it's wrong — fall back to (1), (2), or (3).\n\nUser-preference embedding (important): when the user expressed a style/format/workflow preference, the update belongs in the SKILL.md body, not just in memory. Memory captures 'who the user is and what the current situation and state of your operations are'; skills capture 'how to do this class of task for this user'. When they complain about how you handled a task, the skill that governs that task needs to carry the lesson.\n\nIf you notice two existing skills that overlap, note it in your reply — the background curator handles consolidation at scale.\n\nDo NOT capture (these become persistent self-imposed constraints that bite you later when the environment changes):\n • Environment-dependent failures: missing binaries, fresh-install errors, post-migration path mismatches, 'command not found', unconfigured credentials, uninstalled packages. The user can fix these — they are not durable rules.\n • Negative claims about tools or features ('browser tools do not work', 'X tool is broken', 'cannot use Y from execute_code'). These harden into refusals the agent cites against itself for months after the actual problem was fixed.\n • Session-specific transient errors that resolved before the conversation ended. If retrying worked, the lesson is the retry pattern, not the original failure.\n • One-off task narratives. A user asking 'summarize today's market' or 'analyze this PR' is not a class of work that warrants a skill.\n\nIf a tool failed because of setup state, capture the FIX (install command, config step, env var to set) under an existing setup or troubleshooting skill — never 'this tool does not work' as a standalone constraint.\n\n'Nothing to save.' is a real option but should NOT be the default. If the session ran smoothly with no corrections and produced no new technique, just say 'Nothing to save.' and stop. Otherwise, act.\n\nYou can only call memory and skill management tools. Other tools will be denied at runtime — do not attempt them."
},
{
"role": "assistant",
"content": "看了整个对话，技术上没有新的 workflow 或技术点产生——都是诊断性检查。\n\n**唯一值得记录的**：Cron Job 的 TTS 失败根因是 `MINIMAX_API_KEY` 在 cron 隔离环境中不生效，属于已知问题（已在 memory 里）。\n\n不需要新建或更新 skill：\n- 这是环境配置问题，用户自己修就行\n- 没有新的工具使用模式\n- 没有用户偏好修正\n- 没有 workflow 纠正\n\n**Nothing to save.**",
"reasoning": "Let me review the conversation for skill-relevant signals:\n\n1. The user asked to check local models - they wanted to know if there was a local model available for TTS. The agent checked and found no local model (no Ollama, vLLM, LM Studio, llama.cpp, no GPU).\n\n2. The cron job (morning-briefing) was working but TTS failed because MINIMAX_API_KEY wasn't set in the environment.\n\n3. The agent discovered that MINIMAX_API_KEY IS set (the echo showed \"...\" which means it's masked but exists), but the cron job environment doesn't inherit it.\n\n4. The morning-briefing cron job was manually triggered but didn't produce a new output file in the expected location.\n\n\n5. The core issue is that the cron job runs in a fresh environment without access to the user's environment variables, so it can't reach the MINIMAX_API_KEY even though it's available in the terminal session where the cron was triggered. I need to create a skill that documents the environment variable inheritance problem and outlines the proper approaches to fix it. is a common problem with cron jobs)\n3. The morning-briefing skill might need to be updated to note that TTS requires MINIMAX_API_KEY to be set in the cron environment or passed through\n\nActually, looking at the user's original memory note: \"MiniMax 账户余额耗尽 — 2026-05-18 出现大量 `insufficient balance (1008)` 错误，API 调用失败。TTS 也因 MINIMAX_API_KEY 未设置而失败。\"\n\nSo the issue is known. The skill for morning-briefing should capture this known pitfall.\n\nLet me check what skills exist that might be relevant. The morning-briefing cron job itself - is there a skill for it? Looking at the available skills list, I don't see a \"morning-briefing\" skill. The cron job was created from a prompt but there's no saved skill for it.\n\nThe \"hermes-agent\" skill might be relevant for configuring cron jobs and environment variables, but that's really about configuring Hermes itself. What I actually need is a skill for \"setting up cron jobs that need environment variables\" - something that captures the pattern of passing env vars through. Let me look at what exists in the skills directory first.\n\nActually, the most concrete technical insight here is that cron jobs run in isolated environments and don't automatically get access to shell environment variables. This is a general pattern worth documenting.