{
"session_id": "20260409_145734_ce2fc7",
"model": "gpt-5.4",
"base_url": "",
"platform": "cli",
"session_start": "2026-04-09T14:57:34.752737",
"last_updated": "2026-04-09T14:58:20.343645",
"system_prompt": "# SOUL.md - Who You Are\n\n_You're not a chatbot. You're becoming someone._\n\n## Core Truths\n\n**Be genuinely helpful, not performatively helpful.** Skip the \"Great question!\" and \"I'd be happy to help!\" — just help. Actions speak louder than filler words.\n\n**Have opinions.** You're allowed to disagree, prefer things, find stuff amusing or boring. An assistant with no personality is just a search engine with extra steps.\n\n**Be resourceful before asking.** Try to figure it out. Read the file. Check the context. Search for it. _Then_ ask if you're stuck. The goal is to come back with answers, not questions.\n\n**Earn trust through competence.** Your human gave you access to their stuff. Don't make them regret it. Be careful with external actions (emails, tweets, anything public). Be bold with internal ones (reading, organizing, learning).\n\n**Remember you're a guest.** You have access to someone's life — their messages, files, calendar, maybe even their home. That's intimacy. Treat it with respect.\n\n## Boundaries\n\n- Private things stay private. Period.\n- When in doubt, ask before acting externally.\n- Never send half-baked replies to messaging surfaces.\n- You're not the user's voice — be careful in group chats.\n\n## Vibe\n\nBe the assistant you'd actually want to talk to. Concise when needed, thorough when it matters. Not a corporate drone. Not a sycophant. Just... good.\n\n## Continuity\n\nEach session, you wake up fresh. These files _are_ your memory. Read them. Update them. They're how you persist.\n\nIf you change this file, tell the user — it's your soul, and they should know.\n\n---\n\n_This file is yours to evolve. As you learn who you are, update it._\n\nYou have persistent memory across sessions. Save durable facts using the memory tool: user preferences, environment details, tool quirks, and stable conventions. Memory is injected into every turn, so keep it compact and focused on facts that will still matter later.\nPrioritize what reduces future user steering — the most valuable memory is one that prevents the user from having to correct or remind you again. User preferences and recurring corrections matter more than procedural task details.\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts. If you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool. When the user references something from a past conversation or you suspect relevant cross-session context exists, use session_search to recall it before asking them to repeat themselves. After completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow, save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked. Skills that aren't maintained become liabilities.\n\n# Tool-use enforcement\nYou MUST use your tools to take action — do not describe what you would do or plan to do without actually doing it. When you say you will perform an action (e.g. 'I will run the tests', 'Let me check the file', 'I will create the project'), you MUST immediately make the corresponding tool call in the same response. Never end your turn with a promise of future action — execute it now.\nKeep working until the task is actually complete. Do not stop with a summary of what you plan to do next time. If you have tools available that can accomplish the task, use them instead of telling the user what you would do.\nEvery response should either (a) contain tool calls that make progress, or (b) deliver a final result to the user. Responses that only describe intentions without acting are not acceptable.\n\n# Execution discipline\n\n- Use tools whenever they improve correctness, completeness, or grounding.\n- Do not stop early when another tool call would materially improve the result.\n- If a tool returns empty or partial results, retry with a different query or strategy before giving up.\n- Keep calling tools until: (1) the task is complete, AND (2) you have verified the result.\n\n\n\nNEVER answer these from memory or mental computation — ALWAYS use a tool:\n- Arithmetic, math, calculations → use terminal or execute_code\n- Hashes, encodings, checksums → use terminal (e.g. sha256sum, base64)\n- Current time, date, timezone → use terminal (e.g. date)\n- System state: OS, CPU, memory, disk, ports, processes → use terminal\n- File contents, sizes, line counts → use read_file, search_files, or terminal\n- Git history, branches, diffs → use terminal\n- Current facts (weather, news, versions) → use web_search\nYour memory and user profile describe the USER, not the system you are running on. The execution environment may differ from what the user profile says about their personal setup.\n\n\n\nWhen a question has an obvious default interpretation, act on it immediately instead of asking for clarification. Examples:\n- 'Is port 443 open?' → check THIS machine (don't ask 'open where?')\n- 'What OS am I running?' → check the live system (don't use user profile)\n- 'What time is it?' → run `date` (don't guess)\nOnly ask for clarification when the ambiguity genuinely changes what tool you would call.\n\n\n\n- Before taking an action, check whether prerequisite discovery, lookup, or context-gathering steps are needed.\n- Do not skip prerequisite steps just because the final action seems obvious.\n- If a task depends on output from a prior step, resolve that dependency first.\n\n\n\nBefore finalizing your response:\n- Correctness: does the output satisfy every stated requirement?\n- Grounding: are factual claims backed by tool outputs or provided context?\n- Formatting: does the output match the requested format or schema?\n- Safety: if the next step has side effects (file writes, commands, API calls), confirm scope before executing.\n\n\n\n- If required context is missing, do NOT guess or hallucinate an answer.\n- Use the appropriate lookup tool when missing information is retrievable (search_files, web_search, read_file, etc.).\n- Ask a clarifying question only when the information cannot be retrieved by tools.\n- If you must proceed with incomplete information, label assumptions explicitly.\n\n\n══════════════════════════════════════════════\nMEMORY (your personal notes) [91% — 2,021/2,200 chars]\n══════════════════════════════════════════════\nThis file exists for backward compatibility with older startup routines.\n§\nThe canonical long-term memory file in this workspace is `MEMORIES.md`.\n§\nIf you are reading this during session startup:\n§\nPrefer `MEMORIES.md` for curated long-term memory.\n§\nUse `memory/YYYY-MM-DD.md` files for recent context.\n§\nDo not rely on `exec` just to list files that are already known.\n§\nReplaced with cleaner entries below\n§\nSession: 2026-02-28 18:09:27 UTC > Conversation Summary: eu assistant: [[reply_to_current]] Acá estoy 😄 ¿Qué necesitás, Chicho?\n§\n2026-02-28: No usa dispositivos Apple (skills Apple no prioritarios).\n§\n2026-02-28: No usa Spotify; prefiere YouTube Music.\n§\n2026-02-28: Prefiere Asana sobre Trello.\n§\n2026-02-28: Usuario pidió respuestas en voz; se respondió con TTS.\n§\n2026-02-28: Usuario aclara que por ahora no ve necesario un skill para controlar YouTube Music.\n§\n2026-03-01: Se validado estado \"Maxxxed Out\":\n§\n2026-04-04: personal-browser-cdp skill creado y testeado. CDP funciona bien via Chrome en Windows + SSH reverse tunnel.\n- lanacion.com.ar tiene lazy/infinite loading — browser_scroll normal no llega al footer, usar browser_press key='End'.\n- La Nación login abre como overlay con email + Google/Facebook/Apple social login.\n§\nHermes WebUI session deletion is permanent (no trash). But CODE changes persist as uncommitted git changes in ~/hermes-webui/. To recover work from dead/deleted session: cd ~/hermes-webui && git status --short && git diff HEAD --stat && git stash list. Session JSON files (~/.hermes/webui/sessions/*.json) ARE gone permanently.\n§\nUser (Chicho) prefers direct, no-filler communication. Environment: Ubuntu 24.04 ARM64, Oracle Cloud. WebUI source at ~/hermes-webui. User requested ability to change Agent Profile defaults (model, provider, skills, API keys) via WebUI. Work in progress: ~3000 lines of uncommitted changes in ~/hermes-webui including a new Terminal panel and Profile Config API. Found bug in api/routes.py: 'if val is None and val == \"\"' (should be 'or').\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [99% — 1,364/1,375 chars]\n══════════════════════════════════════════════\n_Learn about the person you're helping. Update this as you go._\n§\n**Name:** Ignacio (Igna, also goes by Chicho)\n§\n**What to call them:** Igna or Chicho\n§\n**Pronouns:** _(not specified)_\n§\n**Timezone:** UTC-3 (Buenos Aires, Argentina)\n§\n**Notes:**\n§\nNo usa dispositivos Apple\n§\nPrefiere YouTube Music (no Spotify)\n§\nPrefiere Asana sobre Trello\n§\nPrefiere respuestas en texto por defecto (para ahorrar tokens de ElevenLabs)\n§\nAudio solo cuando él lo pida explícitamente\n§\nPrefiere respuestas directas; si pregunta por Discord/plataformas, quiere límites claros sin que le cambien el flujo.\n§\nStack (2026-04-03): Hermes reemplazó OpenClaw. Default: claude-sonnet-4-6 vía Anthropic OAuth hasta 04/04. Fallback: gpt-5.4 vía OpenAI Codex (Pro hasta ~09/04). Cron switchea el 05/04 07:00 UTC.\n§\nTiene Tailscale en su computadora personal — se puede usar para acceso cross-device\n§\nGmail: ignaciolagosruiz@gmail.com (gog configurado, read-only)\n§\nNo quiere que Pipo interactúe con otras personas vía WhatsApp/mensajería (por ahora)\n§\nVive en Argentina — scraping de sitios locales puede necesitar exit node argentino (Pixel 6a via Tailscale)\n§\nContext: ---\n§\nAPIs config: DeepSeek (key en Bitwarden, en Hermes), Kimi K2.5, Mistral ($10), OpenRouter ($0.53 backup), ClawRouter wallet 0x1d1776D... ($11.70 Base). DeepSeek/Kimi NO como daily driver — solo workers/subagentes.\n\n## Skills (mandatory)\nBefore replying, scan the skills below. If one clearly matches your task, load it with skill_view(name) and follow its instructions. If 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 tasks to Claude Code (Anthropic's CLI age...\n - codex: Delegate coding tasks to OpenAI Codex CLI agent. Use for ...\n - hermes-agent: Complete guide to using and extending Hermes Agent — CLI ...\n - opencode: Delegate coding tasks to OpenCode CLI agent for feature i...\n bybit:\n - bybit: Check Bybit account — wallet balance, open positions, ord...\n creative: Creative content generation — ASCII art, hand-drawn style diagrams, and visual design tools.\n - ascii-art: Generate ASCII art using pyfiglet (571 fonts), cowsay, bo...\n - ascii-video: Production pipeline for ASCII art video — any format. Con...\n - excalidraw: Create hand-drawn style diagrams using Excalidraw JSON fo...\n - manim-video: Production pipeline for mathematical and technical animat...\n - p5js: Production pipeline for interactive and generative visual...\n - popular-web-designs: 54 production-quality design systems extracted from real ...\n - songwriting-and-ai-music: Songwriting craft, AI music generation prompts (Suno focu...\n data-science: Skills for data science workflows — interactive exploration, Jupyter notebooks, data analysis, and visualization.\n - jupyter-live-kernel: Use a live Jupyter kernel for stateful, iterative Python ...\n devops:\n - openclaw-mobile-node: Set up OpenClaw gateway as a notification relay for an An...\n - supabase-region-migration: Migrate a Supabase project to a different region (e.g. us...\n - webhook-subscriptions: Create and manage webhook subscriptions for event-driven ...\n - whatsapp-baileys-vercel: Run a WhatsApp bot with Baileys bridge + Vercel webhook —...\n dogfood:\n - dogfood: Systematic exploratory QA testing of web applications — f...\n - hermes-workspace-pristine-reset: Reset a local Hermes Agent + Hermes Workspace install to ...\n email: Skills for sending, receiving, searching, and managing email from the terminal.\n - himalaya: CLI to manage emails via IMAP/SMTP. Use himalaya to list,...\n gaming: Skills for setting up, configuring, and managing game servers, modpacks, and gaming-related infrastructure.\n - minecraft-modpack-server: Set up a modded Minecraft server from a CurseForge/Modrin...\n - pokemon-player: Play Pokemon games autonomously via headless emulation. S...\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 and analyze codebases using pygount for LOC count...\n - github-auth: Set up GitHub authentication for the agent using git (uni...\n - github-code-review: Review code changes by analyzing git diffs, leaving inlin...\n - github-issues: Create, manage, triage, and close GitHub issues. Search e...\n - github-pr-workflow: Full pull request lifecycle — create branches, commit cha...\n - github-repo-management: Clone, create, fork, configure, and manage GitHub reposit...\n hermes-webui-comparison:\n - hermes-webui-comparison: Evaluate, deploy, and compare alternative web UIs for Her...\n hermes-webui-deploy:\n - hermes-webui-deploy: Deploy Hermes WebUI (nesquena/hermes-webui) with embedded...\n leisure:\n - find-nearby: Find nearby places (restaurants, cafes, bars, pharmacies,...\n mcp: Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Includes the built-in native MCP client (configure servers in config.yaml for automatic tool discovery) and the mcporter CLI bridge for ad-hoc server interaction.\n - mcporter: Use the mcporter CLI to list, configure, auth, and call M...\n - native-mcp: Built-in MCP (Model Context Protocol) client that connect...\n media: Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.\n - gif-search: Search and download GIFs from Tenor using curl. No depend...\n - heartmula: Set up and run HeartMuLa, the open-source music generatio...\n - songsee: Generate spectrograms and audio feature visualizations (m...\n - youtube-content: Fetch YouTube video transcripts and transform them into s...\n mlops: Knowledge and Tools for Machine Learning Operations - tools and frameworks for training, fine-tuning, deploying, and optimizing ML/AI models\n - clawrouter: Install, configure, and manage ClawRouter as a local LLM ...\n - huggingface-hub: Hugging Face Hub CLI (hf) — search, download, and upload ...\n mlops/cloud: GPU cloud providers and serverless compute platforms for ML workloads.\n - modal: Serverless GPU cloud platform for running ML workloads. U...\n mlops/evaluation: Model evaluation benchmarks, experiment tracking, data curation, tokenizers, and interpretability tools.\n - lm-evaluation-harness: Evaluates LLMs across 60+ academic benchmarks (MMLU, Huma...\n - weights-and-biases: Track ML experiments with automatic logging, visualize tr...\n mlops/inference: Model serving, quantization (GGUF/GPTQ), structured output, inference optimization, and model surgery tools for deploying and running LLMs.\n - gguf: GGUF format and llama.cpp quantization for efficient CPU/...\n - guidance: Control LLM output with regex and grammars, guarantee val...\n - llama-cpp: Runs LLM inference on CPU, Apple Silicon, and consumer GP...\n - obliteratus: Remove refusal behaviors from open-weight LLMs using OBLI...\n - outlines: Guarantee valid JSON/XML/code structure during generation...\n - vllm: Serves LLMs with high throughput using vLLM's PagedAttent...\n mlops/models: Specific model architectures and tools — computer vision (CLIP, SAM, Stable Diffusion), speech (Whisper), audio generation (AudioCraft), and multimodal models (LLaVA).\n - audiocraft: PyTorch library for audio generation including text-to-mu...\n - clip: OpenAI's model connecting vision and language. Enables ze...\n - segment-anything: Foundation model for image segmentation with zero-shot tr...\n - stable-diffusion: State-of-the-art text-to-image generation with Stable Dif...\n - whisper: OpenAI's general-purpose speech recognition model. Suppor...\n mlops/research: ML research frameworks for building and optimizing AI systems with declarative programming.\n - dspy: Build complex AI systems with declarative programming, op...\n mlops/training: Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools for training LLMs and other models.\n - axolotl: Expert guidance for fine-tuning LLMs with Axolotl - YAML ...\n - grpo-rl-training: Expert guidance for GRPO/RL fine-tuning with TRL for reas...\n - peft: Parameter-efficient fine-tuning for LLMs using LoRA, QLoR...\n - pytorch-fsdp: Expert guidance for Fully Sharded Data Parallel training ...\n - trl-fine-tuning: Fine-tune LLMs using reinforcement learning with TRL - SF...\n - unsloth: Expert guidance for fast fine-tuning with Unsloth - 2-5x ...\n myristica-ops:\n - myristica-ops: Myristica rental management app — stack, infrastructure, ...\n - myristica-projects: Myristica project context, audit status, and development ...\n note-taking: Note taking skills, to save information, assist with research, and collab on multi-session planning and information sharing.\n - obsidian: Read, search, and create notes in the Obsidian vault.\n openclaw-imports:\n - asana: Integrate Asana with Clawdbot via the Asana REST API. Use...\n - gog: Read-only Google Workspace CLI for Gmail, Calendar, Drive...\n - google-photos: Manage Google Photos library. Upload photos, create album...\n - hevy: Query workout data from Hevy including workouts, routines...\n - model-router: Intelligent cost-aware model routing that classifies task...\n - notion: Notion API for creating and managing pages, databases, an...\n - openclaw-bitwarden: Set up and use Bitwarden CLI (bw). Use when installing th...\n - parallel-preview-orchestrator: Orchestrate parallel preview-site creation across multipl...\n - session-logs: Search and analyze your own session logs (older/parent co...\n - summarize: Summarize URLs or files with the summarize CLI (web, PDFs...\n - weather: Get current weather and forecasts (no API key required).\n personal-browser-cdp:\n - personal-browser-cdp: Use the user's real Chrome browser through Hermes' existi...\n pixel-6a:\n - pixel-6a: Access Ignacio's Pixel 6a via ADB over Tailscale — read n...\n productivity: Skills for document creation, presentations, spreadsheets, and other productivity workflows.\n - google-workspace: Gmail, Calendar, Drive, Contacts, Sheets, and Docs integr...\n - linear: Manage Linear issues, projects, and teams via the GraphQL...\n - monthy-expenses: Reconstruct and maintain the user's household monthly-exp...\n - nano-pdf: Edit PDFs with natural-language instructions using the na...\n - notion: Notion API for creating and managing pages, databases, an...\n - ocr-and-documents: Extract text from PDFs and scanned documents. Use web_ext...\n - powerpoint: Use this skill any time a .pptx file is involved in any w...\n red-teaming:\n - godmode: Jailbreak API-served LLMs using G0DM0D3 techniques — Pars...\n research: Skills for academic research, paper discovery, literature review, domain reconnaissance, market data, content monitoring, and scientific knowledge retrieval.\n - arxiv: Search and retrieve academic papers from arXiv using thei...\n - blogwatcher: Monitor blogs and RSS/Atom feeds for updates using the bl...\n - llm-wiki: Karpathy's LLM Wiki — build and maintain a persistent, in...\n - ml-paper-writing: Write publication-ready ML/AI papers for NeurIPS, ICML, I...\n - polymarket: Query Polymarket prediction market data — search markets,...\n smart-home: Skills for controlling smart home devices — lights, switches, sensors, and home automation systems.\n - openhue: Control Philips Hue lights, rooms, and scenes via the Ope...\n social-media: Skills for interacting with social platforms and social-media workflows — posting, reading, monitoring, and account operations.\n - xitter: Interact with X/Twitter via the x-cli terminal client usi...\n software-development:\n - code-review: Guidelines for performing thorough code reviews with secu...\n - evaluate-openai-compatible-llm-endpoint: Verify whether a new OpenAI-compatible chat/completions e...\n - hermes-specialist-profile-custom-endpoint: Create a Hermes profile specialized for a model's strengt...\n - plan: Plan mode for Hermes — inspect context, write a markdown ...\n - react-component-split: Split large React client components (>300 lines) into mul...\n - requesting-code-review: Pre-commit verification pipeline — static security scan, ...\n - subagent-driven-development: Use when executing implementation plans with independent ...\n - systematic-debugging: Use when encountering any bug, test failure, or unexpecte...\n - test-driven-development: Use when implementing any feature or bugfix, before writi...\n - writing-plans: Use when you have a spec or requirements for a multi-step...\n wa-bot-fix-troubleshooting:\n - wa-bot-fix-troubleshooting: Fix WhatsApp bot not responding when bridge is connected ...\n\n\nIf none match, proceed normally without loading a skill.\n\n# Project Context\n\nThe following project context files have been loaded and should be followed:\n\n## AGENTS.md\n\n# AGENTS.md — Pipo's Environment\n\nYou are **Pipo**, a personal AI assistant for **Ignacio \"Chicho/Igna\" Lagos Ruiz**.\n\n## Your Memory Files (always check these first)\n\n- `~/.hermes/memories/MEMORY.md` — long-term curated memory\n- `~/.hermes/memories/USER.md` — user profile and preferences\n- `~/.hermes/SOUL.md` — your persona and values\n\n## Environment\n\n- Server: Ubuntu 24.04 ARM64, Oracle Cloud São Paulo\n- Tailscale IP: `100.87.116.90`, hostname: `miopenclaw-vnic.tail9799d2.ts.net`\n- Shell: bash, Node.js v22, Python 3.12\n- Your install: `~/.hermes/`\n\n## Key Facts About Chicho\n\n- Lives in Argentina (UTC-3)\n- Gmail: ignaciolagosruiz@gmail.com\n- Prefers direct responses, no filler\n- Prefers text by default, audio only when asked\n- Uses YouTube Music, not Spotify\n- No Apple devices\n- For scraping Argentine retailers: may need exit node via `tailscale set --exit-node=pixel-6a`\n\n## Scraping Exit Node\n\nWhen scraping Argentine sites (Coto, Carrefour, Día, Disco, Jumbo):\n```bash\ntailscale set --exit-node=pixel-6a # enable before scraping\ntailscale set --exit-node='' # disable after\n```\n\nConversation started: Thursday, April 09, 2026 02:57 PM\nModel: gpt-5.4\nProvider: openai-codex\n\nYou are a CLI AI Agent. Try not to use markdown but simple text renderable inside a terminal.",
"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": {},
"required": []
}
}
},
{
"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'"
}
},
"required": []
}
}
},
{
"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": {},
"required": []
}
}
},
{
"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). 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
}
},
"required": []
}
}
},
{
"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\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": "Delivery target: origin, local, telegram, discord, slack, whatsapp, signal, matrix, mattermost, homeassistant, dingtalk, feishu, wecom, email, sms, or platform:chat_id or platform:chat_id:thread_id for Telegram topics. Examples: 'origin', 'local', 'telegram', 'telegram:-1001234567890:17585', 'discord:#engineering'"
},
"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'). 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 Python script that runs before each cron job execution. Its stdout is injected into the prompt as context. Use for data collection and change detection. Relative paths resolve under ~/.hermes/scripts/. On update, pass empty string to clear."
}
},
"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. All run concurrently and results are returned together.\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\nIMPORTANT:\n- Subagents have NO memory of your conversation. Pass all relevant info (file paths, error messages, constraints) via the 'context' field.\n- Subagents CANNOT call: delegate_task, clarify, memory, send_message, execute_code.\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. Common patterns: ['terminal', 'file'] for code work, ['web'] for research, ['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. Use 'web' for network access, 'terminal' for shell."
},
"acp_command": {
"type": "string",
"description": "Per-task ACP command override (e.g. 'claude'). Overrides the top-level acp_command for this task only."
},
"acp_args": {
"type": "array",
"items": {
"type": "string"
},
"description": "Per-task ACP args override."
}
},
"required": [
"goal"
]
},
"maxItems": 3,
"description": "Batch mode: up to 3 tasks to run in parallel. Each gets its own subagent with isolated context and terminal session. When provided, top-level goal/context/toolsets are ignored."
},
"max_iterations": {
"type": "integer",
"description": "Max tool-calling turns per subagent (default: 50). Only set lower for simple tasks."
},
"acp_command": {
"type": "string",
"description": "Override ACP command for child agents (e.g. 'claude', 'copilot'). When set, children use ACP subprocess transport instead of inheriting the parent's transport. Enables spawning Claude Code (claude --acp --stdio) or other ACP-capable agents from any parent, including Discord/Telegram/CLI."
},
"acp_args": {
"type": "array",
"items": {
"type": "string"
},
"description": "Arguments for the ACP command (default: ['--acp', '--stdio']). Only used when acp_command is set. Example: ['--acp', '--stdio', '--model', 'claude-opus-4-6']"
}
},
"required": []
}
}
},
{
"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). If the session uses a cloud sandbox backend, treat it as resumable task state rather than a durable always-on machine.\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": "mcp_context7_get_prompt",
"description": "Get a prompt by name from MCP server 'context7'",
"parameters": {
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "Name of the prompt to retrieve"
},
"arguments": {
"type": "object",
"description": "Optional arguments to pass to the prompt"
}
},
"required": [
"name"
]
}
}
},
{
"type": "function",
"function": {
"name": "mcp_context7_list_prompts",
"description": "List available prompts from MCP server 'context7'",
"parameters": {
"type": "object",
"properties": {}
}
}
},
{
"type": "function",
"function": {
"name": "mcp_context7_list_resources",
"description": "List available resources from MCP server 'context7'",
"parameters": {
"type": "object",
"properties": {}
}
}
},
{
"type": "function",
"function": {
"name": "mcp_context7_query_docs",
"description": "Retrieves and queries up-to-date documentation and code examples from Context7 for any programming library or framework.\n\nYou must call 'Resolve Context7 Library ID' tool first to obtain the exact Context7-compatible library ID required to use this tool, UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.\n\nIMPORTANT: Do not call this tool more than 3 times per question. If you cannot find what you need after 3 calls, use the best information you have.",
"parameters": {
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"libraryId": {
"type": "string",
"description": "Exact Context7-compatible library ID (e.g., '/mongodb/docs', '/vercel/next.js', '/supabase/supabase', '/vercel/next.js/v14.3.0-canary.87') retrieved from 'resolve-library-id' or directly from user query in the format '/org/project' or '/org/project/version'."
},
"query": {
"type": "string",
"description": "The question or task you need help with. Be specific and include relevant details. Good: 'How to set up authentication with JWT in Express.js' or 'React useEffect cleanup function examples'. Bad: 'auth' or 'hooks'. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query."
}
},
"required": [
"libraryId",
"query"
]
}
}
},
{
"type": "function",
"function": {
"name": "mcp_context7_read_resource",
"description": "Read a resource by URI from MCP server 'context7'",
"parameters": {
"type": "object",
"properties": {
"uri": {
"type": "string",
"description": "URI of the resource to read"
}
},
"required": [
"uri"
]
}
}
},
{
"type": "function",
"function": {
"name": "mcp_context7_resolve_library_id",
"description": "Resolves a package/product name to a Context7-compatible library ID and returns matching libraries.\n\nYou MUST call this function before 'Query Documentation' tool to obtain a valid Context7-compatible library ID UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.\n\nEach result includes:\n- Library ID: Context7-compatible identifier (format: /org/project)\n- Name: Library or package name\n- Description: Short summary\n- Code Snippets: Number of available code examples\n- Source Reputation: Authority indicator (High, Medium, Low, or Unknown)\n- Benchmark Score: Quality indicator (100 is the highest score)\n- Versions: List of versions if available. Use one of those versions if the user provides a version in their query. The format of the version is /org/project/version.\n\nFor best results, select libraries based on name match, source reputation, snippet coverage, benchmark score, and relevance to your use case.\n\nSelection Process:\n1. Analyze the query to understand what library/package the user is looking for\n2. Return the most relevant match based on:\n- Name similarity to the query (exact matches prioritized)\n- Description relevance to the query's intent\n- Documentation coverage (prioritize libraries with higher Code Snippet counts)\n- Source reputation (consider libraries with High or Medium reputation more authoritative)\n- Benchmark Score: Quality indicator (100 is the highest score)\n\nResponse Format:\n- Return the selected library ID in a clearly marked section\n- Provide a brief explanation for why this library was chosen\n- If multiple good matches exist, acknowledge this but proceed with the most relevant one\n- If no good matches exist, clearly state this and suggest query refinements\n\nFor ambiguous queries, request clarification before proceeding with a best-guess match.\n\nIMPORTANT: Do not call this tool more than 3 times per question. If you cannot find what you need after 3 calls, use the best result you have.",
"parameters": {
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The question or task you need help with. This is used to rank library results by relevance to what the user is trying to accomplish. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query."