\n\nBut the user also wanted me to review the conversation and update the skill library, with the priority being updating currently-loaded skills. I didn't load any skills this conversation - I just listed and viewed cron jobs and ran terminal commands. So there's nothing currently loaded to update.\n\nLet me check what skills are available that might be relevant: kanban-worker, kanban-orchestrator, github-*, software-development/*, etc. The software-development skills like spike, test-driven-development, writing-plans, and plan seem potentially useful here.\n\nI don't think I need to create a new skill for this - it's a relatively narrow technical pattern about cron environment isolation that doesn't really warrant a full class-level skill. The actual issue was the MINIMAX_API_KEY wasn't being passed through to the cron job environment, which is a specific configuration problem rather than a general pattern worth documenting.\n\nBut wait - the user specifically asked me to be active about updating skills. Let me reconsider what happened in this session that might be worth capturing. The user wanted to test the morning-briefing cron job, I listed and ran it, and found the cron environment doesn't inherit the shell environment variables - that's a real insight worth saving. Though actually, this is more of a transient session issue rather than something that warrants a full skill. I should just note that in my response rather than creating new skills unnecessarily.",
"finish_reason": "stop",
"reasoning_content": "Let me review the conversation for skill-relevant signals:\n\n1. The user asked to check local models - they wanted to know if there was a local model available for TTS. The agent checked and found no local model (no Ollama, vLLM, LM Studio, llama.cpp, no GPU).\n\n2. The cron job (morning-briefing) was working but TTS failed because MINIMAX_API_KEY wasn't set in the environment.\n\n3. The agent discovered that MINIMAX_API_KEY IS set (the echo showed \"...\" which means it's masked but exists), but the cron job environment doesn't inherit it.\n\n4. The morning-briefing cron job was manually triggered but didn't produce a new output file in the expected location.\n\n\n5. The core issue is that the cron job runs in a fresh environment without access to the user's environment variables, so it can't reach the MINIMAX_API_KEY even though it's available in the terminal session where the cron was triggered. I need to create a skill that documents the environment variable inheritance problem and outlines the proper approaches to fix it. is a common problem with cron jobs)\n3. The morning-briefing skill might need to be updated to note that TTS requires MINIMAX_API_KEY to be set in the cron environment or passed through\n\nActually, looking at the user's original memory note: \"MiniMax 账户余额耗尽 — 2026-05-18 出现大量 `insufficient balance (1008)` 错误，API 调用失败。TTS 也因 MINIMAX_API_KEY 未设置而失败。\"\n\nSo the issue is known. The skill for morning-briefing should capture this known pitfall.\n\nLet me check what skills exist that might be relevant. The morning-briefing cron job itself - is there a skill for it? Looking at the available skills list, I don't see a \"morning-briefing\" skill. The cron job was created from a prompt but there's no saved skill for it.\n\nThe \"hermes-agent\" skill might be relevant for configuring cron jobs and environment variables, but that's really about configuring Hermes itself. What I actually need is a skill for \"setting up cron jobs that need environment variables\" - something that captures the pattern of passing env vars through. Let me look at what exists in the skills directory first.\n\nActually, the most concrete technical insight here is that cron jobs run in isolated environments and don't automatically get access to shell environment variables. This is a general pattern worth documenting.\n\nBut the user also wanted me to review the conversation and update the skill library, with the priority being updating currently-loaded skills. I didn't load any skills this conversation - I just listed and viewed cron jobs and ran terminal commands. So there's nothing currently loaded to update.\n\nLet me check what skills are available that might be relevant: kanban-worker, kanban-orchestrator, github-*, software-development/*, etc. The software-development skills like spike, test-driven-development, writing-plans, and plan seem potentially useful here.\n\nI don't think I need to create a new skill for this - it's a relatively narrow technical pattern about cron environment isolation that doesn't really warrant a full class-level skill. The actual issue was the MINIMAX_API_KEY wasn't being passed through to the cron job environment, which is a specific configuration problem rather than a general pattern worth documenting.\n\nBut wait - the user specifically asked me to be active about updating skills. Let me reconsider what happened in this session that might be worth capturing. The user wanted to test the morning-briefing cron job, I listed and ran it, and found the cron environment doesn't inherit the shell environment variables - that's a real insight worth saving. Though actually, this is more of a transient session issue rather than something that warrants a full skill. I should just note that in my response rather than creating new skills unnecessarily.",