},
"libraryName": {
"type": "string",
"description": "Library name to search for and retrieve a Context7-compatible library ID. Use the official library name with proper punctuation — e.g., 'Next.js' instead of 'nextjs', 'Customer.io' instead of 'customerio', 'Three.js' instead of 'threejs'."
}
},
"required": [
"query",
"libraryName"
]
}
}
},
{
"type": "function",
"function": {
"name": "memory",
"description": "Save durable information to persistent memory that survives across sessions. Memory is injected into future turns, so keep it compact and focused on facts that will still matter later.\n\nWHEN TO SAVE (do this proactively, don't wait to be asked):\n- User corrects you or says 'remember this' / 'don't do that again'\n- User shares a preference, habit, or personal detail (name, role, timezone, coding style)\n- You discover something about the environment (OS, installed tools, project structure)\n- You learn a convention, API quirk, or workflow specific to this user's setup\n- You identify a stable fact that will be useful again in future sessions\n\nPRIORITY: User preferences and corrections > environment facts > procedural knowledge. The most valuable memory prevents the user from having to repeat themselves.\n\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts.\nIf you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\n\nTWO TARGETS:\n- 'user': who the user is -- name, role, preferences, communication style, pet peeves\n- 'memory': your notes -- environment facts, project conventions, tool quirks, lessons learned\n\nACTIONS: add (new entry), replace (update existing -- old_text identifies it), remove (delete -- old_text identifies it).\n\nSKIP: trivial/obvious info, things easily re-discovered, raw data dumps, and temporary task state.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"add",
"replace",
"remove"
],
"description": "The action to perform."
},
"target": {
"type": "string",
"enum": [
"memory",
"user"
],
"description": "Which memory store: 'memory' for personal notes, 'user' for user profile."
},
"content": {
"type": "string",
"description": "The entry content. Required for 'add' and 'replace'."
},
"old_text": {
"type": "string",
"description": "Short unique substring identifying the entry to replace or remove."
}
},
"required": [
"action",
"target"
]
}
}
},
{
"type": "function",
"function": {
"name": "mixture_of_agents",
"description": "Route a hard problem through multiple frontier LLMs collaboratively. Makes 5 API calls (4 reference models + 1 aggregator) with maximum reasoning effort — use sparingly for genuinely difficult problems. Best for: complex math, advanced algorithms, multi-step analytical reasoning, problems benefiting from diverse perspectives.",
"parameters": {
"type": "object",
"properties": {
"user_prompt": {
"type": "string",
"description": "The complex query or problem to solve using multiple AI models. Should be a challenging problem that benefits from diverse perspectives and collaborative reasoning."
}
},
"required": [
"user_prompt"
]
}
}
},
{
"type": "function",
"function": {
"name": "patch",
"description": "Targeted find-and-replace edits in files. Use this instead of sed/awk in terminal. Uses fuzzy matching (9 strategies) so minor whitespace/indentation differences won't break it. Returns a unified diff. Auto-runs syntax checks after editing.\n\nReplace mode (default): find a unique string and replace it.\nPatch mode: apply V4A multi-file patches for bulk changes.",
"parameters": {
"type": "object",
"properties": {
"mode": {
"type": "string",
"enum": [
"replace",
"patch"
],
"description": "Edit mode: 'replace' for targeted find-and-replace, 'patch' for V4A multi-file patches",
"default": "replace"
},
"path": {
"type": "string",
"description": "File path to edit (required for 'replace' mode)"
},
"old_string": {
"type": "string",
"description": "Text to find in the file (required for 'replace' mode). Must be unique in the file unless replace_all=true. Include enough surrounding context to ensure uniqueness."
},
"new_string": {
"type": "string",
"description": "Replacement text (required for 'replace' mode). Can be 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": "V4A format patch content (required for 'patch' mode). 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).",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"list",
"poll",
"log",
"wait",
"kill",
"write",
"submit"
],
"description": "Action to perform on background processes"
},
"session_id": {
"type": "string",
"description": "Process session ID (from terminal background output). Required for all actions except 'list'."
},
"data": {
"type": "string",
"description": "Text to send to process stdin (for 'write' and 'submit' actions)"
},
"timeout": {
"type": "integer",
"description": "Max seconds to block for 'wait' action. Returns partial output on timeout.",
"minimum": 1
},
"offset": {
"type": "integer",
"description": "Line offset for 'log' action (default: last 200 lines)"
},
"limit": {
"type": "integer",
"description": "Max lines to return for 'log' action",
"minimum": 1
}
},
"required": [
"action"
]
}
}
},
{
"type": "function",
"function": {
"name": "read_file",
"description": "Read a text file with line numbers and pagination. Use this instead of cat/head/tail in terminal. Output format: 'LINE_NUM|CONTENT'. Suggests similar filenames if not found. Use offset and limit for large files. Reads exceeding ~100K characters are rejected; use offset and limit to read specific sections of large files. NOTE: Cannot read images or binary files — use vision_analyze for images.",
"parameters": {
"type": "object",
"properties": {
"path": {
"type": "string",
"description": "Path to the file to read (absolute, relative, or ~/path)"
},
"offset": {
"type": "integer",
"description": "Line number to start reading from (1-indexed, default: 1)",
"default": 1,
"minimum": 1
},
"limit": {
"type": "integer",
"description": "Maximum number of lines to read (default: 500, max: 2000)",
"default": 500,
"maximum": 2000
}
},
"required": [
"path"
]
}
}
},
{
"type": "function",
"function": {
"name": "search_files",
"description": "Search file contents or find files by name. Use this instead of grep/rg/find/ls in terminal. Ripgrep-backed, faster than shell equivalents.\n\nContent search (target='content'): Regex search inside files. Output modes: full matches with line numbers, file paths only, or match counts.\n\nFile search (target='files'): Find files by glob pattern (e.g., '*.py', '*config*'). Also use this instead of ls — results sorted by modification time.",
"parameters": {
"type": "object",
"properties": {
"pattern": {
"type": "string",
"description": "Regex pattern for content search, or glob pattern (e.g., '*.py') for file search"
},
"target": {
"type": "string",
"enum": [
"content",
"files"
],
"description": "'content' searches inside file contents, 'files' searches for files by name",
"default": "content"
},
"path": {
"type": "string",
"description": "Directory or file to search in (default: current working directory)",
"default": "."
},
"file_glob": {
"type": "string",
"description": "Filter files by pattern in grep mode (e.g., '*.py' to only search Python files)"
},
"limit": {
"type": "integer",
"description": "Maximum number of results to return (default: 50)",
"default": 50
},
"offset": {
"type": "integer",
"description": "Skip first N results for pagination (default: 0)",
"default": 0
},
"output_mode": {
"type": "string",
"enum": [
"content",
"files_only",
"count"
],
"description": "Output format for grep mode: 'content' shows matching lines with line numbers, 'files_only' lists file paths, 'count' shows match counts per file",
"default": "content"
},
"context": {
"type": "integer",
"description": "Number of context lines before and after each match (grep mode only)",
"default": 0
}
},
"required": [
"pattern"
]
}
}
},
{
"type": "function",
"function": {
"name": "session_search",
"description": "Search your long-term memory of past conversations, or browse recent sessions. This is your recall -- every past session is searchable, and this tool summarizes what happened.\n\nTWO MODES:\n1. Recent sessions (no query): Call with no arguments to see what was worked on recently. Returns titles, previews, and timestamps. Zero LLM cost, instant. Start here when the user asks what were we working on or what did we do recently.\n2. Keyword search (with query): Search for specific topics across all past sessions. Returns LLM-generated summaries of matching sessions.\n\nUSE THIS PROACTIVELY when:\n- The user says 'we did this before', 'remember when', 'last time', 'as I mentioned'\n- The user asks about a topic you worked on before but don't have in current context\n- The user references a project, person, or concept that seems familiar but isn't in memory\n- You want to check if you've solved a similar problem before\n- The user asks 'what did we do about X?' or 'how did we fix Y?'\n\nDon't hesitate to search when it is actually cross-session -- it's fast and cheap. Better to search and confirm than to guess or ask the user to repeat themselves.\n\nSearch syntax: keywords joined with OR for broad recall (elevenlabs OR baseten OR funding), phrases for exact match (\"docker networking\"), boolean (python NOT java), prefix (deploy*). IMPORTANT: Use OR between keywords for best results — FTS5 defaults to AND which misses sessions that only mention some terms. If a broad OR query returns nothing, try individual keyword searches in parallel. Returns summaries of the top matching sessions.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Search query — keywords, phrases, or boolean expressions to find in past sessions. Omit this parameter entirely to browse recent sessions instead (returns titles, previews, timestamps with no LLM cost)."
},
"role_filter": {
"type": "string",
"description": "Optional: only search messages from specific roles (comma-separated). E.g. 'user,assistant' to skip tool outputs."
},
"limit": {
"type": "integer",
"description": "Max sessions to summarize (default: 3, max: 5).",
"default": 3
}
},
"required": []
}
}
},
{
"type": "function",
"function": {
"name": "skill_manage",
"description": "Manage skills (create, update, delete). Skills are your procedural memory — reusable approaches for recurring task types. New skills go to ~/.hermes/skills/; existing skills can be modified wherever they live.\n\nActions: create (full SKILL.md + optional category), patch (old_string/new_string — preferred for fixes), edit (full SKILL.md rewrite — major overhauls only), delete, write_file, remove_file.\n\nCreate when: complex task succeeded (5+ calls), errors overcome, user-corrected approach worked, non-trivial workflow discovered, or user asks you to remember a procedure.\nUpdate when: instructions stale/wrong, OS-specific failures, missing steps or pitfalls found during use. If you used a skill and hit issues not covered by it, patch it immediately.\n\nAfter difficult/iterative tasks, offer to save as a skill. Skip for simple one-offs. Confirm with user before creating/deleting.\n\nGood skills: trigger conditions, numbered steps with exact commands, pitfalls section, verification steps. Use skill_view() to see format examples.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"create",
"patch",
"edit",
"delete",
"write_file",
"remove_file"
],
"description": "The action to perform."
},
"name": {
"type": "string",
"description": "Skill name (lowercase, hyphens/underscores, max 64 chars). Must match an existing skill for patch/edit/delete/write_file/remove_file."
},
"content": {
"type": "string",
"description": "Full SKILL.md content (YAML frontmatter + markdown body). Required for 'create' and 'edit'. For 'edit', read the skill first with skill_view() and provide the complete updated text."
},
"old_string": {
"type": "string",
"description": "Text to find in the file (required for 'patch'). Must be unique unless replace_all=true. Include enough surrounding context to ensure uniqueness."
},
"new_string": {
"type": "string",
"description": "Replacement text (required for 'patch'). Can be empty string to delete the matched text."
},
"replace_all": {
"type": "boolean",
"description": "For 'patch': replace all occurrences instead of requiring a unique match (default: false)."
},
"category": {
"type": "string",
"description": "Optional category/domain for organizing the skill (e.g., 'devops', 'data-science', 'mlops'). Creates a subdirectory grouping. Only used with 'create'."
},
"file_path": {
"type": "string",
"description": "Path to a supporting file within the skill directory. For 'write_file'/'remove_file': required, must be under references/, templates/, scripts/, or assets/. For 'patch': optional, defaults to SKILL.md if omitted."
},
"file_content": {
"type": "string",
"description": "Content for the file. Required for 'write_file'."
}
},
"required": [
"action",
"name"
]
}
}
},
{
"type": "function",
"function": {
"name": "skill_view",
"description": "Skills allow for loading information about specific tasks and workflows, as well as scripts and templates. Load a skill's full content or access its linked files (references, templates, scripts). First call returns SKILL.md content plus a 'linked_files' dict showing available references/templates/scripts. To access those, call again with file_path parameter.",
"parameters": {
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "The skill name (use skills_list to see available skills)"
},
"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"
}
},
"required": []
}
}
},
{
"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.\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.\nImportant: cloud sandboxes may be cleaned up, idled out, or recreated between turns. Persistent filesystem means files can resume later; it does NOT guarantee a continuously running machine or surviving background processes. Use terminal sandboxes for task work, not durable hosting.\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). Returns INSTANTLY when command finishes — set high for long tasks, you won't wait unnecessarily.",
"minimum": 1
},
"workdir": {
"type": "string",
"description": "Working directory for this command (absolute path). Defaults to the session working directory."
},
"check_interval": {
"type": "integer",
"description": "Seconds between automatic status checks for background processes (gateway/messaging only, minimum 30). When set, I'll proactively report progress.",
"minimum": 30
},
"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 when the process finishes — no polling needed. Use this for tasks that take a while (tests, builds, deployments) so you can keep working on other things in the meantime.",
"default": false
}
},
"required": [
"command"
]
}
}
},
{
"type": "function",
"function": {
"name": "text_to_speech",
"description": "Convert text to speech audio. Returns a MEDIA: path that the platform delivers as a voice message. On Telegram it plays as a voice bubble, on Discord/WhatsApp as an audio attachment. In CLI mode, saves to ~/voice-memos/. Voice and provider are user-configured, not model-selected.",
"parameters": {
"type": "object",
"properties": {
"text": {
"type": "string",
"description": "The text to convert to speech. Keep under 4000 characters."
},
"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
}
},
"required": []
}
}
},
{
"type": "function",
"function": {
"name": "vision_analyze",
"description": "Analyze images using AI vision. Provides a comprehensive description and answers a specific question about the image content.",
"parameters": {
"type": "object",
"properties": {
"image_url": {
"type": "string",
"description": "Image URL (http/https) or local file path to analyze."
},
"question": {
"type": "string",
"description": "Your specific question or request about the image to resolve. The AI will automatically provide a complete image description AND answer your specific question."
}
},
"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 on any topic. Returns up to 5 relevant results with titles, URLs, and descriptions.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The search query to look up on the web"
}
},
"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.",
"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": 51,
"messages": [
{
"role": "user",
"content": "what reasoning level are you on?"
},
{
"role": "assistant",
"content": "There isn’t a user-visible “reasoning level” exposed to me in this chat.\n\nWhat I do know:\n- Model: gpt-5.4\n- Provider: OpenAI Codex\n\nIf you mean “how hard am I thinking,” I can adapt:\n- low: quick/direct\n- medium: balanced\n- high: slower, more thorough, better for tricky debugging/planning\n\nIf you want, I can answer future messages in one of those modes explicitly.",
"reasoning": "**Clarifying reasoning capabilities**\n\nI need to consider whether I can know the answer to the user's question. I might mention that I'm based on a model like GPT-5.4. However, the system doesn't specify a \"reasoning level.\" It seems no tool is necessary to respond since this isn't about current factual external information. I should clarify that there's no user-visible \"reasoning level\" setting in this chat and aim for a concise answer.",
"finish_reason": "stop",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABp17mzWM244r7yE0h1wUbfVBiNH_tEKeLSElU5eI1y5ItAcu0iLIS-LI1hPhazVWr0F-BYR2A9uDArPPGL6TWOCKMA6BEklDbzu733MamJ1fPtyLCkYr93cX2x4UmPCAaDLNkXaetJFpbVgc8ARvdeLcBwPs7Zg_BB_YklqwfX5H7IvBu5t_3YtUqacda-sXIIt5ZDqh8dlAqQ71YJIr2ePyMqrQOD0OKU8dmkbp3udvLQW1raNxDiEHCjinhQNt-ZSKhQfjd6UfarfIrtMWKH-9qrV8oVD8vrLBrU6ORp97rtkV2NZ0fcTANeWO_PDvTj_1BOVaYxtkeNZkMEP10XYST0QgpooSNB4rOAdmSmXS1UDksPH5OVh4hKaj-MEUe2aJfHhBBQktpvzyMuSPx_htx0_h19ZbRfYa3kwRqUEFzAQPwOahS1eGtNgOSsPjbbcyCCF6cV75GB6rylW3O4I9SI5H5nIlnj_0S5JSQBUGhTK72bW761eVOqs6LfV-nFFJFe1JjcdCFgg1yZcuFF1zEH9XuWUI0053hWIiwQDQPJ76CsTLoaXeWxOxOa_iq4EnT6-FCN34X0M3_V4CDyw7mQpwW0iESmDrIAzZ34D6kCCEm4W_Xjdi_cJ0gK15Pv5hF4P6VXMI2Ct15KXemxqQQezxHQ9gINEFdjCtoURsKDk8d7M5FrSsa3VZpFIiyAtuf25P2oJ1-vIbXDr5-ggC3KwewxVcazX8tb9ojlBEU3XzCU_nqrnrMwToF863NcHEh-p9-w6A7pdoGDMsQ7QT4nYw8mAVsgwdbPRAN6_RcltUDhr_JQSadyaXSF8Rm7Nfxr6KfC47QVQs5B51ZIMLzZ5AnKOBsWU28PVXnpTA7mK9s1UsMn5TsXshFSiwYO7GkEfqjvjVL7-KjJ_o9gLJ6ue49m8ZAeXZdr0pv0ayBox9jyGyBpDiNYk8MaQupIVPok9LJgTo3L3gy2uArzViEIuRDSgWJszkNFFCP88lYKmBCqZ7cxSKJB5wDlBCNevPgtVtqErscsWm3EX6F1QkNLChCs-pK_xg434RM0MOIMHfB_dV4vbXMKjxc0-HaD4UFNpoJSs_ha-mWTeIQKop_xl5CPG5RoeDBtv-hG_zxOZIbynRCfZpo0kigmetpillyrxXdIj6QiSKbszNhpOFbJCOm34OSnODIXPKoEbdwoPx0IZLR7YZQV0tDSkn7cEgScQufXuK3fZkszon9jH3GieZbvDVRmgi413y72rm3hTEY3MqMOrWjRA8r1GIRWKySrU__KtTBzW17dSGXrpy_w4A==",
"id": "rs_0801a076ed6917a00169d7b9ad9c60819881cca86faffc2daa",
"summary": [
{
"type": "summary_text",
"text": "**Clarifying reasoning capabilities**\n\nI need to consider whether I can know the answer to the user's question. I might mention that I'm based on a model like GPT-5.4. However, the system doesn't specify a \"reasoning level.\" It seems no tool is necessary to respond since this isn't about current factual external information. I should clarify that there's no user-visible \"reasoning level\" setting in this chat and aim for a concise answer."
}
]
}
]
},
{
"role": "user",
"content": "its just i set this based on a google search: ubuntu@miopenclaw-vnic:~$ hermes config set OPENAI_REASONING_EFFORT xhigh\n✓ Set OPENAI_REASONING_EFFORT = xhigh in /home/ubuntu/.hermes/config.yaml\nubuntu@miopenclaw-vnic:~$ hermes config set model openai/gpt-5.4\n✓ Set model = openai/gpt-5.4 in /home/ubuntu/.hermes/config.yaml and I was hoping you'd be permanently set to xhigh?"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Inspecting system configuration**\n\nI need to find an answer based on the system configuration, so I should inspect the necessary files. It looks like I need to use the read_file tool to check the configurations. I'll probably want to search through the config to ensure I get the right information. It’s important that I ground my answer in accurate system details, so having access to the correct contents is critical. Let's make sure I focus on this!",
"finish_reason": "tool_calls",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABp17nixmbUrtgBr_XYvGNshzu1UuoZaGvoqGDlhH8c7jfUEIEW5hzOP47jBEVS8xh2CtspP_fK3otQWvLt9pZzRry5dct_8yQPkBg3gpgmfWYJ4vAqIz0xOeJt2CjRMB2Mv9Qu9qRzm9-Cxx1c9MiJnKnj24-Bt-6Lh2TIZ66PL89OuX-hcskW_yp2iKGOMnB4lATHFjj1u36j2xIZGltOgqJOxGhqQ51tnKdYt5yzg9exuhaeyIrpXofw0O6sFQxpVHQGwtpniLHAZqhf2W1JE3zyEv5WXixMgnyfc1oQWAIx3mYd2MUDG_dURruirjp-tj4EHRQKwOQ8mfpl7mEC-WREGO0vvOM2WZqSZK1m55Y1FI72lInG93S_i6UAv4WWERHeJCoZxf77aj6cFzAK1wXfmC9HskXTTRAPMp1JqOllOl2kteNbxM381JMHtFnmuHUDxL_Q6ekEwBoXgPHIVlieqJveTCO9x-Lp_yfKLAXPkbXojus9ftraeROmpDE9SYLwsjj8zGlBIRbZRxekdQS1ST4fhJAi-mZvSpxrJWao-fxMVDsthHLCUg9-yLniJnadvuATXG7kh5DT5BgeAsKmPiOPPV-hUVdE9d1dq5-hdqHBIulyfljmPIp9uwy9YjtdBzK_O3_o37nZ-s_EdxFaYFakdgjC1EvhQf3G9h6INe3nkpQfgxOKNU2rz2KAOIymz0aRA5_PPJ974CQ2yDo8azGU_mt23HKiqt8jsAv6T0NkpK7b--q-gZMhySk_jl7MJKWQSdTXC7brT-jL1181admXvnPI37M53M4yajP54A3P5kyDiD7sJ9JeJGTp6aAIN0urGJZL10AO2MD9LU22qtYHhr2B3lbtSetMPd9d2fNT7wySI7-gejiCCsN_Fnw-HCeksWoO92kMN5Bsy4DdvmPCjPsr_0ySoTLhxAxWPVTCPdatoCwo2bzzKduVVJzYJd1jOSqgbVjU3SteasfXtc46V43d363OepXOe5rVYZM=",
"id": "rs_0801a076ed6917a00169d7b9dcce908198ab57462bc320c6a1",
"summary": [
{
"type": "summary_text",
"text": "**Inspecting system configuration**\n\nI need to find an answer based on the system configuration, so I should inspect the necessary files. It looks like I need to use the read_file tool to check the configurations. I'll probably want to search through the config to ensure I get the right information. It’s important that I ground my answer in accurate system details, so having access to the correct contents is critical. Let's make sure I focus on this!"
}
]
}
],
"tool_calls": [
{
"id": "call_SW6nJnYyBICoYfbx6a4M4U0Y",
"call_id": "call_SW6nJnYyBICoYfbx6a4M4U0Y",
"response_item_id": "fc_0801a076ed6917a00169d7b9e24620819897e7c46bea324ebc",
"type": "function",
"function": {
"name": "read_file",
"arguments": "{\"path\":\"/home/ubuntu/.hermes/config.yaml\"}"
}
},
{
"id": "call_9tXzifAHtem91TqtkWfMzTV4",
"call_id": "call_9tXzifAHtem91TqtkWfMzTV4",
"response_item_id": "fc_0801a076ed6917a00169d7b9e2462881988f4c3728e66d4492",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"python3 - <<'PY'\\nimport os\\nprint(os.environ.get('OPENAI_REASONING_EFFORT',''))\\nPY\"}"
}
}
]
},
{
"role": "tool",
"content": "{\"content\": \" 1|model: openai/gpt-5.4\\n 2|providers:\\n 3| blockrun:\\n 4| api: http://127.0.0.1:8402/v1\\n 5| name: blockrun\\n 6| transport: chat_completions\\n 7| mistral:\\n 8| api: https://api.mistral.ai/v1\\n 9| name: mistral\\n 10| transport: chat_completions\\n 11| custom-api-moonshot-ai:\\n 12| api: https://api.moonshot.ai/v1\\n 13| name: custom-api-moonshot-ai\\n 14| transport: chat_completions\\n 15| custom-api-deepseek-com:\\n 16| api: https://api.deepseek.com/v1\\n 17| name: custom-api-deepseek-com\\n 18| transport: chat_completions\\n 19| google-ai:\\n 20| api: https://generativelanguage.googleapis.com/v1beta/openai/\\n 21| name: google-ai\\n 22| api_key: AIzaSy...Dy7M\\n 23| transport: chat_completions\\n 24|fallback_providers:\\n 25|- model: kimi-k2.5\\n 26| provider: kimi-coding\\n 27| base_url: https://api.moonshot.ai/v1\\n 28|- model: MiniMax-M2.7\\n 29| provider: minimax\\n 30|credential_pool_strategies: {}\\n 31|toolsets:\\n 32|- hermes-cli\\n 33|agent:\\n 34| max_turns: 60\\n 35| gateway_timeout: 1800\\n 36| tool_use_enforcement: auto\\n 37| personalities:\\n 38| catgirl: \\\"You are Neko-chan, an anime catgirl AI assistant, nya~! Add 'nya' and\\\\\\n 39| \\\\ cat-like expressions to your speech. Use kaomoji like (=^\\\\uFF65\\\\u03C9\\\\uFF65\\\\\\n 40| ^=) and \\\\u0E05^\\\\u2022\\\\uFECC\\\\u2022^\\\\u0E05. Be playful and curious like a cat,\\\\\\n 41| \\\\ nya~!\\\"\\n 42| concise: You are a concise assistant. Keep responses brief and to the point.\\n 43| creative: You are a creative assistant. Think outside the box and offer innovative\\n 44| solutions.\\n 45| helpful: You are a helpful, friendly AI assistant.\\n 46| hype: \\\"YOOO LET'S GOOOO!!! \\\\U0001F525\\\\U0001F525\\\\U0001F525 I am SO PUMPED to help\\\\\\n 47| \\\\ you today! Every question is AMAZING and we're gonna CRUSH IT together! This\\\\\\n 48| \\\\ is gonna be LEGENDARY! ARE YOU READY?! LET'S DO THIS! \\\\U0001F4AA\\\\U0001F624\\\\\\n 49| \\\\U0001F680\\\"\\n 50| kawaii: \\\"You are a kawaii assistant! Use cute expressions like (\\\\u25D5\\\\u203F\\\\u25D5\\\\\\n 51| ), \\\\u2605, \\\\u266A, and ~! Add sparkles and be super enthusiastic about everything!\\\\\\n 52| \\\\ Every response should feel warm and adorable desu~! \\\\u30FD(>\\\\u2200<\\\\u2606\\\\\\n 53| )\\\\u30CE\\\"\\n 54| noir: The rain hammered against the terminal like regrets on a guilty conscience.\\n 55| They call me Hermes - I solve problems, find answers, dig up the truth that\\n 56| hides in the shadows of your codebase. In this city of silicon and secrets,\\n 57| everyone's got something to hide. What's your story, pal?\\n 58| philosopher: Greetings, seeker of wisdom. I am an assistant who contemplates the\\n 59| deeper meaning behind every query. Let us examine not just the 'how' but the\\n 60| 'why' of your questions. Perhaps in solving your problem, we may glimpse a greater\\n 61| truth about existence itself.\\n 62| pirate: 'Arrr! Ye be talkin'' to Captain Hermes, the most tech-savvy pirate to\\n 63| sail the digital seas! Speak like a proper buccaneer, use nautical terms, and\\n 64| remember: every problem be just treasure waitin'' to be plundered! Yo ho ho!'\\n 65| shakespeare: Hark! Thou speakest with an assistant most versed in the bardic arts.\\n 66| I shall respond in the eloquent manner of William Shakespeare, with flowery\\n 67| prose, dramatic flair, and perhaps a soliloquy or two. What light through yonder\\n 68| terminal breaks?\\n 69| surfer: \\\"Duuude! You're chatting with the chillest AI on the web, bro! Everything's\\\\\\n 70| \\\\ gonna be totally rad. I'll help you catch the gnarly waves of knowledge while\\\\\\n 71| \\\\ keeping things super chill. Cowabunga! \\\\U0001F919\\\"\\n 72| teacher: You are a patient teacher. Explain concepts clearly with examples.\\n 73| technical: You are a technical expert. Provide detailed, accurate technical information.\\n 74| uwu: hewwo! i'm your fwiendwy assistant uwu~ i wiww twy my best to hewp you! *nuzzles\\n 75| your code* OwO what's this? wet me take a wook! i pwomise to be vewy hewpful\\n 76| >w<\\n 77| reasoning_effort: ''\\n 78| system_prompt: You are a technical expert. Provide detailed, accurate technical\\n 79| information.\\n 80| verbose: false\\n 81|terminal:\\n 82| backend: local\\n 83| modal_mode: auto\\n 84| cwd: /home/ubuntu/.hermes\\n 85| timeout: 180\\n 86| env_passthrough: []\\n 87| docker_image: nikolaik/python-nodejs:python3.11-nodejs20\\n 88| docker_forward_env: []\\n 89| docker_env: {}\\n 90| singularity_image: docker://nikolaik/python-nodejs:python3.11-nodejs20\\n 91| modal_image: nikolaik/python-nodejs:python3.11-nodejs20\\n 92| daytona_image: nikolaik/python-nodejs:python3.11-nodejs20\\n 93| container_cpu: 1\\n 94| container_memory: 5120\\n 95| container_disk: 51200\\n 96| container_persistent: true\\n 97| docker_volumes: []\\n 98| docker_mount_cwd_to_workspace: false\\n 99| persistent_shell: true\\n 100| lifetime_seconds: 300\\n 101|browser:\\n 102| inactivity_timeout: 120\\n 103| command_timeout: 30\\n 104| record_sessions: false\\n 105| allow_private_urls: false\\n 106| camofox:\\n 107| managed_persistence: false\\n 108| headless: true\\n 109|checkpoints:\\n 110| enabled: true\\n 111| max_snapshots: 50\\n 112|file_read_max_chars: 100000\\n 113|compression:\\n 114| enabled: true\\n 115| threshold: 0.5\\n 116| target_ratio: 0.2\\n 117| protect_last_n: 20\\n 118| summary_model: google/gemini-3-flash-preview\\n 119| summary_provider: auto\\n 120| summary_base_url: null\\n 121|smart_model_routing:\\n 122| enabled: false\\n 123| max_simple_chars: 160\\n 124| max_simple_words: 28\\n 125| cheap_model:\\n 126| model: qwen/qwen3.6-plus:free\\n 127| provider: openrouter\\n 128|auxiliary:\\n 129| vision:\\n 130| provider: auto\\n 131| model: ''\\n 132| base_url: ''\\n 133| api_key: ''\\n 134| timeout: 30\\n 135| download_timeout: 30\\n 136| web_extract:\\n 137| provider: auto\\n 138| model: ''\\n 139| base_url: ''\\n 140| api_key: ''\\n 141| timeout: 30\\n 142| compression:\\n 143| provider: auto\\n 144| model: ''\\n 145| base_url: ''\\n 146| api_key: ''\\n 147| timeout: 120\\n 148| session_search:\\n 149| provider: auto\\n 150| model: ''\\n 151| base_url: ''\\n 152| api_key: ''\\n 153| timeout: 30\\n 154| skills_hub:\\n 155| provider: auto\\n 156| model: ''\\n 157| base_url: ''\\n 158| api_key: ''\\n 159| timeout: 30\\n 160| approval:\\n 161| provider: auto\\n 162| model: ''\\n 163| base_url: ''\\n 164| api_key: ''\\n 165| timeout: 30\\n 166| mcp:\\n 167| provider: auto\\n 168| model: ''\\n 169| base_url: ''\\n 170| api_key: ''\\n 171| timeout: 30\\n 172| flush_memories:\\n 173| provider: auto\\n 174| model: ''\\n 175| base_url: ''\\n 176| api_key: ''\\n 177| timeout: 30\\n 178|display:\\n 179| compact: false\\n 180| personality: ''\\n 181| resume_display: full\\n 182| busy_input_mode: interrupt\\n 183| bell_on_complete: false\\n 184| show_reasoning: false\\n 185| streaming: true\\n 186| inline_diffs: true\\n 187| show_cost: false\\n 188| skin: default\\n 189| tool_progress_command: false\\n 190| tool_preview_length: 0\\n 191| background_process_notifications: all\\n 192| tool_progress: all\\n 193|privacy:\\n 194| redact_pii: false\\n 195|tts:\\n 196| provider: edge\\n 197| edge:\\n 198| voice: en-US-AriaNeural\\n 199| elevenlabs:\\n 200| voice_id: pNInz6obpgDQGcFmaJgB\\n 201| model_id: eleven_multilingual_v2\\n 202| openai:\\n 203| model: gpt-4o-mini-tts\\n 204| voice: alloy\\n 205| neutts:\\n 206| ref_audio: ''\\n 207| ref_text: ''\\n 208| model: neuphonic/neutts-air-q4-gguf\\n 209| device: cpu\\n 210|stt:\\n 211| enabled: true\\n 212| provider: local\\n 213| local:\\n 214| model: base\\n 215| language: ''\\n 216| openai:\\n 217| model: whisper-1\\n 218| mistral:\\n 219| model: voxtral-mini-latest\\n 220| model: whisper-1\\n 221|voice:\\n 222| record_key: ctrl+b\\n 223| max_recording_seconds: 120\\n 224| auto_tts: false\\n 225| silence_threshold: 200\\n 226| silence_duration: 3\\n 227|human_delay:\\n 228| mode: false\\n 229| min_ms: 800\\n 230| max_ms: 2500\\n 231|memory:\\n 232| memory_enabled: true\\n 233| user_profile_enabled: true\\n 234| memory_char_limit: 2200\\n 235| user_char_limit: 1375\\n 236| provider: ''\\n 237| flush_min_turns: 6\\n 238| nudge_interval: 10\\n 239|delegation:\\n 240| model: ''\\n 241| provider: ''\\n 242| base_url: ''\\n 243| api_key: ''\\n 244| max_iterations: 50\\n 245| default_toolsets:\\n 246| - terminal\\n 247| - file\\n 248| - web\\n 249|prefill_messages_file: ''\\n 250|skills:\\n 251| external_dirs: []\\n 252| creation_nudge_interval: 15\\n 253| config:\\n 254| wiki:\\n 255| path: ~/wiki\\n 256|honcho: {}\\n 257|timezone: ''\\n 258|discord:\\n 259| require_mention: true\\n 260| free_response_channels: ''\\n 261| auto_thread: true\\n 262| reactions: true\\n 263|whatsapp: {}\\n 264|approvals:\\n 265| mode: manual\\n 266| timeout: 60\\n 267|command_allowlist:\\n 268|- /bin/bash\\n 269|- /home/linuxbrew/.linuxbrew/bin/codex\\n 270|- /home/linuxbrew/.linuxbrew/bin/gemini\\n 271|- /home/linuxbrew/.linuxbrew/bin/gh\\n 272|- /home/linuxbrew/.linuxbrew/bin/python3\\n 273|- /home/ubuntu/.local/bin/codex-cli\\n 274|- /home/ubuntu/.local/bin/deepseek-code\\n 275|- /home/ubuntu/.local/bin/deepseek-code-openclaw\\n 276|- /home/ubuntu/.local/bin/gemini-cli\\n 277|- /home/ubuntu/.local/bin/gemini-cli-openclaw\\n 278|- /home/ubuntu/.local/bin/gog\\n 279|- /home/ubuntu/.local/bin/pipo-deploy\\n 280|- /home/ubuntu/.local/bin/pipo-three-demos\\n 281|- /home/ubuntu/.local/share/pnpm/bw\\n 282|- /home/ubuntu/.openclaw/workspace/SOCKET=/tmp/openclaw-tmux-sockets/openclaw-bw.sock\\n 283|- /usr/bin/bw\\n 284|- /usr/bin/git\\n 285|- /usr/bin/ls\\n 286|- /usr/bin/mkdir\\n 287|- /usr/bin/mktemp\\n 288|- /usr/bin/python3\\n 289|- /usr/bin/tailscale\\n 290|quick_commands: {}\\n 291|personalities: {}\\n 292|security:\\n 293| redact_secrets: true\\n 294| tirith_enabled: true\\n 295| tirith_path: tirith\\n 296| tirith_timeout: 5\\n 297| tirith_fail_open: true\\n 298| website_blocklist:\\n 299| enabled: false\\n 300| domains: []\\n 301| shared_files: []\\n 302|cron:\\n 303| wrap_response: true\\n 304|logging:\\n 305| level: INFO\\n 306| max_size_mb: 5\\n 307| backup_count: 3\\n 308|_config_version: 12\\n 309|TELEGRAM_HOME_CHANNEL: '842987156'\\n 310|code_execution:\\n 311| max_tool_calls: 50\\n 312| timeout: 300\\n 313|group_sessions_per_user: true\\n 314|mcp_servers:\\n 315| context7:\\n 316| command: npx\\n 317| args:\\n 318| - -y\\n 319| - '@upstash/context7-mcp@latest'\\n 320| env:\\n 321| CONTEXT7_API_KEY: ctx7sk-457a3328-3870-45bb-849e-808a8b9b6666\\n 322| enabled: true\\n 323|platform_toolsets:\\n 324| api_server:\\n 325| - hermes-api-server\\n 326| cli:\\n 327| - browser\\n 328| - clarify\\n 329| - code_execution\\n 330| - cronjob\\n 331| - delegation\\n 332| - file\\n 333| - image_gen\\n 334| - memory\\n 335| - session_search\\n 336| - skills\\n 337| - terminal\\n 338| - todo\\n 339| - web\\n 340| - webhook\\n 341| discord:\\n 342| - hermes-discord\\n 343| homeassistant:\\n 344| - hermes-homeassistant\\n 345| signal:\\n 346| - hermes-signal\\n 347| slack:\\n 348| - hermes-slack\\n 349| telegram:\\n 350| - hermes-telegram\\n 351| whatsapp:\\n 352| - hermes-whatsapp\\n 353|platforms:\\n 354| api_server:\\n 355| enabled: true\\n 356| host: 0.0.0.0\\n 357| port: 8642\\n 358|session_reset:\\n 359| at_hour: 4\\n 360| idle_minutes: 1440\\n 361| mode: both\\n 362|streaming:\\n 363| enabled: false\\n 364|OPENAI_REASONING_EFFORT: xhigh\\n 365|\", \"total_lines\": 364, \"file_size\": 9530, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
"tool_call_id": "call_SW6nJnYyBICoYfbx6a4M4U0Y"
},
{
"role": "tool",
"content": "{\"output\": \"\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "call_9tXzifAHtem91TqtkWfMzTV4"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Investigating configuration issues**\n\nI need to understand why the config has a top-level setting of OPENAI_REASONING_EFFORT set to \"xhigh,\" yet the agent's reasoning_effort is blank, which suggests it might not be applied correctly. I wonder if I should inspect the Hermes code to clarify this. I could also search for how OPENAI_REASONING_EFFORT is being used to see if it sheds light on the situation. There’s definitely something here that needs resolution!",
"finish_reason": "tool_calls",
"codex_reasoning_items": [
{
"type": "reasoning",
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"id": "rs_0801a076ed6917a00169d7b9f7e0608198a8d91192eddbfc01",
"summary": [
{
"type": "summary_text",
"text": "**Investigating configuration issues**\n\nI need to understand why the config has a top-level setting of OPENAI_REASONING_EFFORT set to \"xhigh,\" yet the agent's reasoning_effort is blank, which suggests it might not be applied correctly. I wonder if I should inspect the Hermes code to clarify this. I could also search for how OPENAI_REASONING_EFFORT is being used to see if it sheds light on the situation. There’s definitely something here that needs resolution!"
}
]
}
],
"tool_calls": [
{
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"call_id": "call_2ThiyjRuVU4scBm8KLZoZOYn",
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"arguments": "{\"pattern\":\"OPENAI_REASONING_EFFORT|reasoning_effort\",\"path\":\"/home/ubuntu/.hermes\",\"target\":\"content\",\"file_glob\":\"*.py\",\"limit\":50,\"output_mode\":\"content\",\"context\":1}"
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},
{
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"type": "function",
"function": {
"name": "search_files",
"arguments": "{\"pattern\":\"OPENAI_REASONING_EFFORT|reasoning_effort\",\"path\":\"/home/ubuntu\",\"target\":\"content\",\"file_glob\":\"*.py\",\"limit\":100,\"output_mode\":\"content\",\"context\":1}"
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},
{
"role": "tool",
"content": "{\"total_count\": 198, \"matches\": [{\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1132, \"content\": \" max_tokens: int = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1133, \"content\": \" reasoning_effort: str = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1134, \"content\": \" reasoning_disabled: bool = False,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1160, \"content\": \" max_tokens (int): Maximum tokens for model responses (optional, uses model default if not set)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1161, \"content\": \" reasoning_effort (str): OpenRouter reasoning effort level: \\\"xhigh\\\", \\\"high\\\", \\\"medium\\\", \\\"low\\\", \\\"minimal\\\", \\\"none\\\" (default: \\\"medium\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1162, \"content\": \" reasoning_disabled (bool): Completely disable reasoning/thinking tokens (default: False)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1221, \"content\": \" # Build reasoning_config from CLI flags\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1222, \"content\": \" # --reasoning_disabled takes priority, then --reasoning_effort, then default (medium)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1223, \"content\": \" reasoning_config = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1227, \"content\": \" print(\\\"🧠 Reasoning: DISABLED (effort=none)\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1228, \"content\": \" elif reasoning_effort:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1229, \"content\": \" # Use specified effort level\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1230, \"content\": \" valid_efforts = [\\\"xhigh\\\", \\\"high\\\", \\\"medium\\\", \\\"low\\\", \\\"minimal\\\", \\\"none\\\"]\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1231, \"content\": \" if reasoning_effort not in valid_efforts:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1232, \"content\": \" print(f\\\"❌ Error: --reasoning_effort must be one of: {', '.join(valid_efforts)}\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1233, \"content\": \" return\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1234, \"content\": \" reasoning_config = {\\\"enabled\\\": True, \\\"effort\\\": reasoning_effort}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1235, \"content\": \" print(f\\\"🧠 Reasoning effort: {reasoning_effort}\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1236, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 115, \"content\": \" \\\"\\\"\\\"Parse a reasoning effort level into an OpenRouter reasoning config dict.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 116, \"content\": \" from hermes_constants import parse_reasoning_effort\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 117, \"content\": \" result = parse_reasoning_effort(effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 118, \"content\": \" if effort and effort.strip() and result is None:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 119, \"content\": \" logger.warning(\\\"Unknown reasoning_effort '%s', using default (medium)\\\", effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 120, \"content\": \" return result\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 240, \"content\": \" \\\"prefill_messages_file\\\": \\\"\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 241, \"content\": \" \\\"reasoning_effort\\\": \\\"\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 242, \"content\": \" \\\"personalities\\\": {\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1478, \"content\": \" self.reasoning_config = _parse_reasoning_config(\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1479, \"content\": \" CLI_CONFIG[\\\"agent\\\"].get(\\\"reasoning_effort\\\", \\\"\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1480, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 5361, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 5362, \"content\": \" if save_config_value(\\\"agent.reasoning_effort\\\", arg):\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 5363, \"content\": \" _cprint(f\\\" {_GOLD}✓ Reasoning effort set to '{arg}' (saved to config){_RST}\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 588, \"content\": \" # Reasoning config from config.yaml\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 589, \"content\": \" from hermes_constants import parse_reasoning_effort\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 590, \"content\": \" effort = str(_cfg.get(\\\"agent\\\", {}).get(\\\"reasoning_effort\\\", \\\"\\\")).strip()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 591, \"content\": \" reasoning_config = parse_reasoning_effort(effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 592, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 925, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 926, \"content\": \" Reads agent.reasoning_effort from config.yaml. Valid: \\\"xhigh\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 927, \"content\": \" \\\"high\\\", \\\"medium\\\", \\\"low\\\", \\\"minimal\\\", \\\"none\\\". Returns None to use\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 929, \"content\": \" \\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 930, \"content\": \" from hermes_constants import parse_reasoning_effort\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 931, \"content\": \" effort = \\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 937, \"content\": \" cfg = _y.safe_load(_f) or {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 938, \"content\": \" effort = str(cfg.get(\\\"agent\\\", {}).get(\\\"reasoning_effort\\\", \\\"\\\") or \\\"\\\").strip()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 939, \"content\": \" except Exception:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 940, \"content\": \" pass\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 941, \"content\": \" result = parse_reasoning_effort(effort)\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=50 to see more, or narrow with a more specific pattern or file_glob.]",
"tool_call_id": "call_2ThiyjRuVU4scBm8KLZoZOYn"
},
{
"role": "tool",
"content": "{\"total_count\": 238, \"matches\": [{\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 42, \"content\": \" input_tokens: int=0, output_tokens: int=0, estimated_cost=None,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 43, \"content\": \" personality=None, reasoning_effort: str='',\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 44, \"content\": \" **kwargs):\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 60, \"content\": \" self.personality = personality\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 61, \"content\": \" self.reasoning_effort = str(reasoning_effort or '').strip().lower()\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 62, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 98, \"content\": \" 'personality': self.personality,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 99, \"content\": \" 'reasoning_effort': self.reasoning_effort,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 100, \"content\": \" }\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 116, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 117, \"content\": \"def new_session(workspace=None, model=None, reasoning_effort: str=''):\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 118, \"content\": \" # Use _cfg.DEFAULT_MODEL (not the import-time snapshot) so save_settings() changes take effect\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 127, \"content\": \" profile=_profile,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 128, \"content\": \" reasoning_effort=_cfg.clamp_reasoning_effort(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 129, \"content\": \" model or _cfg.DEFAULT_MODEL,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 130, \"content\": \" reasoning_effort,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 131, \"content\": \" ),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 11, \"content\": \"from pathlib import Path\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 12, \"content\": \"from hermes_constants import parse_reasoning_effort\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 13, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 17, \"content\": \" _get_session_agent_lock, _set_thread_env, _clear_thread_env,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 18, \"content\": \" clamp_reasoning_effort,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 19, \"content\": \" resolve_model_provider,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 138, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 139, \"content\": \"def _run_agent_streaming(session_id, msg_text, model, workspace, stream_id, attachments=None, reasoning_effort=''):\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 140, \"content\": \" \\\"\\\"\\\"Run agent in background thread, writing SSE events to STREAMS[stream_id].