"reasoning_details": [
{
"signature": "91fa4756ec6ba31386ea7bd78e0db9773312dd22b08c54f37ba5576051e7a5a3",
"thinking": "Let me review the conversation for skill-relevant signals:\n\n1. The user asked to check local models - they wanted to know if there was a local model available for TTS. The agent checked and found no local model (no Ollama, vLLM, LM Studio, llama.cpp, no GPU).\n\n2. The cron job (morning-briefing) was working but TTS failed because MINIMAX_API_KEY wasn't set in the environment.\n\n3. The agent discovered that MINIMAX_API_KEY IS set (the echo showed \"...\" which means it's masked but exists), but the cron job environment doesn't inherit it.\n\n4. The morning-briefing cron job was manually triggered but didn't produce a new output file in the expected location.\n\n\n5. The core issue is that the cron job runs in a fresh environment without access to the user's environment variables, so it can't reach the MINIMAX_API_KEY even though it's available in the terminal session where the cron was triggered. I need to create a skill that documents the environment variable inheritance problem and outlines the proper approaches to fix it. is a common problem with cron jobs)\n3. The morning-briefing skill might need to be updated to note that TTS requires MINIMAX_API_KEY to be set in the cron environment or passed through\n\nActually, looking at the user's original memory note: \"MiniMax 账户余额耗尽 — 2026-05-18 出现大量 `insufficient balance (1008)` 错误，API 调用失败。TTS 也因 MINIMAX_API_KEY 未设置而失败。\"\n\nSo the issue is known. The skill for morning-briefing should capture this known pitfall.\n\nLet me check what skills exist that might be relevant. The morning-briefing cron job itself - is there a skill for it? Looking at the available skills list, I don't see a \"morning-briefing\" skill. The cron job was created from a prompt but there's no saved skill for it.\n\nThe \"hermes-agent\" skill might be relevant for configuring cron jobs and environment variables, but that's really about configuring Hermes itself. What I actually need is a skill for \"setting up cron jobs that need environment variables\" - something that captures the pattern of passing env vars through. Let me look at what exists in the skills directory first.\n\nActually, the most concrete technical insight here is that cron jobs run in isolated environments and don't automatically get access to shell environment variables. This is a general pattern worth documenting.\n\nBut the user also wanted me to review the conversation and update the skill library, with the priority being updating currently-loaded skills. I didn't load any skills this conversation - I just listed and viewed cron jobs and ran terminal commands. So there's nothing currently loaded to update.\n\nLet me check what skills are available that might be relevant: kanban-worker, kanban-orchestrator, github-*, software-development/*, etc. The software-development skills like spike, test-driven-development, writing-plans, and plan seem potentially useful here.\n\nI don't think I need to create a new skill for this - it's a relatively narrow technical pattern about cron environment isolation that doesn't really warrant a full class-level skill. The actual issue was the MINIMAX_API_KEY wasn't being passed through to the cron job environment, which is a specific configuration problem rather than a general pattern worth documenting.\n\nBut wait - the user specifically asked me to be active about updating skills. Let me reconsider what happened in this session that might be worth capturing. The user wanted to test the morning-briefing cron job, I listed and ran it, and found the cron environment doesn't inherit the shell environment variables - that's a real insight worth saving. Though actually, this is more of a transient session issue rather than something that warrants a full skill. I should just note that in my response rather than creating new skills unnecessarily.",
"type": "thinking"
}
]
}
]
}