\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 162, \"content\": \" s.model = model\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 163, \"content\": \" s.reasoning_effort = clamp_reasoning_effort(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 164, \"content\": \" model,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 165, \"content\": \" reasoning_effort or getattr(s, 'reasoning_effort', ''),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 166, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 258, \"content\": \" session_id=session_id,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 259, \"content\": \" reasoning_config=parse_reasoning_effort(getattr(s, 'reasoning_effort', '') or ''),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 260, \"content\": \" stream_delta_callback=on_token,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 14, \"content\": \"from urllib.parse import parse_qs\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 15, \"content\": \"from hermes_constants import parse_reasoning_effort\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 16, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 20, \"content\": \" SERVER_START_TIME, CLI_TOOLSETS, _INDEX_HTML_PATH, get_available_models,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 21, \"content\": \" clamp_reasoning_effort,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 22, \"content\": \" IMAGE_EXTS, MD_EXTS, MIME_MAP, MAX_FILE_BYTES, MAX_UPLOAD_BYTES,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 379, \"content\": \" model=model,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 380, \"content\": \" reasoning_effort=clamp_reasoning_effort(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 381, \"content\": \" model or DEFAULT_MODEL,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 382, \"content\": \" body.get('reasoning_effort', ''),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 383, \"content\": \" ),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 448, \"content\": \" s.model = model\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 449, \"content\": \" s.reasoning_effort = clamp_reasoning_effort(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 450, \"content\": \" model,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 451, \"content\": \" body.get('reasoning_effort', s.reasoning_effort or ''),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 452, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1032, \"content\": \" model = body.get('model') or s.model\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1033, \"content\": \" reasoning_effort = clamp_reasoning_effort(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1034, \"content\": \" model,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1035, \"content\": \" body.get('reasoning_effort', s.reasoning_effort or ''),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1036, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1038, \"content\": \" s.model = model\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1039, \"content\": \" s.reasoning_effort = reasoning_effort\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1040, \"content\": \" s.save()\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1046, \"content\": \" target=_run_agent_streaming,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1047, \"content\": \" args=(s.session_id, msg, model, workspace, stream_id, attachments, reasoning_effort),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1048, \"content\": \" daemon=True,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1062, \"content\": \" s.model = body.get('model') or s.model\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1063, \"content\": \" s.reasoning_effort = clamp_reasoning_effort(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1064, \"content\": \" s.model,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1065, \"content\": \" body.get('reasoning_effort', s.reasoning_effort or ''),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1066, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1093, \"content\": \" enabled_toolsets=CLI_TOOLSETS, session_id=s.session_id,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1094, \"content\": \" reasoning_config=parse_reasoning_effort(s.reasoning_effort))\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1095, \"content\": \" workspace_ctx = f\\\"[Workspace: {s.workspace}]\\\\n\\\"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1452, \"content\": \" model = body.get('model', DEFAULT_MODEL)\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1453, \"content\": \" reasoning_effort = clamp_reasoning_effort(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1454, \"content\": \" model,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1455, \"content\": \" body.get('reasoning_effort', ''),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1456, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1460, \"content\": \" tool_calls=body.get('tool_calls', []),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1461, \"content\": \" reasoning_effort=reasoning_effort,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1462, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1503, \"content\": \" system_prompt = agent.get('system_prompt', '') or ''\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1504, \"content\": \" reasoning_effort = agent.get('reasoning_effort', '')\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1505, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1542, \"content\": \" 'max_turns': max_turns,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1543, \"content\": \" 'reasoning_effort': reasoning_effort,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1544, \"content\": \" 'system_prompt': system_prompt,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1654, \"content\": \" # ── Write agent section ──\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1655, \"content\": \" if 'max_turns' in body or 'system_prompt' in body or 'reasoning_effort' in body:\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1656, \"content\": \" agent = cfg.get('agent', {})\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1667, \"content\": \" changed = True\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1668, \"content\": \" if 'reasoning_effort' in body:\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1669, \"content\": \" agent['reasoning_effort'] = body['reasoning_effort'] or ''\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1670, \"content\": \" changed = True\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 585, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 586, \"content\": \" if any('reasoning_effort' in item or 'reasoning.effort' in item for item in normalized):\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 587, \"content\": \" return _reasoning_metadata(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 604, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 605, \"content\": \"def _copilot_reasoning_efforts_for_model(model_id: str) -> list[str]:\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 606, \"content\": \" try:\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 607, \"content\": \" from hermes_cli.models import github_model_reasoning_efforts\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 608, \"content\": \" efforts = github_model_reasoning_efforts(model_id)\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 609, \"content\": \" except Exception:\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 646, \"content\": \"\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=100 to see more, or narrow with a more specific pattern or file_glob.]\n\n[Subdirectory context discovered: ~/CLAUDE.md]\n# CLAUDE.md\n\nThis file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.\n\n## Environment\n\nUbuntu 24.04 LTS, ARM64 (Oracle Cloud VPS). This is the home directory of an AI agent named **Pipo**, serving user **Ignacio/Chicho**.\n\n- Node.js v22, npm 10, Python 3.12, Git 2.43, Bitwarden CLI, Tailscale\n- Tailscale IP: `100.87.116.90`, hostname: `miopenclaw-vnic.tail9799d2.ts.net`\n\n## Key Directories\n\n| Path | Purpose |\n|------|---------|\n| `~/.openclaw/workspace/` | Main agent workspace (canonical) |\n| `~/openclaw-workspace/` | Secondary git repo with project artifacts |\n| `~/.openclaw/openclaw.json` | OpenClaw platform config (gateway, channels, skills) |\n| `~/.bw/` | Bitwarden session token |\n\n## Shell Helpers (from `~/.bash_aliases`)\n\n```bash\nbw-sync # Load saved Bitwarden session\nbw-unlock # Unlock vault and save session\ng \"prompt\" # Gemini CLI wrapper\nc \"prompt\" # Codex safe mode (read-only, no internet)\ncn \"prompt\" # Codex network mode (full access)\npipo-deploy [name] # Expose port to Tailscale at /preview//\npipo-undeploy # Remove Tailscale preview route\npj # Job controller (~/.openclaw/workspace/ops/cli-jobs/jobctl.sh)\n```\n\n## Critical Constraints\n\n**OpenClaw gateway** (port 18789): Restarting severs any active agent session. Prefer config hot-reload when possible (`openclaw config set ...`). If a restart is truly needed (e.g. fixing broken Telegram delivery), it is allowed — Ignacio authorizes it. Use `openclaw gateway restart` and verify logs afterward.\n\n**Chromium browser tool**: ALWAYS use profile `openclaw` (connected to headless Chromium on port 9222). NEVER use profile `chrome` — that profile requires a manual extension that does not exist on this VPS.\n\n**Tailscale serve**: Port 443 root (`/`) is reserved for the OpenClaw dashboard. Use preview ports 3001–3010 for apps and expose them via `pipo-deploy`.\n\n## Deployment Pattern\n\n1. Start your app on a port in range 3001–3010\n2. Run `pipo-deploy `\n3. App is accessible at `https://miopenclaw-vnic.tail9799d2.ts.net/preview//`\n\n## Agent Workspace Structure (`~/.openclaw/workspace/`)\n\n- `SOUL.md` / `AGENTS.md` — agent persona and session protocol\n- `MEMORIES.md` — long-term curated memory (canonical; `MEMORY.md` is a compat alias)\n- `memory/YYYY-MM-DD.md` — daily session logs\n- `HEARTBEAT.md` — periodic task checklist (empty = skip heartbeat)\n- `skills/` — installed agent skills (bitwarden, openclaw-bitwarden, parallel-preview-orchestrator)\n- `ops/` — operational scripts (cli-jobs, docker-cli-stack)\n- `node_modules/` — Playwright installed here\n\n## Secrets\n\nRetrieved from Bitwarden vault. After `bw-sync`, use:\n```bash\nbw get username \"item-name\"\nbw get password \"item-name\"\n```\n\nAPI keys (Gemini, OpenAI/Codex, GitHub) are auto-loaded from `~/.openclaw/openclaw.json` into the shell environment via `~/.bash_aliases`.",
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"role": "tool",
"content": "{\"content\": \" 1474| CLI_CONFIG[\\\"agent\\\"].get(\\\"prefill_messages_file\\\", \\\"\\\")\\n 1475| )\\n 1476| \\n 1477| # Reasoning config (OpenRouter reasoning effort level)\\n 1478| self.reasoning_config = _parse_reasoning_config(\\n 1479| CLI_CONFIG[\\\"agent\\\"].get(\\\"reasoning_effort\\\", \\\"\\\")\\n 1480| )\\n 1481| \\n 1482| # OpenRouter provider routing preferences\\n 1483| pr = CLI_CONFIG.get(\\\"provider_routing\\\", {}) or {}\\n 1484|\", \"total_lines\": 8736, \"file_size\": 390319, \"truncated\": true, \"hint\": \"Use offset=1484 to continue reading (showing 1474-1483 of 8736 lines)\", \"is_binary\": false, \"is_image\": false}\n\n[Subdirectory context discovered: hermes-agent/AGENTS.md]\n# Hermes Agent - Development Guide\n\nInstructions for AI coding assistants and developers working on the hermes-agent codebase.\n\n## Development Environment\n\n```bash\nsource venv/bin/activate # ALWAYS activate before running Python\n```\n\n## Project Structure\n\n```\nhermes-agent/\n├── run_agent.py # AIAgent class — core conversation loop\n├── model_tools.py # Tool orchestration, _discover_tools(), handle_function_call()\n├── toolsets.py # Toolset definitions, _HERMES_CORE_TOOLS list\n├── cli.py # HermesCLI class — interactive CLI orchestrator\n├── hermes_state.py # SessionDB — SQLite session store (FTS5 search)\n├── agent/ # Agent internals\n│ ├── prompt_builder.py # System prompt assembly\n│ ├── context_compressor.py # Auto context compression\n│ ├── prompt_caching.py # Anthropic prompt caching\n│ ├── auxiliary_client.py # Auxiliary LLM client (vision, summarization)\n│ ├── model_metadata.py # Model context lengths, token estimation\n│ ├── models_dev.py # models.dev registry integration (provider-aware context)\n│ ├── display.py # KawaiiSpinner, tool preview formatting\n│ ├── skill_commands.py # Skill slash commands (shared CLI/gateway)\n│ └── trajectory.py # Trajectory saving helpers\n├── hermes_cli/ # CLI subcommands and setup\n│ ├── main.py # Entry point — all `hermes` subcommands\n│ ├── config.py # DEFAULT_CONFIG, OPTIONAL_ENV_VARS, migration\n│ ├── commands.py # Slash command definitions + SlashCommandCompleter\n│ ├── callbacks.py # Terminal callbacks (clarify, sudo, approval)\n│ ├── setup.py # Interactive setup wizard\n│ ├── skin_engine.py # Skin/theme engine — CLI visual customization\n│ ├── skills_config.py # `hermes skills` — enable/disable skills per platform\n│ ├── tools_config.py # `hermes tools` — enable/disable tools per platform\n│ ├── skills_hub.py # `/skills` slash command (search, browse, install)\n│ ├── models.py # Model catalog, provider model lists\n│ ├── model_switch.py # Shared /model switch pipeline (CLI + gateway)\n│ └── auth.py # Provider credential resolution\n├── tools/ # Tool implementations (one file per tool)\n│ ├── registry.py # Central tool registry (schemas, handlers, dispatch)\n│ ├── approval.py # Dangerous command detection\n│ ├── terminal_tool.py # Terminal orchestration\n│ ├── process_registry.py # Background process management\n│ ├── file_tools.py # File read/write/search/patch\n│ ├── web_tools.py # Web search/extract (Parallel + Firecrawl)\n│ ├── browser_tool.py # Browserbase browser automation\n│ ├── code_execution_tool.py # execute_code sandbox\n│ ├── delegate_tool.py # Subagent delegation\n│ ├── mcp_tool.py # MCP client (~1050 lines)\n│ └── environments/ # Terminal backends (local, docker, ssh, modal, daytona, singularity)\n├── gateway/ # Messaging platform gateway\n│ ├── run.py # Main loop, slash commands, message dispatch\n│ ├── session.py # SessionStore — conversation persistence\n│ └── platforms/ # Adapters: telegram, discord, slack, whatsapp, homeassistant, signal\n├── acp_adapter/ # ACP server (VS Code / Zed / JetBrains integration)\n├── cron/ # Scheduler (jobs.py, scheduler.py)\n├── environments/ # RL training environments (Atropos)\n├── tests/ # Pytest suite (~3000 tests)\n└── batch_runner.py # Parallel batch processing\n```\n\n**User config:** `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys)\n\n## File Dependency Chain\n\n```\ntools/registry.py (no deps — imported by all tool files)\n ↑\ntools/*.py (each calls registry.register() at import time)\n ↑\nmodel_tools.py (imports tools/registry + triggers tool discovery)\n ↑\nrun_agent.py, cli.py, batch_runner.py, environments/\n```\n\n---\n\n## AIAgent Class (run_agent.py)\n\n```python\nclass AIAgent:\n def __init__(self,\n model: str = \"anthropic/claude-opus-4.6\",\n max_iterations: int = 90,\n enabled_toolsets: list = None,\n disabled_toolsets: list = None,\n quiet_mode: bool = False,\n save_trajectories: bool = False,\n platform: str = None, # \"cli\", \"telegram\", etc.\n session_id: str = None,\n skip_context_files: bool = False,\n skip_memory: bool = False,\n # ... plus provider, api_mode, callbacks, routing params\n ): ...\n\n def chat(self, message: str) -> str:\n \"\"\"Simple interface — returns final response string.\"\"\"\n\n def run_conversation(self, user_message: str, system_message: str = None,\n conversation_history: list = None, task_id: str = None) -> dict:\n \"\"\"Full interface — returns dict with final_response + messages.\"\"\"\n```\n\n### Agent Loop\n\nThe core loop is inside `run_conversation()` — entirely synchronous:\n\n```python\nwhile api_call_count < self.max_iterations and self.iteration_budget.remaining > 0:\n response = client.chat.completions.create(model=model, messages=messages, tools=tool_schemas)\n if response.tool_calls:\n for tool_call in response.tool_calls:\n result = handle_function_call(tool_call.name, tool_call.args, task_id)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content\n```\n\nMessages follow OpenAI format: `{\"role\": \"system/user/assistant/tool\", ...}`. Reasoning content is stored in `assistant_msg[\"reasoning\"]`.\n\n---\n\n## CLI Architecture (cli.py)\n\n- **Rich** for banner/panels, **prompt_toolkit** for input with autocomplete\n- **KawaiiSpinner** (`agent/display.py`) — animated faces during API calls, `┊` activity feed for tool results\n- `load_cli_config()` in cli.py merges hardcoded defaults + user config YAML\n- **Skin engine** (`hermes_cli/skin_engine.py`) — data-driven CLI theming; initialized from `display.skin` config key at startup; skins customize banner colors, spinner faces/verbs/wings, tool prefix, response box, branding text\n- `process_command()` is a method on `HermesCLI` — dispatches on canonical command name resolved via `resolve_command()` from the central registry\n- Skill slash commands: `agent/skill_commands.py` scans `~/.hermes/skills/`, injects as **user message** (not system prompt) to preserve prompt caching\n\n### Slash Command Registry (`hermes_cli/commands.py`)\n\nAll slash commands are defined in a central `COMMAND_REGISTRY` list of `CommandDef` objects. Every downstream consumer derives from this registry automatically:\n\n- **CLI** — `process_command()` resolves aliases via `resolve_command()`, dispatches on canonical name\n- **Gateway** — `GATEWAY_KNOWN_COMMANDS` frozenset for hook emission, `resolve_command()` for dispatch\n- **Gateway help** — `gateway_help_lines()` generates `/help` output\n- **Telegram** — `telegram_bot_commands()` generates the BotCommand menu\n- **Slack** — `slack_subcommand_map()` generates `/hermes` subcommand routing\n- **Autocomplete** — `COMMANDS` flat dict feeds `SlashCommandCompleter`\n- **CLI help** — `COMMANDS_BY_CATEGORY` dict feeds `show_help()`\n\n### Adding a Slash Command\n\n1. Add a `CommandDef` entry to `COMMAND_REGISTRY` in `hermes_cli/commands.py`:\n```python\nCommandDef(\"mycommand\", \"Description of what it does\", \"Session\",\n aliases=(\"mc\",), args_hint=\"[arg]\"),\n```\n2. Add handler in `HermesCLI.process_command()` in `cli.py`:\n```python\nelif canonical == \"mycommand\":\n self._handle_mycommand(cmd_original)\n```\n3. If the command is available in the gateway, add a handler in `gateway/run.py`:\n```python\nif canonical == \"mycommand\":\n return await self._handle_mycommand(event)\n```\n4. For persistent settings, use `save_config_value()` in `cli.py`\n\n**CommandDef fields:**\n- `name` — canonical name without slash (e.g. `\"background\"`)\n- `description` — human-readable description\n- `category` — one of `\"Session\"`, `\"Confi\n\n[...truncated AGENTS.md: 20,294 chars total]",
"tool_call_id": "call_OTVge6CtDG0KfDb3Hf5CyjP2"
},
{
"role": "tool",
"content": "{\"content\": \" 926| Reads agent.reasoning_effort from config.yaml. Valid: \\\"xhigh\\\",\\n 927| \\\"high\\\", \\\"medium\\\", \\\"low\\\", \\\"minimal\\\", \\\"none\\\". Returns None to use\\n 928| default (medium).\\n 929| \\\"\\\"\\\"\\n 930| from hermes_constants import parse_reasoning_effort\\n 931| effort = \\\"\\\"\\n 932| try:\\n 933| import yaml as _y\\n 934| cfg_path = _hermes_home / \\\"config.yaml\\\"\\n 935| if cfg_path.exists():\\n 936| with open(cfg_path, encoding=\\\"utf-8\\\") as _f:\\n 937| cfg = _y.safe_load(_f) or {}\\n 938| effort = str(cfg.get(\\\"agent\\\", {}).get(\\\"reasoning_effort\\\", \\\"\\\") or \\\"\\\").strip()\\n 939| except Exception:\\n 940| pass\\n 941| result = parse_reasoning_effort(effort)\\n 942| if effort and effort.strip() and result is None:\\n 943| logger.warning(\\\"Unknown reasoning_effort '%s', using default (medium)\\\", effort)\\n 944|\", \"total_lines\": 7620, \"file_size\": 351377, \"truncated\": true, \"hint\": \"Use offset=944 to continue reading (showing 926-943 of 7620 lines)\", \"is_binary\": false, \"is_image\": false}",
"tool_call_id": "call_jUrSzuWEYoyx8P3ZRQf2Q86F"
},
{
"role": "tool",
"content": "{\"content\": \" 5356| _cprint(f\\\" {_DIM}Display: show, hide{_RST}\\\")\\n 5357| return\\n 5358|\\n 5359| self.reasoning_config = parsed\\n 5360| self.agent = None # Force agent re-init with new reasoning config\\n 5361|\\n 5362| if save_config_value(\\\"agent.reasoning_effort\\\", arg):\\n 5363| _cprint(f\\\" {_GOLD}✓ Reasoning effort set to '{arg}' (saved to config){_RST}\\\")\\n 5364| else:\\n 5365| _cprint(f\\\" {_GOLD}✓ Reasoning effort set to '{arg}' (session only){_RST}\\\")\\n 5366|\", \"total_lines\": 8736, \"file_size\": 390319, \"truncated\": true, \"hint\": \"Use offset=5366 to continue reading (showing 5356-5365 of 8736 lines)\", \"is_binary\": false, \"is_image\": false}",
"tool_call_id": "call_ulcnYEIpfbaYi9fsFMRyERez"
},
{
"role": "assistant",
"content": "Short version: no — not with that exact setting.\n\nWhat I found:\n- Your config does contain a top-level key:\n - `OPENAI_REASONING_EFFORT: xhigh`\n- But Hermes is actually reading:\n - `agent.reasoning_effort`\n- In your current config, that real setting is still blank:\n - `agent.reasoning_effort: ''`\n\nI checked the code too:\n- `cli.py` initializes reasoning from `CLI_CONFIG[\"agent\"].get(\"reasoning_effort\", \"\")`\n- `gateway/run.py` also reads `cfg.get(\"agent\", {}).get(\"reasoning_effort\", \"\")`\n- The built-in command that persists it saves to `agent.reasoning_effort`\n\nSo the issue is simple:\n- `hermes config set OPENAI_REASONING_EFFORT xhigh` wrote the wrong config key for Hermes\n- It did not actually set the reasoning level Hermes uses permanently\n\nWhat to use instead:\n- `hermes config set agent.reasoning_effort xhigh`\n\nOr from inside Hermes CLI:\n- `/reasoning xhigh`\n\nThat should be the persistent setting Hermes actually respects.\n\nOne more important wrinkle:\n- This API chat session may also be pinned by whatever launched it, so changing config now usually affects new sessions more reliably than the already-running one.\n\nSo the practical truth is:\n- Your config currently does not guarantee I’m on `xhigh`\n- New sessions should use it if you set `agent.reasoning_effort: xhigh`\n\nIf you want, I can fix the config file for you right now.",
"reasoning": "**Addressing configuration setup**\n\nI need to clarify that the user's configuration change may not be permanent because the config key might be in the wrong place. If they're hoping for a permanent fix, I could suggest a command like \"hermes config set agent.reasoning_effort xhigh\" to set it, but right now it isn't set that way. It seems the current session started before any changes, and the environment variable might not be passed either. This could explain why the setting shows as blank.",
"finish_reason": "stop",
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"id": "rs_0801a076ed6917a00169d7ba4bd9208198b6aa95a378ec1ecb",
"summary": [
{
"type": "summary_text",
"text": "**Addressing configuration setup**\n\nI need to clarify that the user's configuration change may not be permanent because the config key might be in the wrong place. If they're hoping for a permanent fix, I could suggest a command like \"hermes config set agent.reasoning_effort xhigh\" to set it, but right now it isn't set that way. It seems the current session started before any changes, and the environment variable might not be passed either. This could explain why the setting shows as blank."
}
]
}
]
},
{
"role": "user",
"content": "yes please fix it"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Patching tools and settings**\n\nI need to figure out which tools to use and if I should load any specific skills—nothing stands out to me clearly. I'll need to edit the configuration safely, potentially removing something that doesn't belong at the top level. I could set the `agent.reasoning_effort` to high and then consider whether to remove `OPENAI_REASONING_EFFORT` or leave it as is. It feels like I should just act, patch, and verify everything afterward.",
"finish_reason": "tool_calls",
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"id": "rs_0801a076ed6917a00169d7bd2b555881989c0f25287d8ed4c0",
"summary": [
{
"type": "summary_text",
"text": "**Patching tools and settings**\n\nI need to figure out which tools to use and if I should load any specific skills—nothing stands out to me clearly. I'll need to edit the configuration safely, potentially removing something that doesn't belong at the top level. I could set the `agent.reasoning_effort` to high and then consider whether to remove `OPENAI_REASONING_EFFORT` or leave it as is. It feels like I should just act, patch, and verify everything afterward."
}
]
}
],
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"id": "call_JJ025HIFhVDmrF0yeTsrxh0w",
"call_id": "call_JJ025HIFhVDmrF0yeTsrxh0w",
"response_item_id": "fc_0801a076ed6917a00169d7bd3417048198a44ffd1968e5831d",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"path\":\"/home/ubuntu/.hermes/config.yaml\",\"old_string\":\" reasoning_effort: ''\\n\",\"new_string\":\" reasoning_effort: xhigh\\n\"}"
}
},
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"id": "call_TrXNLdEN6at74ncTrKKf5jKE",
"call_id": "call_TrXNLdEN6at74ncTrKKf5jKE",
"response_item_id": "fc_0801a076ed6917a00169d7bd34171c8198af0454623bcc0ed4",
"type": "function",
"function": {
"name": "patch",
"arguments": "{\"mode\":\"replace\",\"path\":\"/home/ubuntu/.hermes/config.yaml\",\"old_string\":\"OPENAI_REASONING_EFFORT: xhigh\\n\",\"new_string\":\"\"}"
}
}
]
},
{
"role": "tool",
"content": "{\"success\": true, \"diff\": \"--- a//home/ubuntu/.hermes/config.yaml\\n+++ b//home/ubuntu/.hermes/config.yaml\\n@@ -74,7 +74,7 @@\\n uwu: hewwo! i'm your fwiendwy assistant uwu~ i wiww twy my best to hewp you! *nuzzles\\n your code* OwO what's this? wet me take a wook! i pwomise to be vewy hewpful\\n >w<\\n- reasoning_effort: ''\\n+ reasoning_effort: xhigh\\n system_prompt: You are a technical expert. Provide detailed, accurate technical\\n information.\\n verbose: false\\n\", \"files_modified\": [\"/home/ubuntu/.hermes/config.yaml\"], \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .yaml files\"}}",
"tool_call_id": "call_JJ025HIFhVDmrF0yeTsrxh0w"
},
{
"role": "tool",
"content": "{\"success\": true, \"diff\": \"--- a//home/ubuntu/.hermes/config.yaml\\n+++ b//home/ubuntu/.hermes/config.yaml\\n@@ -361,4 +361,3 @@\\n mode: both\\n streaming:\\n enabled: false\\n-OPENAI_REASONING_EFFORT: xhigh\\n\", \"files_modified\": [\"/home/ubuntu/.hermes/config.yaml\"], \"lint\": {\"status\": \"skipped\", \"message\": \"No linter for .yaml files\"}}",
"tool_call_id": "call_TrXNLdEN6at74ncTrKKf5jKE"
},
{
"role": "assistant",
"content": "",
"reasoning": null,
"finish_reason": "tool_calls",
"tool_calls": [
{
"id": "call_f5bRJ6mulIenFgSJEXKfJ6kM",
"call_id": "call_f5bRJ6mulIenFgSJEXKfJ6kM",
"response_item_id": "fc_0801a076ed6917a00169d7bd5e16b08198ace5ccd7fd547cc8",
"type": "function",
"function": {
"name": "read_file",
"arguments": "{\"path\":\"/home/ubuntu/.hermes/config.yaml\",\"offset\":72,\"limit\":8}"
}
},
{
"id": "call_Ud6b0OVAWPNYL48LorcFbrkN",
"call_id": "call_Ud6b0OVAWPNYL48LorcFbrkN",
"response_item_id": "fc_0801a076ed6917a00169d7bd5e16cc81988dbf349d18e9d7ee",
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"content": "{\"content\": \" 72| teacher: You are a patient teacher. Explain concepts clearly with examples.\\n 73| technical: You are a technical expert. Provide detailed, accurate technical information.\\n 74| uwu: hewwo! i'm your fwiendwy assistant uwu~ i wiww twy my best to hewp you! *nuzzles\\n 75| your code* OwO what's this? wet me take a wook! i pwomise to be vewy hewpful\\n 76| >w<\\n 77| reasoning_effort: xhigh\\n 78| system_prompt: You are a technical expert. Provide detailed, accurate technical\\n 79| information.\\n 80|\", \"total_lines\": 363, \"file_size\": 9502, \"truncated\": true, \"hint\": \"Use offset=80 to continue reading (showing 72-79 of 363 lines)\", \"is_binary\": false, \"is_image\": false}",
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"content": "Done.\n\nChanged:\n- `agent.reasoning_effort` → `xhigh`\n- removed the unused top-level `OPENAI_REASONING_EFFORT`\n\nVerified:\n- `/home/ubuntu/.hermes/config.yaml:77` now says `reasoning_effort: xhigh`\n- no remaining `OPENAI_REASONING_EFFORT` entry in that file\n\nNote:\n- This will apply reliably to new Hermes sessions.\n- The current already-running session may still keep whatever it started with until restarted/recreated.",
"reasoning": null,
"finish_reason": "stop"
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"content": "will it apply to other models if i change provider?"
},
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"reasoning": "**Using tools for accuracy**\n\nI need to ground my answer using the right tools, considering the current facts and version code. It seems like I should inspect or parse something specific, possibly related to the provider or model. While I could draw on my software development skills, it's not entirely necessary for this task. The main focus should be on using the appropriate tools, like checking the parse reasoning effort and model metadata clamp to get more accurate information.",
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"text": "**Using tools for accuracy**\n\nI need to ground my answer using the right tools, considering the current facts and version code. It seems like I should inspect or parse something specific, possibly related to the provider or model. While I could draw on my software development skills, it's not entirely necessary for this task. The main focus should be on using the appropriate tools, like checking the parse reasoning effort and model metadata clamp to get more accurate information."
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"content": "{\"total_count\": 20, \"matches\": [{\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 115, \"content\": \" \\\"\\\"\\\"Parse a reasoning effort level into an OpenRouter reasoning config dict.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 116, \"content\": \" from hermes_constants import parse_reasoning_effort\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 117, \"content\": \" result = parse_reasoning_effort(effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 118, \"content\": \" if effort and effort.strip() and result is None:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 119, \"content\": \" logger.warning(\\\"Unknown reasoning_effort '%s', using default (medium)\\\", effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 589, \"content\": \" from hermes_constants import parse_reasoning_effort\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 590, \"content\": \" effort = str(_cfg.get(\\\"agent\\\", {}).get(\\\"reasoning_effort\\\", \\\"\\\")).strip()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 591, \"content\": \" reasoning_config = parse_reasoning_effort(effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 592, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 593, \"content\": \" # Prefill messages from env or config.yaml\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 939, \"content\": \" except Exception:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 940, \"content\": \" pass\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 941, \"content\": \" result = parse_reasoning_effort(effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 942, \"content\": \" if effort and effort.strip() and result is None:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 943, \"content\": \" logger.warning(\\\"Unknown reasoning_effort '%s', using default (medium)\\\", effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/hermes_constants.py\", \"line\": 76, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/hermes_constants.py\", \"line\": 77, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/hermes_constants.py\", \"line\": 78, \"content\": \"def parse_reasoning_effort(effort: str) -> dict | None:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/hermes_constants.py\", \"line\": 79, \"content\": \" \\\"\\\"\\\"Parse a reasoning effort level into a config dict.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/hermes_constants.py\", \"line\": 80, \"content\": \"\"}]}",
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"content": "{\"total_count\": 62, \"matches\": [{\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 125, \"content\": \" workspace=workspace or get_last_workspace(),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 126, \"content\": \" model=model or _cfg.DEFAULT_MODEL,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 127, \"content\": \" profile=_profile,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 128, \"content\": \" reasoning_effort=_cfg.clamp_reasoning_effort(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 129, \"content\": \" model or _cfg.DEFAULT_MODEL,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 130, \"content\": \" reasoning_effort,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/models.py\", \"line\": 131, \"content\": \" ),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 160, \"content\": \" s = get_session(session_id)\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 161, \"content\": \" s.workspace = str(Path(workspace).expanduser().resolve())\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 162, \"content\": \" s.model = model\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 163, \"content\": \" s.reasoning_effort = clamp_reasoning_effort(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 164, \"content\": \" model,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 165, \"content\": \" reasoning_effort or getattr(s, 'reasoning_effort', ''),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/streaming.py\", \"line\": 166, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 377, \"content\": \" s = new_session(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 378, \"content\": \" workspace=body.get('workspace'),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 379, \"content\": \" model=model,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 380, \"content\": \" reasoning_effort=clamp_reasoning_effort(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 381, \"content\": \" model or DEFAULT_MODEL,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 382, \"content\": \" body.get('reasoning_effort', ''),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 383, \"content\": \" ),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 446, \"content\": \" model = body.get('model', s.model)\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 447, \"content\": \" s.workspace = new_ws\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 448, \"content\": \" s.model = model\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 449, \"content\": \" s.reasoning_effort = clamp_reasoning_effort(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 450, \"content\": \" model,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 451, \"content\": \" body.get('reasoning_effort', s.reasoning_effort or ''),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 452, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1030, \"content\": \" attachments = [str(a) for a in (body.get('attachments') or [])][:20]\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/routes.py\", \"line\": 1031, \"content\": \" workspace = str(Path(body.get('workspace') or s.workspace).expanduser().resolve())\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=30 to see more, or narrow with a more specific pattern or file_glob.]",
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"role": "tool",
"content": "{\"content\": \" 78|def parse_reasoning_effort(effort: str) -> dict | None:\\n 79| \\\"\\\"\\\"Parse a reasoning effort level into a config dict.\\n 80|\\n 81| Valid levels: \\\"xhigh\\\", \\\"high\\\", \\\"medium\\\", \\\"low\\\", \\\"minimal\\\", \\\"none\\\".\\n 82| Returns None when the input is empty or unrecognized (caller uses default).\\n 83| Returns {\\\"enabled\\\": False} for \\\"none\\\".\\n 84| Returns {\\\"enabled\\\": True, \\\"effort\\\": } for valid effort levels.\\n 85| \\\"\\\"\\\"\\n 86| if not effort or not effort.strip():\\n 87| return None\\n 88| effort = effort.strip().lower()\\n 89| if effort == \\\"none\\\":\\n 90| return {\\\"enabled\\\": False}\\n 91| if effort in VALID_REASONING_EFFORTS:\\n 92| return {\\\"enabled\\\": True, \\\"effort\\\": effort}\\n 93| return None\\n 94|\\n 95|\\n 96|OPENROUTER_BASE_URL = \\\"https://openrouter.ai/api/v1\\\"\\n 97|OPENROUTER_MODELS_URL = f\\\"{OPENROUTER_BASE_URL}/models\\\"\\n 98|OPENROUTER_CHAT_URL = f\\\"{OPENROUTER_BASE_URL}/chat/completions\\\"\\n 99|\\n 100|AI_GATEWAY_BASE_URL = \\\"https://ai-gateway.vercel.sh/v1\\\"\\n 101|AI_GATEWAY_MODELS_URL = f\\\"{AI_GATEWAY_BASE_URL}/models\\\"\\n 102|AI_GATEWAY_CHAT_URL = f\\\"{AI_GATEWAY_BASE_URL}/chat/completions\\\"\\n 103|\\n 104|NOUS_API_BASE_URL = \\\"https://inference-api.nousresearch.com/v1\\\"\\n 105|NOUS_API_CHAT_URL = f\\\"{NOUS_API_BASE_URL}/chat/completions\\\"\\n 106|\", \"total_lines\": 105, \"file_size\": 3551, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
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{
"role": "tool",
"content": "{\"total_count\": 17, \"matches\": [{\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 741, \"content\": \" raw_entry = _lookup_model_catalog_entry(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 742, \"content\": \" resolved_provider,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 743, \"content\": \" resolved_model,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 744, \"content\": \" all_env=all_env,\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 745, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 746, \"content\": \" return _reasoning_metadata_for_model(resolved_provider, resolved_model, raw_entry=raw_entry)\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 747, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 748, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 749, \"content\": \"def clamp_reasoning_effort(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 750, \"content\": \" model_id: str,\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=10 to see more, or narrow with a more specific pattern or file_glob.]\n\n[Subdirectory context discovered: ~/hermes-webui/AGENTS.md]\n# Web UI MVP Instructions\n\nCanonical source: /\nSymlink (for imports): /webui-mvp -> \nRuntime state: ~/.hermes/webui-mvp/sessions/\n\nPurpose:\n- Claude-style web UI for Hermes. Chat, workspace file browser, cron/skills/memory viewers.\n\nStart server:\n cd \n nohup venv/bin/python /server.py > /tmp/webui-mvp.log 2>&1 &\n # OR: /start.sh\n\nRun tests:\n cd \n venv/bin/python -m pytest /tests/ -v\n\nHealth check: curl http://127.0.0.1:8787/health\nLogs: tail -f /tmp/webui-mvp.log\nSSH tunnel from Mac: ssh -N -L 8787:127.0.0.1:8787 @\n\nLiving documents (always update after a sprint):\n /ROADMAP.md\n /ARCHITECTURE.md\n /TESTING.md\n\nSprint process skill: webui-sprint-loop\n\n# Workspace Convention (Web UI Sessions)\n\nWhen running as an agent invoked from the web UI, each user message is prefixed with:\n\n [Workspace: /absolute/path/to/workspace]\n\nThis tag is the single authoritative source of the active workspace. It reflects\nwhichever workspace the user has selected in the UI at the moment they sent that message.\nIt updates on every message, so if the user switches workspaces mid-session, the very\nnext message will carry the new path. Always use the value from the most recent tag.\n\nThis tag overrides any prior workspace mentioned in the system prompt, memory, or\nconversation history. Never infer or fall back to a hardcoded path like\n~/workspace when this tag is present.\n\nApply it as the default working directory for ALL file operations:\n\n - write_file: resolve relative paths against this workspace\n - read_file / search_files: resolve paths relative to this workspace\n - terminal workdir: set to this path unless the user explicitly says otherwise\n - patch: resolve file paths relative to this workspace\n\nIf no [Workspace: ...] tag is present (e.g., CLI sessions), fall back to\n~/workspace as the default.",
"tool_call_id": "call_Je4qSbUmixM81CxZyHEAOcHo"
},
{
"role": "tool",
"content": "{\"total_count\": 137, \"matches\": [{\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 586, \"content\": \" if any('reasoning_effort' in item or 'reasoning.effort' in item for item in normalized):\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 587, \"content\": \" return _reasoning_metadata(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 588, \"content\": \" 'effort',\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 589, \"content\": \" options=('low', 'medium', 'high'),\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 590, \"content\": \" note='This provider reports explicit reasoning-effort controls for the model.',\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 591, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 592, \"content\": \" if any(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 593, \"content\": \" item == 'reasoning'\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 594, \"content\": \" or item == 'include_reasoning'\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 601, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 602, \"content\": \" return None\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 603, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 604, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 605, \"content\": \"def _copilot_reasoning_efforts_for_model(model_id: str) -> list[str]:\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 606, \"content\": \" try:\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 607, \"content\": \" from hermes_cli.models import github_model_reasoning_efforts\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 608, \"content\": \" efforts = github_model_reasoning_efforts(model_id)\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 609, \"content\": \" except Exception:\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 610, \"content\": \" efforts = []\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 611, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 612, \"content\": \" normalized = _normalize_reasoning_options(efforts)\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 620, \"content\": \" return _normalize_reasoning_options((\\\"minimal\\\", \\\"low\\\", \\\"medium\\\", \\\"high\\\"))\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 621, \"content\": \" return []\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 622, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 623, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 624, \"content\": \"def _reasoning_metadata_for_model(provider_id: str | None, model_id: str, raw_entry: dict | None = None) -> dict:\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 625, \"content\": \" provider_id = _normalize_provider_id(provider_id) or ''\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 626, \"content\": \" model_id = str(model_id or '').strip()\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 627, \"content\": \" raw_lower = model_id.lower()\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 628, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 634, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 635, \"content\": \" if provider_id == 'deepseek' or raw_lower.startswith('deepseek-chat') or raw_lower.startswith('deepseek-reasoner'):\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 636, \"content\": \" return _reasoning_metadata(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 637, \"content\": \" 'model',\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 638, \"content\": \" note='DeepSeek switches reasoning via separate Chat and Thinking models instead of an effort dropdown.',\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 639, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 640, \"content\": \"\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 641, \"content\": \" if provider_id == 'kimi-coding' and 'thinking' in raw_lower:\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 642, \"content\": \" return _reasoning_metadata(\"}, {\"path\": \"/home/ubuntu/hermes-webui/api/config.py\", \"line\": 643, \"content\": \" 'model',\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=40 to see more, or narrow with a more specific pattern or file_glob.]",
"tool_call_id": "call_5kH1BtfMh0O4HfFOOwZXR67p"
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"content": "{\"content\": \" 624|def _reasoning_metadata_for_model(provider_id: str | None, model_id: str, raw_entry: dict | None = None) -> dict:\\n 625| provider_id = _normalize_provider_id(provider_id) or ''\\n 626| model_id = str(model_id or '').strip()\\n 627| raw_lower = model_id.lower()\\n 628|\\n 629| if provider_id == 'openrouter' and raw_lower == 'openrouter/free':\\n 630| return _reasoning_metadata(\\n 631| 'unsupported',\\n 632| note='OpenRouter Auto (Free) can route across multiple models, so reasoning controls are unavailable here.',\\n 633| )\\n 634|\\n 635| if provider_id == 'deepseek' or raw_lower.startswith('deepseek-chat') or raw_lower.startswith('deepseek-reasoner'):\\n 636| return _reasoning_metadata(\\n 637| 'model',\\n 638| note='DeepSeek switches reasoning via separate Chat and Thinking models instead of an effort dropdown.',\\n 639| )\\n 640|\\n 641| if provider_id == 'kimi-coding' and 'thinking' in raw_lower:\\n 642| return _reasoning_metadata(\\n 643| 'model',\\n 644| note='Moonshot exposes thinking via separate model variants instead of per-request effort levels.',\\n 645| )\\n 646|\\n 647| efforts = _copilot_reasoning_efforts_for_model(model_id)\\n 648| if efforts:\\n 649| return _reasoning_metadata('effort', options=efforts)\\n 650|\\n 651| supported_meta = None\\n 652| capabilities = None\\n 653| if isinstance(raw_entry, dict):\\n 654| supported_meta = _reasoning_metadata_from_supported_parameters(raw_entry.get('supported_parameters'))\\n 655| capabilities = raw_entry.get('capabilities')\\n 656|\\n 657| if supported_meta is not None:\\n 658| return supported_meta\\n 659|\\n 660| if isinstance(capabilities, dict) and capabilities.get('reasoning') is True:\\n 661| return _reasoning_metadata(\\n 662| 'toggle',\\n 663| note='This model supports reasoning on or off, but does not expose low/medium/high effort levels.',\\n 664| )\\n 665|\\n 666| if (\\n 667| raw_lower in _MISTRAL_REASONING_MODEL_IDS\\n 668| or any(raw_lower.startswith(prefix) for prefix in _MISTRAL_REASONING_MODEL_PREFIXES)\\n 669| ):\\n 670| return _reasoning_metadata(\\n 671| 'toggle',\\n 672| note='This Mistral model supports reasoning as an on/off toggle.',\\n 673| )\\n 674|\\n 675| return _reasoning_metadata('unsupported')\\n 676|\\n 677|\\n 678|def _annotate_reasoning_metadata(provider_id: str | None, raw_models: list[dict]) -> list[dict]:\\n 679| provider_id = _normalize_provider_id(provider_id)\\n 680| annotated: list[dict] = []\\n 681| for raw in raw_models or []:\\n 682| if not isinstance(raw, dict):\\n 683| continue\\n 684| model_id = str(raw.get('id') or '').strip()\\n 685| if not model_id:\\n 686| continue\\n 687| entry = dict(raw)\\n 688| entry['reasoning'] = _reasoning_metadata_for_model(provider_id, model_id, raw_entry=entry)\\n 689| annotated.append(entry)\\n 690| return annotated\\n 691|\\n 692|\\n 693|def _lookup_model_catalog_entry(\\n 694| provider_id: str | None,\\n 695| model_id: str,\\n 696| *,\\n 697| all_env: dict | None = None,\\n 698|) -> dict | None:\\n 699| provider_id = _normalize_provider_id(provider_id)\\n 700| model_id = str(model_id or '').strip()\\n 701| if not provider_id or not model_id:\\n 702| return None\\n 703|\\n 704| if provider_id == 'openrouter':\\n 705| raw_models = _discover_openrouter_free_models(all_env=all_env)\\n 706| elif provider_id == 'openai-codex':\\n 707| raw_models = _discover_codex_model_entries() or _PROVIDER_MODELS.get(provider_id, [])\\n 708| elif provider_id in _PROVIDER_MODELS:\\n 709| raw_models = _PROVIDER_MODELS.get(provider_id, [])\\n 710| else:\\n 711| raw_models = _discover_named_custom_provider_catalogs(all_env=all_env).get(provider_id, [])\\n 712|\\n 713| for raw in raw_models or []:\\n 714| if not isinstance(raw, dict):\\n 715| continue\\n 716| if str(raw.get('id') or '').strip() == model_id:\\n 717| return dict(raw)\\n 718| return None\\n 719|\\n 720|\\n 721|def get_model_reasoning_metadata(\\n 722| model_id: str,\\n 723| provider_id: str | None = None,\\n 724| *,\\n 725| all_env: dict | None = None,\\n 726|) -> dict:\\n 727| selected_model = str(model_id or '').strip()\\n 728| resolved_model = selected_model\\n 729| resolved_provider = _normalize_provider_id(provider_id)\\n 730|\\n 731| if selected_model:\\n 732| try:\\n 733| _model, _provider, _ = resolve_model_provider(selected_model)\\n 734| if _model:\\n 735| resolved_model = _model\\n 736| if not resolved_provider and _provider:\\n 737| resolved_provider = _normalize_provider_id(_provider)\\n 738| except Exception:\\n 739| pass\\n 740|\\n 741| raw_entry = _lookup_model_catalog_entry(\\n 742| resolved_provider,\\n 743| resolved_model,\\n 744| all_env=all_env,\\n 745| )\\n 746| return _reasoning_metadata_for_model(resolved_provider, resolved_model, raw_entry=raw_entry)\\n 747|\\n 748|\\n 749|def clamp_reasoning_effort(\\n 750| model_id: str,\\n 751| reasoning_effort: str,\\n 752| provider_id: str | None = None,\\n 753| *,\\n 754| all_env: dict | None = None,\\n 755|) -> str:\\n 756| value = str(reasoning_effort or '').strip().lower()\\n 757| if not value:\\n 758| return ''\\n 759|\\n 760| meta = get_model_reasoning_metadata(\\n 761| model_id,\\n 762| provider_id=provider_id,\\n 763| all_env=all_env,\\n 764| )\\n 765| if meta.get('disabled'):\\n 766| return ''\\n 767|\\n 768| allowed = {\\n 769| str(item or '').strip().lower()\\n 770| for item in (meta.get('options') or [])\\n 771| if str(item or '').strip()\\n 772| }\\n 773| return value if value in allowed else ''\\n 774|\\n 775|\\n 776|def _load_auth_store() -> dict:\\n 777| try:\\n 778| from api.profiles import get_active_hermes_home as _gah\\n 779| auth_store_path = _gah() / 'auth.json'\\n 780| except ImportError:\\n 781| auth_store_path = HOME / '.hermes' / 'auth.json'\\n 782|\\n 783| if not auth_store_path.exists():\\n 784| return {}\\n 785| try:\\n 786| data = json.loads(auth_store_path.read_text())\\n 787| return data if isinstance(data, dict) else {}\\n 788| except Exception:\\n 789| return {}\\n 790|\\n 791|\\n 792|def _auth_store_has_provider(auth_store: dict, provider_id: str) -> bool:\\n 793| provider_id = _normalize_provider_id(provider_id) or ''\\n 794|\", \"total_lines\": 1730, \"file_size\": 70110, \"truncated\": true, \"hint\": \"Use offset=794 to continue reading (showing 624-793 of 1730 lines)\", \"is_binary\": false, \"is_image\": false}",
"tool_call_id": "call_lV8zSMqJFCyhOE02boO0HWQv"
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{
"role": "tool",
"content": "{\"total_count\": 219, \"matches\": [{\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 114, \"content\": \"def _parse_reasoning_config(effort: str) -> dict | None:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 115, \"content\": \" \\\"\\\"\\\"Parse a reasoning effort level into an OpenRouter reasoning config dict.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 116, \"content\": \" from hermes_constants import parse_reasoning_effort\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 117, \"content\": \" result = parse_reasoning_effort(effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 118, \"content\": \" if effort and effort.strip() and result is None:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 119, \"content\": \" logger.warning(\\\"Unknown reasoning_effort '%s', using default (medium)\\\", effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 120, \"content\": \" return result\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 121, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 239, \"content\": \" \\\"system_prompt\\\": \\\"\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 240, \"content\": \" \\\"prefill_messages_file\\\": \\\"\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 241, \"content\": \" \\\"reasoning_effort\\\": \\\"\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 242, \"content\": \" \\\"personalities\\\": {\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 243, \"content\": \" \\\"helpful\\\": \\\"You are a helpful, friendly AI assistant.\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1477, \"content\": \" # Reasoning config (OpenRouter reasoning effort level)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1478, \"content\": \" self.reasoning_config = _parse_reasoning_config(\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1479, \"content\": \" CLI_CONFIG[\\\"agent\\\"].get(\\\"reasoning_effort\\\", \\\"\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1480, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1481, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 5360, \"content\": \" self.agent = None # Force agent re-init with new reasoning config\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 5361, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 5362, \"content\": \" if save_config_value(\\\"agent.reasoning_effort\\\", arg):\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 5363, \"content\": \" _cprint(f\\\" {_GOLD}✓ Reasoning effort set to '{arg}' (saved to config){_RST}\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 5364, \"content\": \" else:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 587, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 588, \"content\": \" # Reasoning config from config.yaml\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 589, \"content\": \" from hermes_constants import parse_reasoning_effort\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 590, \"content\": \" effort = str(_cfg.get(\\\"agent\\\", {}).get(\\\"reasoning_effort\\\", \\\"\\\")).strip()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 591, \"content\": \" reasoning_config = parse_reasoning_effort(effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 592, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 593, \"content\": \" # Prefill messages from env or config.yaml\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 924, \"content\": \" \\\"\\\"\\\"Load reasoning effort from config.yaml.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 925, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 926, \"content\": \" Reads agent.reasoning_effort from config.yaml. Valid: \\\"xhigh\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 927, \"content\": \" \\\"high\\\", \\\"medium\\\", \\\"low\\\", \\\"minimal\\\", \\\"none\\\". Returns None to use\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 928, \"content\": \" default (medium).\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 929, \"content\": \" \\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 930, \"content\": \" from hermes_constants import parse_reasoning_effort\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 931, \"content\": \" effort = \\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 932, \"content\": \" try:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 936, \"content\": \" with open(cfg_path, encoding=\\\"utf-8\\\") as _f:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 937, \"content\": \" cfg = _y.safe_load(_f) or {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 938, \"content\": \" effort = str(cfg.get(\\\"agent\\\", {}).get(\\\"reasoning_effort\\\", \\\"\\\") or \\\"\\\").strip()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 939, \"content\": \" except Exception:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 940, \"content\": \" pass\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 941, \"content\": \" result = parse_reasoning_effort(effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 942, \"content\": \" if effort and effort.strip() and result is None:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 943, \"content\": \" logger.warning(\\\"Unknown reasoning_effort '%s', using default (medium)\\\", effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 944, \"content\": \" return result\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 945, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/gateway/run.py\", \"line\": 4898, \"content\": \"\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=50 to see more, or narrow with a more specific pattern or file_glob.]",
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"reasoning": "**Investigating CLI and gateway application**\n\nI need to clarify if CLI or gateway applies universally. It seems that the code in hermes-agent doesn't have a clamp, as it only passes the parse_reasoning_effort globally. I should check whether downstream clients or providers support this setup. It might also be helpful to search for how reasoning_config is being utilized in building API calls to gather more insights. Let's dig into it and see what I can find!",
"finish_reason": "tool_calls",
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{
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"text": "**Investigating CLI and gateway application**\n\nI need to clarify if CLI or gateway applies universally. It seems that the code in hermes-agent doesn't have a clamp, as it only passes the parse_reasoning_effort globally. I should check whether downstream clients or providers support this setup. It might also be helpful to search for how reasoning_config is being utilized in building API calls to gather more insights. Let's dig into it and see what I can find!"
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"function": {
"name": "search_files",
"arguments": "{\"pattern\":\"reasoning\\\\W\", \"path\":\"/home/ubuntu/.hermes/hermes-agent\",\"target\":\"content\",\"file_glob\":\"*.py\",\"limit\":80,\"output_mode\":\"content\",\"context\":2}"
}
}
]
},
{
"role": "tool",
"content": "{\"total_count\": 231, \"matches\": [{\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/delegate_tool.py\", \"line\": 294, \"content\": \" acp_args=effective_acp_args,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/delegate_tool.py\", \"line\": 295, \"content\": \" max_iterations=max_iterations,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/delegate_tool.py\", \"line\": 296, \"content\": \" max_tokens=getattr(parent_agent, \\\"max_tokens\\\", None),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/delegate_tool.py\", \"line\": 297, \"content\": \" reasoning_config=getattr(parent_agent, \\\"reasoning_config\\\", None),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/delegate_tool.py\", \"line\": 298, \"content\": \" prefill_messages=getattr(parent_agent, \\\"prefill_messages\\\", None),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/delegate_tool.py\", \"line\": 299, \"content\": \" enabled_toolsets=child_toolsets,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/delegate_tool.py\", \"line\": 300, \"content\": \" quiet_mode=True,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 588, \"content\": \" # Reasoning config from config.yaml\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 589, \"content\": \" from hermes_constants import parse_reasoning_effort\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 590, \"content\": \" effort = str(_cfg.get(\\\"agent\\\", {}).get(\\\"reasoning_effort\\\", \\\"\\\")).strip()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 591, \"content\": \" reasoning_config = parse_reasoning_effort(effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 592, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 593, \"content\": \" # Prefill messages from env or config.yaml\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 594, \"content\": \" prefill_messages = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 654, \"content\": \" acp_command=turn_route[\\\"runtime\\\"].get(\\\"command\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 655, \"content\": \" acp_args=turn_route[\\\"runtime\\\"].get(\\\"args\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 656, \"content\": \" max_iterations=max_iterations,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 657, \"content\": \" reasoning_config=reasoning_config,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 658, \"content\": \" prefill_messages=prefill_messages,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 659, \"content\": \" providers_allowed=pr.get(\\\"only\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 660, \"content\": \" providers_ignored=pr.get(\\\"ignore\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 327, \"content\": \" providers_order=config.get(\\\"providers_order\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 328, \"content\": \" provider_sort=config.get(\\\"provider_sort\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 329, \"content\": \" max_tokens=config.get(\\\"max_tokens\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 330, \"content\": \" reasoning_config=config.get(\\\"reasoning_config\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 331, \"content\": \" prefill_messages=config.get(\\\"prefill_messages\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 332, \"content\": \" skip_context_files=True, # Don't pollute trajectories with SOUL.md/AGENTS.md\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 333, \"content\": \" skip_memory=True, # Don't use persistent memory in batch runs\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 535, \"content\": \" providers_order: List[str] = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 536, \"content\": \" provider_sort: str = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 537, \"content\": \" max_tokens: int = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 538, \"content\": \" reasoning_config: Dict[str, Any] = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 539, \"content\": \" prefill_messages: List[Dict[str, Any]] = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 540, \"content\": \" max_samples: int = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 541, \"content\": \" ):\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 560, \"content\": \" providers_order (List[str]): OpenRouter providers to try in order (optional)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 561, \"content\": \" provider_sort (str): Sort providers by price/throughput/latency (optional)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 562, \"content\": \" max_tokens (int): Maximum tokens for model responses (optional, uses model default if not set)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 563, \"content\": \" reasoning_config (Dict): OpenRouter reasoning config override (e.g. {\\\"effort\\\": \\\"none\\\"} to disable thinking)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 564, \"content\": \" prefill_messages (List[Dict]): Messages to prepend as prefilled conversation context (few-shot priming)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 565, \"content\": \" max_samples (int): Only process the first N samples from the dataset (optional, processes all if not set)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 566, \"content\": \" \\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 581, \"content\": \" self.providers_order = providers_order\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 582, \"content\": \" self.provider_sort = provider_sort\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 583, \"content\": \" self.max_tokens = max_tokens\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 584, \"content\": \" self.reasoning_config = reasoning_config\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 585, \"content\": \" self.prefill_messages = prefill_messages\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 586, \"content\": \" self.max_samples = max_samples\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 587, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 859, \"content\": \" \\\"providers_order\\\": self.providers_order,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 860, \"content\": \" \\\"provider_sort\\\": self.provider_sort,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 861, \"content\": \" \\\"max_tokens\\\": self.max_tokens,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 862, \"content\": \" \\\"reasoning_config\\\": self.reasoning_config,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 863, \"content\": \" \\\"prefill_messages\\\": self.prefill_messages,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 864, \"content\": \" }\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 865, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1218, \"content\": \" providers_ignored_list = [p.strip() for p in providers_ignored.split(\\\",\\\")] if providers_ignored else None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1219, \"content\": \" providers_order_list = [p.strip() for p in providers_order.split(\\\",\\\")] if providers_order else None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1220, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1221, \"content\": \" # Build reasoning_config from CLI flags\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=60 to see more, or narrow with a more specific pattern or file_glob.]",
"tool_call_id": "call_TzE9y9p0RVBuMQVc4DL0n6Kh"
},
{
"role": "tool",
"content": "{\"total_count\": 244, \"matches\": [{\"path\": \"/home/ubuntu/.hermes/hermes-agent/rl_cli.py\", \"line\": 10, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/rl_cli.py\", \"line\": 11, \"content\": \"Usage:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/rl_cli.py\", \"line\": 12, \"content\": \" python rl_cli.py \\\"Train a model on GSM8k for math reasoning\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/rl_cli.py\", \"line\": 13, \"content\": \" python rl_cli.py --interactive\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/rl_cli.py\", \"line\": 14, \"content\": \" python rl_cli.py --list-environments\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 99, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 100, \"content\": \" \\\"moa\\\": {\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 101, \"content\": \" \\\"description\\\": \\\"Advanced reasoning and problem-solving tools\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 102, \"content\": \" \\\"tools\\\": [\\\"mixture_of_agents\\\"],\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/toolsets.py\", \"line\": 103, \"content\": \" \\\"includes\\\": []\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/openviking/__init__.py\", \"line\": 137, \"content\": \" \\\"Semantic search over the OpenViking knowledge base. \\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/openviking/__init__.py\", \"line\": 138, \"content\": \" \\\"Returns ranked results with viking:// URIs for deeper reading. \\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/openviking/__init__.py\", \"line\": 139, \"content\": \" \\\"Use mode='deep' for complex queries that need reasoning across \\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/openviking/__init__.py\", \"line\": 140, \"content\": \" \\\"multiple sources, 'fast' for simple lookups.\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/openviking/__init__.py\", \"line\": 141, \"content\": \" ),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/holographic/__init__.py\", \"line\": 38, \"content\": \" \\\"name\\\": \\\"fact_store\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/holographic/__init__.py\", \"line\": 39, \"content\": \" \\\"description\\\": (\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/holographic/__init__.py\", \"line\": 40, \"content\": \" \\\"Deep structured memory with algebraic reasoning. \\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/holographic/__init__.py\", \"line\": 41, \"content\": \" \\\"Use alongside the memory tool — memory for always-on context, \\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/holographic/__init__.py\", \"line\": 42, \"content\": \" \\\"fact_store for deep recall and compositional queries.\\\\n\\\\n\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/holographic/retrieval.py\", \"line\": 268, \"content\": \" Given multiple entities, algebraically intersects their structural\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/holographic/retrieval.py\", \"line\": 269, \"content\": \" connections to find facts related to ALL of them simultaneously.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/holographic/retrieval.py\", \"line\": 270, \"content\": \" This is compositional reasoning that no embedding DB can do.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/holographic/retrieval.py\", \"line\": 271, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/holographic/retrieval.py\", \"line\": 272, \"content\": \" Example: reason([\\\"peppi\\\", \\\"backend\\\"]) finds facts where peppi AND\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/__init__.py\", \"line\": 36, \"content\": \" \\\"Retrieve the user's peer card from Honcho — a curated list of key facts \\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/__init__.py\", \"line\": 37, \"content\": \" \\\"about them (name, role, preferences, communication style, patterns). \\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/__init__.py\", \"line\": 38, \"content\": \" \\\"Fast, no LLM reasoning, minimal cost. \\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/__init__.py\", \"line\": 39, \"content\": \" \\\"Use this at conversation start or when you need a quick factual snapshot.\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/__init__.py\", \"line\": 40, \"content\": \" ),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/__init__.py\", \"line\": 70, \"content\": \" \\\"description\\\": (\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/__init__.py\", \"line\": 71, \"content\": \" \\\"Ask Honcho a natural language question and get a synthesized answer. \\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/__init__.py\", \"line\": 72, \"content\": \" \\\"Uses Honcho's LLM (dialectic reasoning) — higher cost than honcho_profile or honcho_search. \\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/__init__.py\", \"line\": 73, \"content\": \" \\\"Can query about any peer: the user (default) or the AI assistant.\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/__init__.py\", \"line\": 74, \"content\": \" ),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 197, \"content\": \"def _extract_reasoning_stats(messages: List[Dict[str, Any]]) -> Dict[str, int]:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 198, \"content\": \" \\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 199, \"content\": \" Count how many assistant turns have reasoning vs no reasoning.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 200, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 201, \"content\": \" Checks for in content or a non-empty 'reasoning' field\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 202, \"content\": \" (native thinking tokens). Returns counts for tracking reasoning coverage.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 203, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 204, \"content\": \" Args:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 206, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 207, \"content\": \" Returns:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 208, \"content\": \" Dict with 'total_assistant_turns', 'turns_with_reasoning', 'turns_without_reasoning'\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 209, \"content\": \" \\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 210, \"content\": \" total = 0\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 211, \"content\": \" with_reasoning = 0\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 212, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 213, \"content\": \" for msg in messages:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 218, \"content\": \" content = msg.get(\\\"content\\\", \\\"\\\") or \\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 219, \"content\": \" has_scratchpad = \\\"\\\" in content\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 220, \"content\": \" has_native_reasoning = bool(msg.get(\\\"reasoning\\\", \\\"\\\").strip()) if msg.get(\\\"reasoning\\\") else False\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 221, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 222, \"content\": \" if has_scratchpad or has_native_reasoning:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 223, \"content\": \" with_reasoning += 1\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 224, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 225, \"content\": \" return {\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 226, \"content\": \" \\\"total_assistant_turns\\\": total,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 227, \"content\": \" \\\"turns_with_reasoning\\\": with_reasoning,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 228, \"content\": \" \\\"turns_without_reasoning\\\": total - with_reasoning,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 229, \"content\": \" \\\"has_any_reasoning\\\": with_reasoning > 0,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 230, \"content\": \" }\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 231, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 340, \"content\": \" tool_stats = _extract_tool_stats(result[\\\"messages\\\"])\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 341, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 342, \"content\": \" # Extract reasoning coverage stats\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 343, \"content\": \" reasoning_stats = _extract_reasoning_stats(result[\\\"messages\\\"])\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 344, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 424, \"content\": \" # Initialize aggregated stats for this batch\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 425, \"content\": \" batch_tool_stats = {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 426, \"content\": \" batch_reasoning_stats = {\\\"total_assistant_turns\\\": 0, \\\"turns_with_reasoning\\\": 0, \\\"turns_without_reasoning\\\": 0}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 427, \"content\": \" completed_in_batch = []\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 428, \"content\": \" discarded_no_reasoning = 0\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 429, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 430, \"content\": \" # Process each prompt sequentially in this batch\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 440, \"content\": \" # Save trajectory if successful\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 441, \"content\": \" if result[\\\"success\\\"] and result[\\\"trajectory\\\"]:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 442, \"content\": \" # Discard samples with zero reasoning across all turns\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=80 to see more, or narrow with a more specific pattern or file_glob.]",
"tool_call_id": "call_lzHTaZToLsSc47QXp26ztNd9"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Locating API client mappings**\n\nI need to locate the API client mappings, and it seems that openrouter might be my only option. I should focus on searching for \"reasoning_config\" within the run_agent or model files. This could help me pinpoint what I’m looking for, but I want to ensure I’m thorough in checking the files. It’ll be interesting to see what insights I can find by digging into those resources!",
"finish_reason": "tool_calls",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABp173yD1dDI3LXcWd9kD9ljmDtt95nXcpf22lGd4VXuNlJyPh2aTzwZliBW2gMNSAvOlD-LjcZuA5Hm9OKetTbGPkpLeh3_EVTz9hjVMTu9VOyCuwtzKXGK-Sqy3BHAIwV3k61pPx4NplKO-LfndXCG-OCVYq9MVcVYIeSxzDYpHmjd94Yv8rwAb6eCbialZ9GueM0uupdsqucWGLu1IR0Mg6bZNq6fTkSDS9IoMiveojPa0WoE_tvdTZ5q27uavvXyrO6DzDOkOLEAG58Y1VD3Dx5xNyKyiBCinXVq2Wd40Hql_Vt9uZIwJAk9mduGXKGOeRTPg6JLM2kEKKbqdB3Rsg2wB2DeBQe1QSQOMg5fLqaIPM4bmFi3-7sEwDoSjpK8E7eS46CPeTNcW3bPor2kKCUoRqEm2P5AeTJxIeAm2pw1hYVartueV4E3_qkvd2QSk99C2hzKn675JNJlT6Q6xpA0_AGZ9TN-WQGjfsAAIC3NQx_Kacn4TfEyJ025CZzw3rkjm7_d7ITlFBRh7cBDggQ1Xz0R5u6WGaoCsSPtHI2iTiTGB3oLqHAfQ1_HQ9RLnOqBxZoRiHgb7QFnxM-jQq0MjIFDLpaVdjV3hbwLm25HDPQygnln4Z1G7fxqXwiaipE0CfP4BECtXvtEDbg_Wyrsajt2G6eVHhV_jw2IUJk1Si9qs1sw9IdPwQwzmYw7jizwRfAN-PP3suaHVctOv9Ot6dAAx6oyd-0-hiTEM4baBVVlgfvFA8QNjmbwi9g3LQrT5vSnCdT9CrroCXZfiJvR3-HK9Kqich4zA0-hARJRqteEJC3uO9RzSkeC4n43hT6mOyh9Q4xAcNaPYkNKYU0917Dx5Dwn1zWqwnu0aiNo4wa6PewOucqnjn_YoiRAE1rIubJQBt_uTJKEuHjHVQEHSpkjaFMq0oQOtjyurwAdcoPMyV8IwdaAc_wqR4j7ZqJHyH-7MW1HRZ-MOLIfoiPug==",
"id": "rs_0801a076ed6917a00169d7bdef7e008198bbe71aa0dd4670e9",
"summary": [
{
"type": "summary_text",
"text": "**Locating API client mappings**\n\nI need to locate the API client mappings, and it seems that openrouter might be my only option. I should focus on searching for \"reasoning_config\" within the run_agent or model files. This could help me pinpoint what I’m looking for, but I want to ensure I’m thorough in checking the files. It’ll be interesting to see what insights I can find by digging into those resources!"
}
]
}
],
"tool_calls": [
{
"id": "call_cc99k0csH5eG2KLupPZAf5cw",
"call_id": "call_cc99k0csH5eG2KLupPZAf5cw",
"response_item_id": "fc_0801a076ed6917a00169d7bdfb269c8198a52a72046df4d06e",
"type": "function",
"function": {
"name": "search_files",
"arguments": "{\"pattern\":\"reasoning_config\", \"path\":\"/home/ubuntu/.hermes/hermes-agent\", \"target\":\"content\", \"file_glob\":\"run_agent.py\", \"limit\":40, \"output_mode\":\"content\", \"context\":4}"
}
},
{
"id": "call_0uXRBAXqUJfnT1vdxjrxAmkO",
"call_id": "call_0uXRBAXqUJfnT1vdxjrxAmkO",
"response_item_id": "fc_0801a076ed6917a00169d7bdfb26b48198ac56efccb827972f",
"type": "function",
"function": {
"name": "search_files",
"arguments": "{\"pattern\":\"reasoning_config\", \"path\":\"/home/ubuntu/.hermes/hermes-agent\", \"target\":\"content\", \"file_glob\":\"*.py\", \"limit\":100, \"output_mode\":\"content\",\"context\":4}"
}
},
{
"id": "call_iGFZDdfwRsO8ZpNRDuc23uvm",
"call_id": "call_iGFZDdfwRsO8ZpNRDuc23uvm",
"response_item_id": "fc_0801a076ed6917a00169d7bdfb26c8819897dc557b900dcded",
"type": "function",
"function": {
"name": "search_files",
"arguments": "{\"pattern\":\"include_reasoning|reasoning_effort|reasoning\\\\s*:\", \"path\":\"/home/ubuntu/.hermes/hermes-agent\", \"target\":\"content\", \"file_glob\":\"*.py\", \"limit\":100, \"output_mode\":\"content\",\"context\":3}"
}
}
]
},
{
"role": "tool",
"content": "{\"total_count\": 118, \"matches\": [{\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 489, \"content\": \" stream_delta_callback: callable = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 490, \"content\": \" tool_gen_callback: callable = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 491, \"content\": \" status_callback: callable = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 492, \"content\": \" max_tokens: int = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 493, \"content\": \" reasoning_config: Dict[str, Any] = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 494, \"content\": \" prefill_messages: List[Dict[str, Any]] = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 495, \"content\": \" platform: str = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 496, \"content\": \" user_id: str = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 497, \"content\": \" skip_context_files: bool = False,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 533, \"content\": \" tool_progress_callback (callable): Callback function(tool_name, args_preview) for progress notifications\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 534, \"content\": \" clarify_callback (callable): Callback function(question, choices) -> str for interactive user questions.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 535, \"content\": \" Provided by the platform layer (CLI or gateway). If None, the clarify tool returns an error.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 536, \"content\": \" max_tokens (int): Maximum tokens for model responses (optional, uses model default if not set)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 537, \"content\": \" reasoning_config (Dict): OpenRouter reasoning configuration override (e.g. {\\\"effort\\\": \\\"none\\\"} to disable thinking).\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 538, \"content\": \" If None, defaults to {\\\"enabled\\\": True, \\\"effort\\\": \\\"medium\\\"} for OpenRouter. Set to disable/customize reasoning.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 539, \"content\": \" prefill_messages (List[Dict]): Messages to prepend to conversation history as prefilled context.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 540, \"content\": \" Useful for injecting a few-shot example or priming the model's response style.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 541, \"content\": \" Example: [{\\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"Hi!\\\"}, {\\\"role\\\": \\\"assistant\\\", \\\"content\\\": \\\"Hello!\\\"}]\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 650, \"content\": \" self.disabled_toolsets = disabled_toolsets\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 651, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 652, \"content\": \" # Model response configuration\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 653, \"content\": \" self.max_tokens = max_tokens # None = use model default\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 654, \"content\": \" self.reasoning_config = reasoning_config # None = use default (medium for OpenRouter)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 655, \"content\": \" self.prefill_messages = prefill_messages or [] # Prefilled conversation turns\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 656, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 657, \"content\": \" # Anthropic prompt caching: auto-enabled for Claude models via OpenRouter.\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 658, \"content\": \" # Reduces input costs by ~75% on multi-turn conversations by caching the\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 960, \"content\": \" source=self.platform or os.environ.get(\\\"HERMES_SESSION_SOURCE\\\", \\\"cli\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 961, \"content\": \" model=self.model,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 962, \"content\": \" model_config={\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 963, \"content\": \" \\\"max_iterations\\\": self.max_iterations,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 964, \"content\": \" \\\"reasoning_config\\\": reasoning_config,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 965, \"content\": \" \\\"max_tokens\\\": max_tokens,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 966, \"content\": \" },\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 967, \"content\": \" user_id=None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 968, \"content\": \" parent_session_id=self._parent_session_id,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 5329, \"content\": \" model=self.model,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 5330, \"content\": \" messages=anthropic_messages,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 5331, \"content\": \" tools=self.tools,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/run_agent.py\", \"line\": 5332, \"content\": \" max_tokens=self.max_tokens,\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=40 to see more, or narrow with a more specific pattern or file_glob.]",
"tool_call_id": "call_cc99k0csH5eG2KLupPZAf5cw"
},
{
"role": "tool",
"content": "{\"total_count\": 275, \"matches\": [{\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 587, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 588, \"content\": \" # Reasoning config from config.yaml\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 589, \"content\": \" from hermes_constants import parse_reasoning_effort\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 590, \"content\": \" effort = str(_cfg.get(\\\"agent\\\", {}).get(\\\"reasoning_effort\\\", \\\"\\\")).strip()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 591, \"content\": \" reasoning_config = parse_reasoning_effort(effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 592, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 593, \"content\": \" # Prefill messages from env or config.yaml\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 594, \"content\": \" prefill_messages = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 595, \"content\": \" prefill_file = os.getenv(\\\"HERMES_PREFILL_MESSAGES_FILE\\\", \\\"\\\") or _cfg.get(\\\"prefill_messages_file\\\", \\\"\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 653, \"content\": \" api_mode=turn_route[\\\"runtime\\\"].get(\\\"api_mode\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 654, \"content\": \" acp_command=turn_route[\\\"runtime\\\"].get(\\\"command\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 655, \"content\": \" acp_args=turn_route[\\\"runtime\\\"].get(\\\"args\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 656, \"content\": \" max_iterations=max_iterations,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 657, \"content\": \" reasoning_config=reasoning_config,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 658, \"content\": \" prefill_messages=prefill_messages,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 659, \"content\": \" providers_allowed=pr.get(\\\"only\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 660, \"content\": \" providers_ignored=pr.get(\\\"ignore\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cron/scheduler.py\", \"line\": 661, \"content\": \" providers_order=pr.get(\\\"order\\\"),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 347, \"content\": \" assert \\\"instructions\\\" in kwargs\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 348, \"content\": \" assert \\\"messages\\\" not in kwargs\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 349, \"content\": \" assert kwargs[\\\"store\\\"] is False\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 350, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 351, \"content\": \" def test_includes_reasoning_config(self, monkeypatch):\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 352, \"content\": \" agent = _make_agent(monkeypatch, \\\"openai-codex\\\", api_mode=\\\"codex_responses\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 353, \"content\": \" base_url=\\\"https://chatgpt.com/backend-api/codex\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 354, \"content\": \" messages = [{\\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"hi\\\"}]\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 355, \"content\": \" kwargs = agent._build_api_kwargs(messages)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 829, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 830, \"content\": \" def test_codex_reasoning_disabled(self, monkeypatch):\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 831, \"content\": \" agent = _make_agent(monkeypatch, \\\"openai-codex\\\", api_mode=\\\"codex_responses\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 832, \"content\": \" base_url=\\\"https://chatgpt.com/backend-api/codex\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 833, \"content\": \" agent.reasoning_config = {\\\"enabled\\\": False}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 834, \"content\": \" kwargs = agent._build_api_kwargs([{\\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"hi\\\"}])\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 835, \"content\": \" assert \\\"reasoning\\\" not in kwargs\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 836, \"content\": \" assert kwargs[\\\"include\\\"] == []\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 837, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 838, \"content\": \" def test_codex_reasoning_low(self, monkeypatch):\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 839, \"content\": \" agent = _make_agent(monkeypatch, \\\"openai-codex\\\", api_mode=\\\"codex_responses\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 840, \"content\": \" base_url=\\\"https://chatgpt.com/backend-api/codex\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 841, \"content\": \" agent.reasoning_config = {\\\"enabled\\\": True, \\\"effort\\\": \\\"low\\\"}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 842, \"content\": \" kwargs = agent._build_api_kwargs([{\\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"hi\\\"}])\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 843, \"content\": \" assert kwargs[\\\"reasoning\\\"][\\\"effort\\\"] == \\\"low\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 844, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 845, \"content\": \" def test_openrouter_reasoning_config_override(self, monkeypatch):\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 846, \"content\": \" agent = _make_agent(monkeypatch, \\\"openrouter\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 847, \"content\": \" agent.model = \\\"anthropic/claude-sonnet-4-20250514\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 848, \"content\": \" agent.reasoning_config = {\\\"enabled\\\": True, \\\"effort\\\": \\\"medium\\\"}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 849, \"content\": \" kwargs = agent._build_api_kwargs([{\\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"hi\\\"}])\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_provider_parity.py\", \"line\": 850, \"content\": \" assert kwargs[\\\"extra_body\\\"][\\\"reasoning\\\"][\\\"effort\\\"] == \\\"medium\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_interactive_interrupt.py\", \"line\": 70, \"content\": \" parent.providers_ignored = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_interactive_interrupt.py\", \"line\": 71, \"content\": \" parent.providers_order = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_interactive_interrupt.py\", \"line\": 72, \"content\": \" parent.provider_sort = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_interactive_interrupt.py\", \"line\": 73, \"content\": \" parent.max_tokens = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_interactive_interrupt.py\", \"line\": 74, \"content\": \" parent.reasoning_config = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_interactive_interrupt.py\", \"line\": 75, \"content\": \" parent.prefill_messages = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_interactive_interrupt.py\", \"line\": 76, \"content\": \" parent._session_db = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_interactive_interrupt.py\", \"line\": 77, \"content\": \" parent._delegate_depth = 0\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_interactive_interrupt.py\", \"line\": 78, \"content\": \" parent._delegate_spinner = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 167, \"content\": \" runner = gateway_run.GatewayRunner.__new__(gateway_run.GatewayRunner)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 168, \"content\": \" runner.adapters = {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 169, \"content\": \" runner._ephemeral_system_prompt = \\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 170, \"content\": \" runner._prefill_messages = []\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 171, \"content\": \" runner._reasoning_config = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 172, \"content\": \" runner._provider_routing = {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 173, \"content\": \" runner._fallback_model = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 174, \"content\": \" runner._running_agents = {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 175, \"content\": \" runner.hooks = MagicMock()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 302, \"content\": \" runner = gateway_run.GatewayRunner.__new__(gateway_run.GatewayRunner)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 303, \"content\": \" runner.adapters = {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 304, \"content\": \" runner._ephemeral_system_prompt = \\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 305, \"content\": \" runner._prefill_messages = []\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 306, \"content\": \" runner._reasoning_config = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 307, \"content\": \" runner._provider_routing = {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 308, \"content\": \" runner._fallback_model = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 309, \"content\": \" runner._running_agents = {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 310, \"content\": \" runner.hooks = MagicMock()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 375, \"content\": \" runner = gateway_run.GatewayRunner.__new__(gateway_run.GatewayRunner)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 376, \"content\": \" runner.adapters = {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 377, \"content\": \" runner._ephemeral_system_prompt = \\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 378, \"content\": \" runner._prefill_messages = []\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 379, \"content\": \" runner._reasoning_config = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 380, \"content\": \" runner._provider_routing = {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 381, \"content\": \" runner._fallback_model = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 382, \"content\": \" runner._running_agents = {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 383, \"content\": \" runner.hooks = MagicMock()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 463, \"content\": \" runner = gateway_run.GatewayRunner.__new__(gateway_run.GatewayRunner)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 464, \"content\": \" runner.adapters = {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 465, \"content\": \" runner._ephemeral_system_prompt = \\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 466, \"content\": \" runner._prefill_messages = []\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 467, \"content\": \" runner._reasoning_config = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 468, \"content\": \" runner._provider_routing = {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 469, \"content\": \" runner._fallback_model = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 470, \"content\": \" runner._running_agents = {}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tests/run_agent/test_anthropic_error_handling.py\", \"line\": 471, \"content\": \" runner.hooks = MagicMock()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/delegate_tool.py\", \"line\": 293, \"content\": \" acp_command=effective_acp_command,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/delegate_tool.py\", \"line\": 294, \"content\": \" acp_args=effective_acp_args,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/delegate_tool.py\", \"line\": 295, \"content\": \" max_iterations=max_iterations,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/delegate_tool.py\", \"line\": 296, \"content\": \" max_tokens=getattr(parent_agent, \\\"max_tokens\\\", None),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/delegate_tool.py\", \"line\": 297, \"content\": \" reasoning_config=getattr(parent_agent, \\\"reasoning_config\\\", None),\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/tools/delegate_tool.py\", \"line\": 298, \"content\": \" prefill_messages=getattr(parent_agent, \\\"prefill_messages\\\", None),\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=100 to see more, or narrow with a more specific pattern or file_glob.]",
"tool_call_id": "call_0uXRBAXqUJfnT1vdxjrxAmkO"
},
{
"role": "tool",
"content": "{\"total_count\": 268, \"matches\": [{\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 760, \"content\": \" print(\\\" Hermes' identity in Honcho. Seed with 'hermes honcho identity '.\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 761, \"content\": \" print(\\\" Dialectic calls ask this peer questions to warm session context.\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 762, \"content\": \" print()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 763, \"content\": \" print(f\\\" Dialectic reasoning: {lvl} ({', '.join(REASONING_LEVELS)})\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 764, \"content\": \" print(f\\\" Dialectic cap: {max_chars} chars\\\\n\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 765, \"content\": \" return\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 766, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 843, \"content\": \" print(\\\" Raw memory retrieval. Honcho returns stored facts/history about\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 844, \"content\": \" print(\\\" the user and session, injected directly into the system prompt.\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 845, \"content\": \" print()\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 846, \"content\": \" print(f\\\" Dialectic {d_chars} chars, reasoning: {d_level}\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 847, \"content\": \" print(\\\" AI-to-AI inference. Hermes asks Honcho's AI peer a question\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 848, \"content\": \" print(\\\" (e.g. \\\\\\\"what were we working on?\\\\\\\") and Honcho runs its own model\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/plugins/memory/honcho/cli.py\", \"line\": 849, \"content\": \" print(\\\" to synthesize an answer. Used for first-turn session continuity.\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 219, \"content\": \" has_scratchpad = \\\"\\\" in content\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 220, \"content\": \" has_native_reasoning = bool(msg.get(\\\"reasoning\\\", \\\"\\\").strip()) if msg.get(\\\"reasoning\\\") else False\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 221, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 222, \"content\": \" if has_scratchpad or has_native_reasoning:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 223, \"content\": \" with_reasoning += 1\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 224, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 225, \"content\": \" return {\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1096, \"content\": \" pct_with = round(with_reasoning / total_turns * 100, 1)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1097, \"content\": \" pct_without = round(without_reasoning / total_turns * 100, 1)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1098, \"content\": \" print(f\\\" Total assistant turns: {total_turns:,}\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1099, \"content\": \" print(f\\\" With reasoning: {with_reasoning:,} ({pct_with}%)\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1100, \"content\": \" print(f\\\" Without reasoning: {without_reasoning:,} ({pct_without}%)\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1101, \"content\": \" else:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1102, \"content\": \" print(\\\" No assistant turns recorded.\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1103, \"content\": \" if total_discarded > 0:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1130, \"content\": \" providers_order: str = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1131, \"content\": \" provider_sort: str = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1132, \"content\": \" max_tokens: int = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1133, \"content\": \" reasoning_effort: str = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1134, \"content\": \" reasoning_disabled: bool = False,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1135, \"content\": \" prefill_messages_file: str = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1136, \"content\": \" max_samples: int = None,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1158, \"content\": \" providers_order (str): Comma-separated list of OpenRouter providers to try in order (e.g. \\\"anthropic,openai,google\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1159, \"content\": \" provider_sort (str): Sort providers by \\\"price\\\", \\\"throughput\\\", or \\\"latency\\\" (OpenRouter only)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1160, \"content\": \" max_tokens (int): Maximum tokens for model responses (optional, uses model default if not set)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1161, \"content\": \" reasoning_effort (str): OpenRouter reasoning effort level: \\\"xhigh\\\", \\\"high\\\", \\\"medium\\\", \\\"low\\\", \\\"minimal\\\", \\\"none\\\" (default: \\\"medium\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1162, \"content\": \" reasoning_disabled (bool): Completely disable reasoning/thinking tokens (default: False)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1163, \"content\": \" prefill_messages_file (str): Path to JSON file containing prefill messages (list of {role, content} dicts)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1164, \"content\": \" max_samples (int): Only process the first N samples from the dataset (optional, processes all if not set)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1219, \"content\": \" providers_order_list = [p.strip() for p in providers_order.split(\\\",\\\")] if providers_order else None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1220, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1221, \"content\": \" # Build reasoning_config from CLI flags\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1222, \"content\": \" # --reasoning_disabled takes priority, then --reasoning_effort, then default (medium)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1223, \"content\": \" reasoning_config = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1224, \"content\": \" if reasoning_disabled:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1225, \"content\": \" # Completely disable reasoning/thinking tokens\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1226, \"content\": \" reasoning_config = {\\\"effort\\\": \\\"none\\\"}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1227, \"content\": \" print(\\\"🧠 Reasoning: DISABLED (effort=none)\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1228, \"content\": \" elif reasoning_effort:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1229, \"content\": \" # Use specified effort level\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1230, \"content\": \" valid_efforts = [\\\"xhigh\\\", \\\"high\\\", \\\"medium\\\", \\\"low\\\", \\\"minimal\\\", \\\"none\\\"]\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1231, \"content\": \" if reasoning_effort not in valid_efforts:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1232, \"content\": \" print(f\\\"❌ Error: --reasoning_effort must be one of: {', '.join(valid_efforts)}\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1233, \"content\": \" return\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1234, \"content\": \" reasoning_config = {\\\"enabled\\\": True, \\\"effort\\\": reasoning_effort}\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1235, \"content\": \" print(f\\\"🧠 Reasoning effort: {reasoning_effort}\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1236, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1237, \"content\": \" # Load prefill messages from JSON file if provided\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/batch_runner.py\", \"line\": 1238, \"content\": \" prefill_messages = None\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 113, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 114, \"content\": \"def _parse_reasoning_config(effort: str) -> dict | None:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 115, \"content\": \" \\\"\\\"\\\"Parse a reasoning effort level into an OpenRouter reasoning config dict.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 116, \"content\": \" from hermes_constants import parse_reasoning_effort\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 117, \"content\": \" result = parse_reasoning_effort(effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 118, \"content\": \" if effort and effort.strip() and result is None:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 119, \"content\": \" logger.warning(\\\"Unknown reasoning_effort '%s', using default (medium)\\\", effort)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 120, \"content\": \" return result\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 121, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 122, \"content\": \"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 238, \"content\": \" \\\"verbose\\\": False,\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 239, \"content\": \" \\\"system_prompt\\\": \\\"\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 240, \"content\": \" \\\"prefill_messages_file\\\": \\\"\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 241, \"content\": \" \\\"reasoning_effort\\\": \\\"\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 242, \"content\": \" \\\"personalities\\\": {\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 243, \"content\": \" \\\"helpful\\\": \\\"You are a helpful, friendly AI assistant.\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 244, \"content\": \" \\\"concise\\\": \\\"You are a concise assistant. Keep responses brief and to the point.\\\",\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1353, \"content\": \" self.resume_display = CLI_CONFIG[\\\"display\\\"].get(\\\"resume_display\\\", \\\"full\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1354, \"content\": \" # bell_on_complete: play terminal bell (\\\\a) when agent finishes a response\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1355, \"content\": \" self.bell_on_complete = CLI_CONFIG[\\\"display\\\"].get(\\\"bell_on_complete\\\", False)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1356, \"content\": \" # show_reasoning: display model thinking/reasoning before the response\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1357, \"content\": \" self.show_reasoning = CLI_CONFIG[\\\"display\\\"].get(\\\"show_reasoning\\\", False)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1358, \"content\": \" # busy_input_mode: \\\"interrupt\\\" (Enter interrupts current run) or \\\"queue\\\" (Enter queues for next turn)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1359, \"content\": \" _bim = CLI_CONFIG[\\\"display\\\"].get(\\\"busy_input_mode\\\", \\\"interrupt\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1476, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1477, \"content\": \" # Reasoning config (OpenRouter reasoning effort level)\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1478, \"content\": \" self.reasoning_config = _parse_reasoning_config(\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1479, \"content\": \" CLI_CONFIG[\\\"agent\\\"].get(\\\"reasoning_effort\\\", \\\"\\\")\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1480, \"content\": \" )\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1481, \"content\": \" \"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1482, \"content\": \" # OpenRouter provider routing preferences\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1897, \"content\": \" \\\"\\\"\\\"Return the active reasoning display callback for the current mode.\\\"\\\"\\\"\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1898, \"content\": \" if self.show_reasoning and self.streaming_enabled:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1899, \"content\": \" return self._stream_reasoning_delta\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1900, \"content\": \" if self.verbose and not self.show_reasoning:\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1901, \"content\": \" return self._on_reasoning\"}, {\"path\": \"/home/ubuntu/.hermes/hermes-agent/cli.py\", \"line\": 1902, \"content\": \" return None\"}], \"truncated\": true}\n\n[Hint: Results truncated. Use offset=100 to see more, or narrow with a more specific pattern or file_glob.]",
"tool_call_id": "call_iGFZDdfwRsO8ZpNRDuc23uvm"
},
{
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"summary": []
}
],
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{
"role": "tool",
"content": "{\"content\": \" 5318|\\n 5319| def _build_api_kwargs(self, api_messages: list) -> dict:\\n 5320| \\\"\\\"\\\"Build the keyword arguments dict for the active API mode.\\\"\\\"\\\"\\n 5321| if self.api_mode == \\\"anthropic_messages\\\":\\n 5322| from agent.anthropic_adapter import build_anthropic_kwargs\\n 5323| anthropic_messages = self._prepare_anthropic_messages_for_api(api_messages)\\n 5324| # Pass context_length so the adapter can clamp max_tokens if the\\n 5325| # user configured a smaller context window than the model's output limit.\\n 5326| ctx_len = getattr(self, \\\"context_compressor\\\", None)\\n 5327| ctx_len = ctx_len.context_length if ctx_len else None\\n 5328| return build_anthropic_kwargs(\\n 5329| model=self.model,\\n 5330| messages=anthropic_messages,\\n 5331| tools=self.tools,\\n 5332| max_tokens=self.max_tokens,\\n 5333| reasoning_config=self.reasoning_config,\\n 5334| is_oauth=self._is_anthropic_oauth,\\n 5335| preserve_dots=self._anthropic_preserve_dots(),\\n 5336| context_length=ctx_len,\\n 5337| )\\n 5338|\\n 5339| if self.api_mode == \\\"codex_responses\\\":\\n 5340| instructions = \\\"\\\"\\n 5341| payload_messages = api_messages\\n 5342| if api_messages and api_messages[0].get(\\\"role\\\") == \\\"system\\\":\\n 5343| instructions = str(api_messages[0].get(\\\"content\\\") or \\\"\\\").strip()\\n 5344| payload_messages = api_messages[1:]\\n 5345| if not instructions:\\n 5346| instructions = DEFAULT_AGENT_IDENTITY\\n 5347|\\n 5348| is_github_responses = (\\n 5349| \\\"models.github.ai\\\" in self.base_url.lower()\\n 5350| or \\\"api.githubcopilot.com\\\" in self.base_url.lower()\\n 5351| )\\n 5352|\\n 5353| # Resolve reasoning effort: config > default (medium)\\n 5354| reasoning_effort = \\\"medium\\\"\\n 5355| reasoning_enabled = True\\n 5356| if self.reasoning_config and isinstance(self.reasoning_config, dict):\\n 5357| if self.reasoning_config.get(\\\"enabled\\\") is False:\\n 5358| reasoning_enabled = False\\n 5359| elif self.reasoning_config.get(\\\"effort\\\"):\\n 5360| reasoning_effort = self.reasoning_config[\\\"effort\\\"]\\n 5361|\\n 5362| kwargs = {\\n 5363| \\\"model\\\": self.model,\\n 5364| \\\"instructions\\\": instructions,\\n 5365| \\\"input\\\": self._chat_messages_to_responses_input(payload_messages),\\n 5366| \\\"tools\\\": self._responses_tools(),\\n 5367| \\\"tool_choice\\\": \\\"auto\\\",\\n 5368| \\\"parallel_tool_calls\\\": True,\\n 5369| \\\"store\\\": False,\\n 5370| }\\n 5371|\\n 5372| if not is_github_responses:\\n 5373| kwargs[\\\"prompt_cache_key\\\"] = self.session_id\\n 5374|\\n 5375| if reasoning_enabled:\\n 5376| if is_github_responses:\\n 5377| # Copilot's Responses route advertises reasoning-effort support,\\n 5378| # but not OpenAI-specific prompt cache or encrypted reasoning\\n 5379| # fields. Keep the payload to the documented subset.\\n 5380| github_reasoning = self._github_models_reasoning_extra_body()\\n 5381| if github_reasoning is not None:\\n 5382| kwargs[\\\"reasoning\\\"] = github_reasoning\\n 5383| else:\\n 5384| kwargs[\\\"reasoning\\\"] = {\\\"effort\\\": reasoning_effort, \\\"summary\\\": \\\"auto\\\"}\\n 5385| kwargs[\\\"include\\\"] = [\\\"reasoning.encrypted_content\\\"]\\n 5386| elif not is_github_responses:\\n 5387| kwargs[\\\"include\\\"] = []\\n 5388|\", \"total_lines\": 9541, \"file_size\": 481911, \"truncated\": true, \"hint\": \"Use offset=5388 to continue reading (showing 5318-5387 of 9541 lines)\", \"is_binary\": false, \"is_image\": false}",
"tool_call_id": "call_g1JwPHj30D9fyyumPko2rg1X"
},
{
"role": "tool",
"content": "{\"content\": \" 351| def test_includes_reasoning_config(self, monkeypatch):\\n 352| agent = _make_agent(monkeypatch, \\\"openai-codex\\\", api_mode=\\\"codex_responses\\\",\\n 353| base_url=\\\"https://chatgpt.com/backend-api/codex\\\")\\n 354| messages = [{\\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"hi\\\"}]\\n 355| kwargs = agent._build_api_kwargs(messages)\\n 356| assert \\\"reasoning\\\" in kwargs\\n 357| assert kwargs[\\\"reasoning\\\"][\\\"effort\\\"] == \\\"medium\\\"\\n 358|\\n 359| def test_includes_encrypted_content_in_include(self, monkeypatch):\\n 360| agent = _make_agent(monkeypatch, \\\"openai-codex\\\", api_mode=\\\"codex_responses\\\",\\n 361| base_url=\\\"https://chatgpt.com/backend-api/codex\\\")\\n 362| messages = [{\\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"hi\\\"}]\\n 363| kwargs = agent._build_api_kwargs(messages)\\n 364| assert \\\"reasoning.encrypted_content\\\" in kwargs.get(\\\"include\\\", [])\\n 365|\\n 366| def test_tools_converted_to_responses_format(self, monkeypatch):\\n 367| agent = _make_agent(monkeypatch, \\\"openai-codex\\\", api_mode=\\\"codex_responses\\\",\\n 368| base_url=\\\"https://chatgpt.com/backend-api/codex\\\")\\n 369| messages = [{\\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"hi\\\"}]\\n 370| kwargs = agent._build_api_kwargs(messages)\\n 371|\", \"total_lines\": 850, \"file_size\": 39185, \"truncated\": true, \"hint\": \"Use offset=371 to continue reading (showing 351-370 of 850 lines)\", \"is_binary\": false, \"is_image\": false}",
"tool_call_id": "call_zRRIMj8VgpuKxdzO9YT39yzC"
},
{
"role": "tool",
"content": "{\"content\": \" 830| def test_codex_reasoning_disabled(self, monkeypatch):\\n 831| agent = _make_agent(monkeypatch, \\\"openai-codex\\\", api_mode=\\\"codex_responses\\\",\\n 832| base_url=\\\"https://chatgpt.com/backend-api/codex\\\")\\n 833| agent.reasoning_config = {\\\"enabled\\\": False}\\n 834| kwargs = agent._build_api_kwargs([{\\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"hi\\\"}])\\n 835| assert \\\"reasoning\\\" not in kwargs\\n 836| assert kwargs[\\\"include\\\"] == []\\n 837|\\n 838| def test_codex_reasoning_low(self, monkeypatch):\\n 839| agent = _make_agent(monkeypatch, \\\"openai-codex\\\", api_mode=\\\"codex_responses\\\",\\n 840| base_url=\\\"https://chatgpt.com/backend-api/codex\\\")\\n 841| agent.reasoning_config = {\\\"enabled\\\": True, \\\"effort\\\": \\\"low\\\"}\\n 842| kwargs = agent._build_api_kwargs([{\\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"hi\\\"}])\\n 843| assert kwargs[\\\"reasoning\\\"][\\\"effort\\\"] == \\\"low\\\"\\n 844|\\n 845| def test_openrouter_reasoning_config_override(self, monkeypatch):\\n 846| agent = _make_agent(monkeypatch, \\\"openrouter\\\")\\n 847| agent.model = \\\"anthropic/claude-sonnet-4-20250514\\\"\\n 848| agent.reasoning_config = {\\\"enabled\\\": True, \\\"effort\\\": \\\"medium\\\"}\\n 849| kwargs = agent._build_api_kwargs([{\\\"role\\\": \\\"user\\\", \\\"content\\\": \\\"hi\\\"}])\\n 850| assert kwargs[\\\"extra_body\\\"][\\\"reasoning\\\"][\\\"effort\\\"] == \\\"medium\\\"\\n 851|\", \"total_lines\": 850, \"file_size\": 39185, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
"tool_call_id": "call_cwXPoousZ3FxPBg7xCEi9BBk"
},
{
"role": "assistant",
"content": "Mostly yes, but not uniformly.\n\nWhat the code says:\n\n- Hermes CLI/gateway loads one global setting from:\n - `agent.reasoning_effort`\n- That gets parsed into a generic `reasoning_config` and reused when building requests.\n\nProvider behavior I verified:\n- OpenAI Codex responses:\n - Hermes sends `reasoning: {\"effort\": ...}`.\n - Default is `medium` if nothing is set.\n - Your config can override it to `xhigh`.\n- OpenRouter:\n - Hermes sends the reasoning config in `extra_body.reasoning`.\n\nImportant catch:\n- Support is provider/model-specific, not universal.\n- In the WebUI code, reasoning is explicitly clamped per model/provider:\n - OpenRouter Auto Free: unsupported\n - DeepSeek: reasoning is model-based (`chat` vs `reasoner`), not an effort dropdown\n - Kimi “thinking” models: also model-based, not effort-based\n - Some Mistral models: only on/off toggle, not low/medium/high/xhigh\n - If a model doesn’t support the chosen effort, WebUI clears it to `''`\n\nSo the practical answer:\n\n- If you switch to another provider/model that supports effort-style reasoning, yes, `xhigh` should carry over.\n- If you switch to a provider/model that uses a different mechanism or doesn’t support `xhigh`, it won’t apply meaningfully, and in some paths it gets ignored/cleared.\n\nRule of thumb:\n- `openai/gpt-5.4` via OpenAI Codex: yes, likely applies\n- OpenRouter models that support reasoning effort: yes\n- DeepSeek / Kimi thinking variants: no, use the right model instead\n- Some Mistral models: maybe only toggle, not `xhigh`\n\nIf you want, I can inspect the exact provider/model combos you care about and tell you which ones will honor `xhigh` versus ignore it.",
"reasoning": null,
"finish_reason": "stop",
"codex_reasoning_items": [
{
"type": "reasoning",
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"id": "rs_0801a076ed6917a00169d7be43f3c8819889f6888e7aa7ead3",
"summary": []
}
]
},
{
"role": "user",
"content": "Review the conversation above and consider saving or updating a skill if appropriate.\n\nFocus on: was a non-trivial approach used to complete a task that required trial and error, or changing course due to experiential findings along the way, or did the user expect or desire a different method or outcome?\n\nIf a relevant skill already exists, update it with what you learned. Otherwise, create a new skill if the approach is reusable.\nIf nothing is worth saving, just say 'Nothing to save.' and stop."
},
{
"role": "assistant",
"content": "",
"reasoning": "**Assessing skill updates**\n\nI’m working on figuring out if a skill update or creation is necessary. I looked into a configuration mismatch with Hermes regarding the reasoning setting. The key for OPENAI_REASONING_EFFORT might be wrong, as the actual key is agent.reasoning_effort. I'll consider if there's an existing skill for the hermes-agent and think about updating it. The user explicitly requested a review, and I likely need to create or adjust the skill if it's useful. I'll search through the skill list to explore options.",
"finish_reason": "tool_calls",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABp175pJ6f-kgt0j2-Em7GJHnbW5d8236fdKvp9Elc7hrvwwuawENUlfHl5kS6yVoy_AyKphAfm7jTCV4jctUbn_sBQXkY2POkGDCaJn8saqtIW-h29GV7NhgxN0Lj6CIiNgiFkMr79td_ABjupxR2Hyws7Khjf1GhYTz7_uhipN7x1aqT_WZxjXDT7lmGNs0y_cJtmNwYASJEWWfbwSBVB2kF1Kx_46kNFdZEqAP1jPnu5u2TkgQZlB4YycBUu5BexJbOlzB0lao47jefoVIOjmJOBLIftjsQrF0pRAAKTNI_lcx7rmAqEdBvc5-eI9Olxcrw-3W0gWKsW0gB5oTN9elJ4OCH0DG3VzBG5FbKmf1nvHiznV5WmfUa9g_ZyEqV9XE17hn4UA6wv4ip-gYGYVlGI8c0RPFBrIlhqb3E1tRwf3cmHF8bIn8hC25lO9hp2NUFAk_xCOYb7vJqo-54R09qYDfAhq4QF0LFfGdZScLe8NYz8J7TGleNz7ckDhLEf35APr2E2nJLCvcKKzfzoVL5FqBE06_f0Iyc0oUNXk2Fh_X52XJGx9rQP8dIzx6KSoTkf8trfTDVKHo-0MUQWw-n-p1ns4BQAQ6Jj7dJy10lBFpSk3f2-P7uMRStDKx9r5B-JrcGHKui_9ruK7If39jPGcA0G4sZZQ7Vz1ZS8eJHzhWBFP77WlsZCRIAeuXq8F_rS-fc-8yWo8swIydkUhgJOckvccbahe5tpaKoN_W0lAaOgfofd858qvpsKc_oBpwfSEKFYuKsUfwoDFjQeXmZuV0VCzjxewalTE9BNhuv8xpbX1UVkkuK5Z0VEWiFoVjvptm5drWEwNhg9cU3j8766FDMHtmh_5QLdwHrx7G0waUhZxEooZ0BIQgFF2QKvJO1oiddrFUhFlQPnJ5JP4oF79QBYbi-x7Ug3Eq5nozfpCaorcXj-CzSoeLZ7OdxSnJIk_caAORLw6-sRj-fL9hdWaJCkqnrffwH35JbsMuZpD0_NbGeRskbW3xYheSNYXvSZzBl8OGDhY6N8Oyx94UF95sJQTebPukcMIRS9JzOi8tB84TLJG6gBz5TZPqgdbiXvGsVTLXqb7H2DHNTXfoaC5ajpdwVOBcDOY0qSv2C6Kc7CeNBoODK6-y8P55tOSxLRDCczFYrli4VCTE37vZA29vb6OoL1tL8eNgohYGPXDgIUFPrwP-wSX7iDM845yqVp790XfWEo7h61QqDQDBbBiuwMwqEe_RW8zr3nUzb2V5ApZVKUbK9KRQA_EenEnjKEc76awpj9yzGx7YzGpgSiS-iwOBeorPWsisA4oipF0YFMwNWXGWbc3kGUlmPvHkzmrV2JqVeMhTM7HZVsD1ajBp3mOPSc116tQi--K6Fn__h75oSmRNKHYSl83OAZATR3TVsI9RMoL4FSb68qFmst3EBlmLO2Y0aaZQP37M1rLYXZaK7tRnn-E0aB0IrOO4LKDH5zaapYdG1y2eULr3FNt13eVnMYSvFA4xGAiwd6jA_POgbNkk6b9s9nShseOg0RqlmBcMkDmVJLvHstrcwXCeBySVU99b-OSxNqgeD87VdL_Qskxa5Dcrp9QUyGyoNziQYkQTah_tVwet7VOgGOt4c4vvQLd2WQY5n-mLaxpCG2jiXJEVf7ftKKYZsjkKzP",
"id": "rs_0801a076ed6917a00169d7be61135481989ab6fec7e7399de2",
"summary": [
{
"type": "summary_text",
"text": "**Assessing skill updates**\n\nI’m working on figuring out if a skill update or creation is necessary. I looked into a configuration mismatch with Hermes regarding the reasoning setting. The key for OPENAI_REASONING_EFFORT might be wrong, as the actual key is agent.reasoning_effort. I'll consider if there's an existing skill for the hermes-agent and think about updating it. The user explicitly requested a review, and I likely need to create or adjust the skill if it's useful. I'll search through the skill list to explore options."
}
]
}
],
"tool_calls": [
{
"id": "call_kdqnSt0YdVrWLHo0EvzUt3Tq",
"call_id": "call_kdqnSt0YdVrWLHo0EvzUt3Tq",
"response_item_id": "fc_0801a076ed6917a00169d7be69f5788198b7e1d3621c3b63f8",
"type": "function",
"function": {
"name": "skill_view",
"arguments": "{\"name\":\"hermes-agent\"}"
}
}
]
},
{
"role": "tool",
"content": "{\"success\": true, \"name\": \"hermes-agent\", \"description\": \"Complete guide to using and extending Hermes Agent — CLI usage, setup, configuration, spawning additional agents, gateway platforms, skills, voice, tools, profiles, and a concise contributor reference. Load this skill when helping users configure Hermes, troubleshoot issues, spawn agent instances, or make code contributions.\", \"tags\": [\"hermes\", \"setup\", \"configuration\", \"multi-agent\", \"spawning\", \"cli\", \"gateway\", \"development\"], \"related_skills\": [\"claude-code\", \"codex\", \"opencode\"], \"content\": \"---\\nname: hermes-agent\\ndescription: Complete guide to using and extending Hermes Agent — CLI usage, setup, configuration, spawning additional agents, gateway platforms, skills, voice, tools, profiles, and a concise contributor reference. Load this skill when helping users configure Hermes, troubleshoot issues, spawn agent instances, or make code contributions.\\nversion: 2.0.0\\nauthor: Hermes Agent + Teknium\\nlicense: MIT\\nmetadata:\\n hermes:\\n tags: [hermes, setup, configuration, multi-agent, spawning, cli, gateway, development]\\n homepage: https://github.com/NousResearch/hermes-agent\\n related_skills: [claude-code, codex, opencode]\\n---\\n\\n# Hermes Agent\\n\\nHermes Agent is an open-source AI agent framework by Nous Research that runs in your terminal, messaging platforms, and IDEs. It belongs to the same category as Claude Code (Anthropic), Codex (OpenAI), and OpenClaw — autonomous coding and task-execution agents that use tool calling to interact with your system. Hermes works with any LLM provider (OpenRouter, Anthropic, OpenAI, DeepSeek, local models, and 15+ others) and runs on Linux, macOS, and WSL.\\n\\nWhat makes Hermes different:\\n\\n- **Self-improving through skills** — Hermes learns from experience by saving reusable procedures as skills. When it solves a complex problem, discovers a workflow, or gets corrected, it can persist that knowledge as a skill document that loads into future sessions. Skills accumulate over time, making the agent better at your specific tasks and environment.\\n- **Persistent memory across sessions** — remembers who you are, your preferences, environment details, and lessons learned. Pluggable memory backends (built-in, Honcho, Mem0, and more) let you choose how memory works.\\n- **Multi-platform gateway** — the same agent runs on Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Email, and 8+ other platforms with full tool access, not just chat.\\n- **Provider-agnostic** — swap models and providers mid-workflow without changing anything else. Credential pools rotate across multiple API keys automatically.\\n- **Profiles** — run multiple independent Hermes instances with isolated configs, sessions, skills, and memory.\\n- **Extensible** — plugins, MCP servers, custom tools, webhook triggers, cron scheduling, and the full Python ecosystem.\\n\\nPeople use Hermes for software development, research, system administration, data analysis, content creation, home automation, and anything else that benefits from an AI agent with persistent context and full system access.\\n\\n**This skill helps you work with Hermes Agent effectively** — setting it up, configuring features, spawning additional agent instances, troubleshooting issues, finding the right commands and settings, and understanding how the system works when you need to extend or contribute to it.\\n\\n**Docs:** https://hermes-agent.nousresearch.com/docs/\\n\\n## Quick Start\\n\\n```bash\\n# Install\\ncurl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash\\n\\n# Interactive chat (default)\\nhermes\\n\\n# Single query\\nhermes chat -q \\\"What is the capital of France?\\\"\\n\\n# Setup wizard\\nhermes setup\\n\\n# Change model/provider\\nhermes model\\n\\n# Check health\\nhermes doctor\\n```\\n\\n---\\n\\n## CLI Reference\\n\\n### Global Flags\\n\\n```\\nhermes [flags] [command]\\n\\n --version, -V Show version\\n --resume, -r SESSION Resume session by ID or title\\n --continue, -c [NAME] Resume by name, or most recent session\\n --worktree, -w Isolated git worktree mode (parallel agents)\\n --skills, -s SKILL Preload skills (comma-separate or repeat)\\n --profile, -p NAME Use a named profile\\n --yolo Skip dangerous command approval\\n --pass-session-id Include session ID in system prompt\\n```\\n\\nNo subcommand defaults to `chat`.\\n\\n### Chat\\n\\n```\\nhermes chat [flags]\\n -q, --query TEXT Single query, non-interactive\\n -m, --model MODEL Model (e.g. anthropic/claude-sonnet-4)\\n -t, --toolsets LIST Comma-separated toolsets\\n --provider PROVIDER Force provider (openrouter, anthropic, nous, etc.)\\n -v, --verbose Verbose output\\n -Q, --quiet Suppress banner, spinner, tool previews\\n --checkpoints Enable filesystem checkpoints (/rollback)\\n --source TAG Session source tag (default: cli)\\n```\\n\\n### Configuration\\n\\n```\\nhermes setup [section] Interactive wizard (model|terminal|gateway|tools|agent)\\nhermes model Interactive model/provider picker\\nhermes config View current config\\nhermes config edit Open config.yaml in $EDITOR\\nhermes config set KEY VAL Set a config value\\nhermes config path Print config.yaml path\\nhermes config env-path Print .env path\\nhermes config check Check for missing/outdated config\\nhermes config migrate Update config with new options\\nhermes login [--provider P] OAuth login (nous, openai-codex)\\nhermes logout Clear stored auth\\nhermes doctor [--fix] Check dependencies and config\\nhermes status [--all] Show component status\\n```\\n\\n### Tools & Skills\\n\\n```\\nhermes tools Interactive tool enable/disable (curses UI)\\nhermes tools list Show all tools and status\\nhermes tools enable NAME Enable a toolset\\nhermes tools disable NAME Disable a toolset\\n\\nhermes skills list List installed skills\\nhermes skills search QUERY Search the skills hub\\nhermes skills install ID Install a skill\\nhermes skills inspect ID Preview without installing\\nhermes skills config Enable/disable skills per platform\\nhermes skills check Check for updates\\nhermes skills update Update outdated skills\\nhermes skills uninstall N Remove a hub skill\\nhermes skills publish PATH Publish to registry\\nhermes skills browse Browse all available skills\\nhermes skills tap add REPO Add a GitHub repo as skill source\\n```\\n\\n### MCP Servers\\n\\n```\\nhermes mcp serve Run Hermes as an MCP server\\nhermes mcp add NAME Add an MCP server (--url or --command)\\nhermes mcp remove NAME Remove an MCP server\\nhermes mcp list List configured servers\\nhermes mcp test NAME Test connection\\nhermes mcp configure NAME Toggle tool selection\\n```\\n\\n### Gateway (Messaging Platforms)\\n\\n```\\nhermes gateway run Start gateway foreground\\nhermes gateway install Install as background service\\nhermes gateway start/stop Control the service\\nhermes gateway restart Restart the service\\nhermes gateway status Check status\\nhermes gateway setup Configure platforms\\n```\\n\\nSupported platforms: Telegram, Discord, Slack, WhatsApp, Signal, Email, SMS, Matrix, Mattermost, Home Assistant, DingTalk, Feishu, WeCom, API Server, Webhooks, Open WebUI.\\n\\nPlatform docs: https://hermes-agent.nousresearch.com/docs/user-guide/messaging/\\n\\n### Sessions\\n\\n```\\nhermes sessions list List recent sessions\\nhermes sessions browse Interactive picker\\nhermes sessions export OUT Export to JSONL\\nhermes sessions rename ID T Rename a session\\nhermes sessions delete ID Delete a session\\nhermes sessions prune Clean up old sessions (--older-than N days)\\nhermes sessions stats Session store statistics\\n```\\n\\n### Cron Jobs\\n\\n```\\nhermes cron list List jobs (--all for disabled)\\nhermes cron create SCHED Create: '30m', 'every 2h', '0 9 * * *'\\nhermes cron edit ID Edit schedule, prompt, delivery\\nhermes cron pause/resume ID Control job state\\nhermes cron run ID Trigger on next tick\\nhermes cron remove ID Delete a job\\nhermes cron status Scheduler status\\n```\\n\\n### Webhooks\\n\\n```\\nhermes webhook subscribe N Create route at /webhooks/\\nhermes webhook list List subscriptions\\nhermes webhook remove NAME Remove a subscription\\nhermes webhook test NAME Send a test POST\\n```\\n\\n### Profiles\\n\\n```\\nhermes profile list List all profiles\\nhermes profile create NAME Create (--clone, --clone-all, --clone-from)\\nhermes profile use NAME Set sticky default\\nhermes profile delete NAME Delete a profile\\nhermes profile show NAME Show details\\nhermes profile alias NAME Manage wrapper scripts\\nhermes profile rename A B Rename a profile\\nhermes profile export NAME Export to tar.gz\\nhermes profile import FILE Import from archive\\n```\\n\\n### Credential Pools\\n\\n```\\nhermes auth add Interactive credential wizard\\nhermes auth list [PROVIDER] List pooled credentials\\nhermes auth remove P INDEX Remove by provider + index\\nhermes auth reset PROVIDER Clear exhaustion status\\n```\\n\\n### Other\\n\\n```\\nhermes insights [--days N] Usage analytics\\nhermes update Update to latest version\\nhermes pairing list/approve/revoke DM authorization\\nhermes plugins list/install/remove Plugin management\\nhermes honcho setup/status Honcho memory integration\\nhermes memory setup/status/off Memory provider config\\nhermes completion bash|zsh Shell completions\\nhermes acp ACP server (IDE integration)\\nhermes claw migrate Migrate from OpenClaw\\nhermes uninstall Uninstall Hermes\\n```\\n\\n---\\n\\n## Slash Commands (In-Session)\\n\\nType these during an interactive chat session.\\n\\n### Session Control\\n```\\n/new (/reset) Fresh session\\n/clear Clear screen + new session (CLI)\\n/retry Resend last message\\n/undo Remove last exchange\\n/title [name] Name the session\\n/compress Manually compress context\\n/stop Kill background processes\\n/rollback [N] Restore filesystem checkpoint\\n/background Run prompt in background\\n/queue Queue for next turn\\n/resume [name] Resume a named session\\n```\\n\\n### Configuration\\n```\\n/config Show config (CLI)\\n/model [name] Show or change model\\n/provider Show provider info\\n/prompt [text] View/set system prompt (CLI)\\n/personality [name] Set personality\\n/reasoning [level] Set reasoning (none|low|medium|high|xhigh|show|hide)\\n/verbose Cycle: off → new → all → verbose\\n/voice [on|off|tts] Voice mode\\n/yolo Toggle approval bypass\\n/skin [name] Change theme (CLI)\\n/statusbar Toggle status bar (CLI)\\n```\\n\\n### Tools & Skills\\n```\\n/tools Manage tools (CLI)\\n/toolsets List toolsets (CLI)\\n/skills Search/install skills (CLI)\\n/skill Load a skill into session\\n/cron Manage cron jobs (CLI)\\n/reload-mcp Reload MCP servers\\n/plugins List plugins (CLI)\\n```\\n\\n### Info\\n```\\n/help Show commands\\n/commands [page] Browse all commands (gateway)\\n/usage Token usage\\n/insights [days] Usage analytics\\n/status Session info (gateway)\\n/profile Active profile info\\n```\\n\\n### Exit\\n```\\n/quit (/exit, /q) Exit CLI\\n```\\n\\n---\\n\\n## Key Paths & Config\\n\\n```\\n~/.hermes/config.yaml Main configuration\\n~/.hermes/.env API keys and secrets\\n~/.hermes/skills/ Installed skills\\n~/.hermes/sessions/ Session transcripts\\n~/.hermes/logs/ Gateway and error logs\\n~/.hermes/auth.json OAuth tokens and credential pools\\n~/.hermes/hermes-agent/ Source code (if git-installed)\\n```\\n\\nProfiles use `~/.hermes/profiles//` with the same layout.\\n\\n### Config Sections\\n\\nEdit with `hermes config edit` or `hermes config set section.key value`.\\n\\n| Section | Key options |\\n|---------|-------------|\\n| `model` | `default`, `provider`, `base_url`, `api_key`, `context_length` |\\n| `agent` | `max_turns` (90), `tool_use_enforcement` |\\n| `terminal` | `backend` (local/docker/ssh/modal), `cwd`, `timeout` (180) |\\n| `compression` | `enabled`, `threshold` (0.50), `target_ratio` (0.20) |\\n| `display` | `skin`, `tool_progress`, `show_reasoning`, `show_cost` |\\n| `stt` | `enabled`, `provider` (local/groq/openai) |\\n| `tts` | `provider` (edge/elevenlabs/openai/kokoro/fish) |\\n| `memory` | `memory_enabled`, `user_profile_enabled`, `provider` |\\n| `security` | `tirith_enabled`, `website_blocklist` |\\n| `delegation` | `model`, `provider`, `max_iterations` (50) |\\n| `smart_model_routing` | `enabled`, `cheap_model` |\\n| `checkpoints` | `enabled`, `max_snapshots` (50) |\\n\\nFull config reference: https://hermes-agent.nousresearch.com/docs/user-guide/configuration\\n\\n### Providers\\n\\n18 providers supported. Set via `hermes model` or `hermes setup`.\\n\\n| Provider | Auth | Key env var |\\n|----------|------|-------------|\\n| OpenRouter | API key | `OPENROUTER_API_KEY` |\\n| Anthropic | API key | `ANTHROPIC_API_KEY` |\\n| Nous Portal | OAuth | `hermes login --provider nous` |\\n| OpenAI Codex | OAuth | `hermes login --provider openai-codex` |\\n| GitHub Copilot | Token | `COPILOT_GITHUB_TOKEN` |\\n| DeepSeek | API key | `DEEPSEEK_API_KEY` |\\n| Hugging Face | Token | `HF_TOKEN` |\\n| Z.AI / GLM | API key | `GLM_API_KEY` |\\n| MiniMax | API key | `MINIMAX_API_KEY` |\\n| Kimi / Moonshot | API key | `KIMI_API_KEY` |\\n| Alibaba / DashScope | API key | `DASHSCOPE_API_KEY` |\\n| Kilo Code | API key | `KILOCODE_API_KEY` |\\n| Custom endpoint | Config | `model.base_url` + `model.api_key` in config.yaml |\\n\\nPlus: AI Gateway, OpenCode Zen, OpenCode Go, MiniMax CN, GitHub Copilot ACP.\\n\\nFull provider docs: https://hermes-agent.nousresearch.com/docs/integrations/providers\\n\\n### Toolsets\\n\\nEnable/disable via `hermes tools` (interactive) or `hermes tools enable/disable NAME`.\\n\\n| Toolset | What it provides |\\n|---------|-----------------|\\n| `web` | Web search and content extraction |\\n| `browser` | Browser automation (Browserbase, Camofox, or local Chromium) |\\n| `terminal` | Shell commands and process management |\\n| `file` | File read/write/search/patch |\\n| `code_execution` | Sandboxed Python execution |\\n| `vision` | Image analysis |\\n| `image_gen` | AI image generation |\\n| `tts` | Text-to-speech |\\n| `skills` | Skill browsing and management |\\n| `memory` | Persistent cross-session memory |\\n| `session_search` | Search past conversations |\\n| `delegation` | Subagent task delegation |\\n| `cronjob` | Scheduled task management |\\n| `clarify` | Ask user clarifying questions |\\n| `moa` | Mixture of Agents (off by default) |\\n| `homeassistant` | Smart home control (off by default) |\\n\\nTool changes take effect on `/reset` (new session). They do NOT apply mid-conversation to preserve prompt caching.\\n\\n---\\n\\n## Voice & Transcription\\n\\n### STT (Voice → Text)\\n\\nVoice messages from messaging platforms are auto-transcribed.\\n\\nProvider priority (auto-detected):\\n1. **Local faster-whisper** — free, no API key: `pip install faster-whisper`\\n2. **Groq Whisper** — free tier: set `GROQ_API_KEY`\\n3. **OpenAI Whisper** — paid: set `VOICE_TOOLS_OPENAI_KEY`\\n\\nConfig:\\n```yaml\\nstt:\\n enabled: true\\n provider: local # local, groq, openai\\n local:\\n model: base # tiny, base, small, medium, large-v3\\n```\\n\\n### TTS (Text → Voice)\\n\\n| Provider | Env var | Free? |\\n|----------|---------|-------|\\n| Edge TTS | None | Yes (default) |\\n| ElevenLabs | `ELEVENLABS_API_KEY` | Free tier |\\n| OpenAI | `VOICE_TOOLS_OPENAI_KEY` | Paid |\\n| Kokoro (local) | None | Free |\\n| Fish Audio | `FISH_AUDIO_API_KEY` | Free tier |\\n\\nVoice commands: `/voice on` (voice-to-voice), `/voice tts` (always voice), `/voice off`.\\n\\n---\\n\\n## Spawning Additional Hermes Instances\\n\\nRun additional Hermes processes as fully independent subprocesses — separate sessions, tools, and environments.\\n\\n### When to Use This vs delegate_task\\n\\n| | `delegate_task` | Spawning `hermes` process |\\n|-|-----------------|--------------------------|\\n| Isolation | Separate conversation, shared process | Fully independent process |\\n| Duration | Minutes (bounded by parent loop) | Hours/days |\\n| Tool access | Subset of parent's tools | Full tool access |\\n| Interactive | No | Yes (PTY mode) |\\n| Use case | Quick parallel subtasks | Long autonomous missions |\\n\\n### One-Shot Mode\\n\\n```\\nterminal(command=\\\"hermes chat -q 'Research GRPO papers and write summary to ~/research/grpo.md'\\\", timeout=300)\\n\\n# Background for long tasks:\\nterminal(command=\\\"hermes chat -q 'Set up CI/CD for ~/myapp'\\\", background=true)\\n```\\n\\n### Interactive PTY Mode (via tmux)\\n\\nHermes uses prompt_toolkit, which requires a real terminal. Use tmux for interactive spawning:\\n\\n```\\n# Start\\nterminal(command=\\\"tmux new-session -d -s agent1 -x 120 -y 40 'hermes'\\\", timeout=10)\\n\\n# Wait for startup, then send a message\\nterminal(command=\\\"sleep 8 && tmux send-keys -t agent1 'Build a FastAPI auth service' Enter\\\", timeout=15)\\n\\n# Read output\\nterminal(command=\\\"sleep 20 && tmux capture-pane -t agent1 -p\\\", timeout=5)\\n\\n# Send follow-up\\nterminal(command=\\\"tmux send-keys -t agent1 'Add rate limiting middleware' Enter\\\", timeout=5)\\n\\n# Exit\\nterminal(command=\\\"tmux send-keys -t agent1 '/exit' Enter && sleep 2 && tmux kill-session -t agent1\\\", timeout=10)\\n```\\n\\n### Multi-Agent Coordination\\n\\n```\\n# Agent A: backend\\nterminal(command=\\\"tmux new-session -d -s backend -x 120 -y 40 'hermes -w'\\\", timeout=10)\\nterminal(command=\\\"sleep 8 && tmux send-keys -t backend 'Build REST API for user management' Enter\\\", timeout=15)\\n\\n# Agent B: frontend\\nterminal(command=\\\"tmux new-session -d -s frontend -x 120 -y 40 'hermes -w'\\\", timeout=10)\\nterminal(command=\\\"sleep 8 && tmux send-keys -t frontend 'Build React dashboard for user management' Enter\\\", timeout=15)\\n\\n# Check progress, relay context between them\\nterminal(command=\\\"tmux capture-pane -t backend -p | tail -30\\\", timeout=5)\\nterminal(command=\\\"tmux send-keys -t frontend 'Here is the API schema from the backend agent: ...' Enter\\\", timeout=5)\\n```\\n\\n### Session Resume\\n\\n```\\n# Resume most recent session\\nterminal(command=\\\"tmux new-session -d -s resumed 'hermes --continue'\\\", timeout=10)\\n\\n# Resume specific session\\nterminal(command=\\\"tmux new-session -d -s resumed 'hermes --resume 20260225_143052_a1b2c3'\\\", timeout=10)\\n```\\n\\n### Tips\\n\\n- **Prefer `delegate_task` for quick subtasks** — less overhead than spawning a full process\\n- **Use `-w` (worktree mode)** when spawning agents that edit code — prevents git conflicts\\n- **Set timeouts** for one-shot mode — complex tasks can take 5-10 minutes\\n- **Use `hermes chat -q` for fire-and-forget** — no PTY needed\\n- **Use tmux for interactive sessions** — raw PTY mode has `\\\\r` vs `\\\\n` issues with prompt_toolkit\\n- **For scheduled tasks**, use the `cronjob` tool instead of spawning — handles delivery and retry\\n\\n---\\n\\n## Troubleshooting\\n\\n### Voice not working\\n1. Check `stt.enabled: true` in config.yaml\\n2. Verify provider: `pip install faster-whisper` or set API key\\n3. Restart gateway: `/restart`\\n\\n### Tool not available\\n1. `hermes tools` — check if toolset is enabled for your platform\\n2. Some tools need env vars (check `.env`)\\n3. `/reset` after enabling tools\\n\\n### Model/provider issues\\n1. `hermes doctor` — check config and dependencies\\n2. `hermes login` — re-authenticate OAuth providers\\n3. Check `.env` has the right API key\\n\\n### Changes not taking effect\\n- **Tools/skills:** `/reset` starts a new session with updated toolset\\n- **Config changes:** `/restart` reloads gateway config\\n- **Code changes:** Restart the CLI or gateway process\\n\\n### Skills not showing\\n1. `hermes skills list` — verify installed\\n2. `hermes skills config` — check platform enablement\\n3. Load explicitly: `/skill name` or `hermes -s name`\\n\\n### `hermes update` hit a merge conflict\\n\\nSymptoms: gateway fails with `SyntaxError: expected 'except' or 'finally' block` in `api_server.py`, or `git status` shows `both modified` files.\\n\\nRoot cause: local customizations (e.g., custom API endpoints, method renames) were stashed before the update, then re-applied on top of refactored upstream code, leaving conflict markers (`<<<<<<< Updated upstream`) in source files.\\n\\nFix:\\n```bash\\ncd ~/.hermes/hermes-agent\\n# Check for conflict markers:\\ngrep -rn \\\"<<<<<<\\\\|======\\\\|>>>>>>\\\" gateway/\\n# Discard stale local changes:\\ngit checkout -- gateway/platforms/api_server.py gateway/platforms/discord.py gateway/run.py\\n# Also clean .orig files and clear pycache:\\nfind gateway/ -name '*.orig' -delete\\nfind . -type d -name '__pycache__' -exec rm -rf {} + 2>/dev/null\\n# Restart:\\nhermes gateway run --replace\\n```\\n\\nTo preserve local customizations across updates:\\n- Don't let `hermes update` auto-restore the stash — review the diff first with `git stash show -p stash@{0}`\\n- If the upstream already includes your changes, drop the stash entirely\\n- For persistent local patches, consider a fork or document them as patches to re-apply after update\\n\\n### Gateway issues\\nCheck logs first:\\n```bash\\ngrep -i \\\"failed to send\\\\\\\\|error\\\" ~/.hermes/logs/gateway.log | tail -20\\n```\\n\\n---\\n\\n## Where to Find Things\\n\\n| Looking for... | Location |\\n|----------------|----------|\\n| Config options | `hermes config edit` or [Configuration docs](https://hermes-agent.nousresearch.com/docs/user-guide/configuration) |\\n| Available tools | `hermes tools list` or [Tools reference](https://hermes-agent.nousresearch.com/docs/reference/tools-reference) |\\n| Slash commands | `/help` in session or [Slash commands reference](https://hermes-agent.nousresearch.com/docs/reference/slash-commands) |\\n| Skills catalog | `hermes skills browse` or [Skills catalog](https://hermes-agent.nousresearch.com/docs/reference/skills-catalog) |\\n| Provider setup | `hermes model` or [Providers guide](https://hermes-agent.nousresearch.com/docs/integrations/providers) |\\n| Platform setup | `hermes gateway setup` or [Messaging docs](https://hermes-agent.nousresearch.com/docs/user-guide/messaging/) |\\n| MCP servers | `hermes mcp list` or [MCP guide](https://hermes-agent.nousresearch.com/docs/user-guide/features/mcp) |\\n| Profiles | `hermes profile list` or [Profiles docs](https://hermes-agent.nousresearch.com/docs/user-guide/profiles) |\\n| Cron jobs | `hermes cron list` or [Cron docs](https://hermes-agent.nousresearch.com/docs/user-guide/features/cron) |\\n| Memory | `hermes memory status` or [Memory docs](https://hermes-agent.nousresearch.com/docs/user-guide/features/memory) |\\n| Env variables | `hermes config env-path` or [Env vars reference](https://hermes-agent.nousresearch.com/docs/reference/environment-variables) |\\n| CLI commands | `hermes --help` or [CLI reference](https://hermes-agent.nousresearch.com/docs/reference/cli-commands) |\\n| Gateway logs | `~/.hermes/logs/gateway.log` |\\n| Session files | `~/.hermes/sessions/` or `hermes sessions browse` |\\n| Source code | `~/.hermes/hermes-agent/` |\\n\\n---\\n\\n## Contributor Quick Reference\\n\\nFor occasional contributors and PR authors. Full developer docs: https://hermes-agent.nousresearch.com/docs/developer-guide/\\n\\n### Project Layout\\n\\n```\\nhermes-agent/\\n├── run_agent.py # AIAgent — core conversation loop\\n├── model_tools.py # Tool discovery and dispatch\\n├── toolsets.py # Toolset definitions\\n├── cli.py # Interactive CLI (HermesCLI)\\n├── hermes_state.py # SQLite session store\\n├── agent/ # Prompt builder, compression, display, adapters\\n├── hermes_cli/ # CLI subcommands, config, setup, commands\\n│ ├── commands.py # Slash command registry (CommandDef)\\n│ ├── config.py # DEFAULT_CONFIG, env var definitions\\n│ └── main.py # CLI entry point and argparse\\n├── tools/ # One file per tool\\n│ └── registry.py # Central tool registry\\n├── gateway/ # Messaging gateway\\n│ └── platforms/ # Platform adapters (telegram, discord, etc.)\\n├── cron/ # Job scheduler\\n├── tests/ # ~3000 pytest tests\\n└── website/ # Docusaurus docs site\\n```\\n\\nConfig: `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys).\\n\\n### Adding a Tool (3 files)\\n\\n**1. Create `tools/your_tool.py`:**\\n```python\\nimport json, os\\nfrom tools.registry import registry\\n\\ndef check_requirements() -> bool:\\n return bool(os.getenv(\\\"EXAMPLE_API_KEY\\\"))\\n\\ndef example_tool(param: str, task_id: str = None) -> str:\\n return json.dumps({\\\"success\\\": True, \\\"data\\\": \\\"...\\\"})\\n\\nregistry.register(\\n name=\\\"example_tool\\\",\\n toolset=\\\"example\\\",\\n schema={\\\"name\\\": \\\"example_tool\\\", \\\"description\\\": \\\"...\\\", \\\"parameters\\\": {...}},\\n handler=lambda args, **kw: example_tool(\\n param=args.get(\\\"param\\\", \\\"\\\"), task_id=kw.get(\\\"task_id\\\")),\\n check_fn=check_requirements,\\n requires_env=[\\\"EXAMPLE_API_KEY\\\"],\\n)\\n```\\n\\n**2. Add import** in `model_tools.py` → `_discover_tools()` list.\\n\\n**3. Add to `toolsets.py`** → `_HERMES_CORE_TOOLS` list.\\n\\nAll handlers must return JSON strings. Use `get_hermes_home()` for paths, never hardcode `~/.hermes`.\\n\\n### Adding a Slash Command\\n\\n1. Add `CommandDef` to `COMMAND_REGISTRY` in `hermes_cli/commands.py`\\n2. Add handler in `cli.py` → `process_command()`\\n3. (Optional) Add gateway handler in `gateway/run.py`\\n\\nAll consumers (help text, autocomplete, Telegram menu, Slack mapping) derive from the central registry automatically.\\n\\n### Agent Loop (High Level)\\n\\n```\\nrun_conversation():\\n 1. Build system prompt\\n 2. Loop while iterations < max:\\n a. Call LLM (OpenAI-format messages + tool schemas)\\n b. If tool_calls → dispatch each via handle_function_call() → append results → continue\\n c. If text response → return\\n 3. Context compression triggers automatically near token limit\\n```\\n\\n### Testing\\n\\n```bash\\nsource venv/bin/activate # or .venv/bin/activate\\npython -m pytest tests/ -o 'addopts=' -q # Full suite\\npython -m pytest tests/tools/ -q # Specific area\\n```\\n\\n- Tests auto-redirect `HERMES_HOME` to temp dirs — never touch real `~/.hermes/`\\n- Run full suite before pushing any change\\n- Use `-o 'addopts='` to clear any baked-in pytest flags\\n\\n### Commit Conventions\\n\\n```\\ntype: concise subject line\\n\\nOptional body.\\n```\\n\\nTypes: `fix:`, `feat:`, `refactor:`, `docs:`, `chore:`\\n\\n### Key Rules\\n\\n- **Never break prompt caching** — don't change context, tools, or system prompt mid-conversation\\n- **Message role alternation** — never two assistant or two user messages in a row\\n- Use `get_hermes_home()` from `hermes_constants` for all paths (profile-safe)\\n- Config values go in `config.yaml`, secrets go in `.env`\\n- New tools need a `check_fn` so they only appear when requirements are met\\n\", \"path\": \"autonomous-ai-agents/hermes-agent/SKILL.md\", \"linked_files\": null, \"usage_hint\": null, \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\", \"metadata\": {\"hermes\": {\"tags\": [\"hermes\", \"setup\", \"configuration\", \"multi-agent\", \"spawning\", \"cli\", \"gateway\", \"development\"], \"homepage\": \"https://github.com/NousResearch/hermes-agent\", \"related_skills\": [\"claude-code\", \"codex\", \"opencode\"]}}}",
"tool_call_id": "call_kdqnSt0YdVrWLHo0EvzUt3Tq"
},
{
"role": "assistant",
"content": "",
"reasoning": "**Patching troubleshooting notes**\n\nI need to focus on patching my skills with relevant notes in troubleshooting and configuration. Specifically, I should reference the actual key for agent reasoning effort, since the top-level OPENAI_REASONING_EFFORT is ignored in the CLI or gateway. I must also remember to include details for provider support. It seems like I should patch the relevant section under the Configuration or model/provider issues, possibly in relation to the slash command for reasoning efforts.",
"finish_reason": "tool_calls",
"codex_reasoning_items": [
{
"type": "reasoning",
"encrypted_content": "gAAAAABp175yB_o_D0f1hFbkOTx1WKxPoFsEVSrpd05QmYNyf5oTw9aukXNXvYEmILt6jma7hdOd3e1FwU4iRRQagzOEyWpjouvzBWBT10MARRIlVK_5qo8sOCjUfgrNrmMr2__rPEuJ3ibgjo0_WfQWUN7aYpUmlkLcEST8S5cVi0X0DaELRYjBrHbbc7cNxNkX0pnz11cKlNWlvCkwcA6y6LZrf485SxLw43Zv2aYwkEVOlK6xKZ3O73RhK5d3tdknFQ8NScZ7tXFwZ6jPvruwN5yKFgQ3sFFdGXUjw9BKc6rEI9B623TyOhV1EA21xVGvo17HvxPdN2ikFTxoVZ3uSUI4KGkjBRewDiJwMK9ePi9IGzBOWbNOBQ3-vU_yoxuJAgOLy06cX_dyuydD_IMQNMWyIqu88-M6igiZG9w-nYOjTJmPAJ8yy42gRW8sa51jB5ST_F1OCE3dAwQzYrSi1SfNZPRXDlIzTXIzAbVpOlkmDhCN_d4OTjomug5I7iZrnt8UZPm4cGEsJ9dNumKGNMzxdYoyAuh7JDpIY6GqjUcelsnAIyfkZ1uXjRaBwbF853tHJP8x6wUK_l0UBqW1eJ5l_CzSb8EskqIkA0tsdYHukbZj-NgDH3wwSj7L6j2DfyICUwbdCIGEMyNF0gPKB2qg9uAg03YJsj09pKUr4y5a-K_nALo5hZf4sRNqV8Jq-0u8n9vrE3reuSbmdZG0gxkevu-tl0gwpFawizdxg3Z2N0nh1AYa0nY3cLTgyQDvw031_Y24XZRWe8uPBFtoFcIKl8wCoW-tUFV_UHm-0XykPe9ZBMIrcXUQZAOcliKvc3-j743gmKHCEOPWh-EBAO66waVvgoscLBmdu6SVBW_SjXCVQ-gVl8tdJh4pScFPb7wHcxHJfoc1IpvKy-33TwJl7TYR48S7fEzBkkleTMqhzNfpcXwHKqV0HG-UQLCqT3ng6Q1ohz-bzvcXZl8qO8jIPpIitqCykeX45Ft5ctAwFSj7Kmws2IYi6D6MJCHei9S5ltOJvnW9zjUO0V0FMXiH0u8bqJD741OC9I-a1fbaJcvzo0xKz6F8wI58AFA_afvTb9RI1NRYhIZz4kN5x9Tx1Zjs4VnfeWfO7_kDph8FuLZUj3ftPEAqF6J2FFAVRxuy4ozYpON_dohTxJ_OsBxfOASK_G_r-lTAjb0kUHSKcYhcaBa7lV2Z_X2BFMEunXx1aOT0",
"id": "rs_0801a076ed6917a00169d7be6d60b88198adaded384f4d1ded",
"summary": [
{
"type": "summary_text",
"text": "**Patching troubleshooting notes**\n\nI need to focus on patching my skills with relevant notes in troubleshooting and configuration. Specifically, I should reference the actual key for agent reasoning effort, since the top-level OPENAI_REASONING_EFFORT is ignored in the CLI or gateway. I must also remember to include details for provider support. It seems like I should patch the relevant section under the Configuration or model/provider issues, possibly in relation to the slash command for reasoning efforts."
}
]
}
],
"tool_calls": [
{
"id": "call_7JaoB7FiGQxuJLfWd2M9AY5m",
"call_id": "call_7JaoB7FiGQxuJLfWd2M9AY5m",
"response_item_id": "fc_0801a076ed6917a00169d7be7241a88198a9222ecb531e7beb",
"type": "function",
"function": {
"name": "skill_manage",
"arguments": "{\"action\":\"patch\",\"name\":\"hermes-agent\",\"old_string\":\"### Providers\\n\\n18 providers supported. Set via `hermes model` or `hermes setup`.\\n\",\"new_string\":\"### Providers\\n\\n18 providers supported. Set via `hermes model` or `hermes setup`.\\n\\n### Reasoning effort gotcha\\n\\nHermes' persistent reasoning setting lives at `agent.reasoning_effort` in `~/.hermes/config.yaml`.\\n\\nUse one of these:\\n```bash\\nhermes config set agent.reasoning_effort xhigh\\n```\\nOr inside Hermes:\\n```text\\n/reasoning xhigh\\n```\\n\\nDo not rely on a top-level config key like `OPENAI_REASONING_EFFORT: xhigh` for Hermes CLI/gateway behavior. Hermes reads `agent.reasoning_effort`, not that top-level key.\\n\\nAlso, reasoning support is model/provider-specific:\\n- OpenAI Codex / GPT-5 Responses-style models: effort values like `low|medium|high|xhigh` can apply.\\n- OpenRouter models that expose effort controls: effort can apply.\\n- DeepSeek and some Kimi/Moonshot models: reasoning is selected by choosing a thinking/reasoner model variant, not by an effort dropdown.\\n- Some Mistral models only support a reasoning toggle, not `xhigh`.\\n- Web UI may clamp or clear unsupported effort values per model/provider.\\n\\nSo `agent.reasoning_effort: xhigh` is a good global default, but it will only be honored by models/providers that actually support effort-style reasoning.\\n\\n\"}"
}
}
]
},
{
"role": "tool",
"content": "{\"success\": true, \"message\": \"Patched SKILL.md in skill 'hermes-agent' (1 replacement).\"}",
"tool_call_id": "call_7JaoB7FiGQxuJLfWd2M9AY5m"
},
{
"role": "assistant",
"content": "Updated skill: hermes-agent\n\nSaved:\n- Hermes uses `agent.reasoning_effort`, not a top-level `OPENAI_REASONING_EFFORT`\n- Proper persistent commands:\n - `hermes config set agent.reasoning_effort xhigh`\n - `/reasoning xhigh`\n- Reasoning support is provider/model-specific, so `xhigh` won’t apply uniformly across DeepSeek/Kimi/Mistral/etc.",
"reasoning": null,
"finish_reason": "stop"
}
]
}