{"role": "session_meta", "tools": [{"type": "function", "function": {"name": "browser_back", "description": "Navigate back to the previous page in browser history. Requires browser_navigate to be called first.", "parameters": {"type": "object", "properties": {}}}}, {"type": "function", "function": {"name": "browser_click", "description": "Click on an element identified by its ref ID from the snapshot (e.g., '@e5'). The ref IDs are shown in square brackets in the snapshot output. Requires browser_navigate and browser_snapshot to be called first.", "parameters": {"type": "object", "properties": {"ref": {"type": "string", "description": "The element reference from the snapshot (e.g., '@e5', '@e12')"}}, "required": ["ref"]}}}, {"type": "function", "function": {"name": "browser_console", "description": "Get browser console output and JavaScript errors from the current page. Returns console.log/warn/error/info messages and uncaught JS exceptions. Use this to detect silent JavaScript errors, failed API calls, and application warnings. Requires browser_navigate to be called first. When 'expression' is provided, evaluates JavaScript in the page context and returns the result — use this for DOM inspection, reading page state, or extracting data programmatically.", "parameters": {"type": "object", "properties": {"clear": {"type": "boolean", "default": false, "description": "If true, clear the message buffers after reading"}, "expression": {"type": "string", "description": "JavaScript expression to evaluate in the page context. Runs in the browser like DevTools console — full access to DOM, window, document. Return values are serialized to JSON. Example: 'document.title' or 'document.querySelectorAll(\"a\").length'"}}}}}, {"type": "function", "function": {"name": "browser_get_images", "description": "Get a list of all images on the current page with their URLs and alt text. Useful for finding images to analyze with the vision tool. Requires browser_navigate to be called first.", "parameters": {"type": "object", "properties": {}}}}, {"type": "function", "function": {"name": "browser_navigate", "description": "Navigate to a URL in the browser. Initializes the session and loads the page. Must be called before other browser tools. For plain-text endpoints — URLs ending in .md, .txt, .json, .yaml, .yml, .csv, .xml, raw.githubusercontent.com, or any documented API endpoint — prefer curl via the terminal tool or web_extract; the browser stack is overkill and much slower for these. Use browser tools when you need to interact with a page (click, fill forms, dynamic content). Returns a compact page snapshot with interactive elements and ref IDs — no need to call browser_snapshot separately after navigating.", "parameters": {"type": "object", "properties": {"url": {"type": "string", "description": "The URL to navigate to (e.g., 'https://example.com')"}}, "required": ["url"]}}}, {"type": "function", "function": {"name": "browser_press", "description": "Press a keyboard key. Useful for submitting forms (Enter), navigating (Tab), or keyboard shortcuts. Requires browser_navigate to be called first.", "parameters": {"type": "object", "properties": {"key": {"type": "string", "description": "Key to press (e.g., 'Enter', 'Tab', 'Escape', 'ArrowDown')"}}, "required": ["key"]}}}, {"type": "function", "function": {"name": "browser_scroll", "description": "Scroll the page in a direction. Use this to reveal more content that may be below or above the current viewport. Requires browser_navigate to be called first.", "parameters": {"type": "object", "properties": {"direction": {"type": "string", "enum": ["up", "down"], "description": "Direction to scroll"}}, "required": ["direction"]}}}, {"type": "function", "function": {"name": "browser_snapshot", "description": "Get a text-based snapshot of the current page's accessibility tree. Returns interactive elements with ref IDs (like @e1, @e2) for browser_click and browser_type. full=false (default): compact view with interactive elements. full=true: complete page content. Snapshots over 8000 chars are truncated or LLM-summarized. Requires browser_navigate first. Note: browser_navigate already returns a compact snapshot — use this to refresh after interactions that change the page, or with full=true for complete content.", "parameters": {"type": "object", "properties": {"full": {"type": "boolean", "description": "If true, returns complete page content. If false (default), returns compact view with interactive elements only.", "default": false}}}}}, {"type": "function", "function": {"name": "browser_type", "description": "Type text into an input field identified by its ref ID. Clears the field first, then types the new text. Requires browser_navigate and browser_snapshot to be called first.", "parameters": {"type": "object", "properties": {"ref": {"type": "string", "description": "The element reference from the snapshot (e.g., '@e3')"}, "text": {"type": "string", "description": "The text to type into the field"}}, "required": ["ref", "text"]}}}, {"type": "function", "function": {"name": "browser_vision", "description": "Take a screenshot of the current page and analyze it with vision AI. Use this when you need to visually understand what's on the page - especially useful for CAPTCHAs, visual verification challenges, complex layouts, or when the text snapshot doesn't capture important visual information. Returns both the AI analysis and a screenshot_path that you can share with the user by including MEDIA: in your response. Requires browser_navigate to be called first.", "parameters": {"type": "object", "properties": {"question": {"type": "string", "description": "What you want to know about the page visually. Be specific about what you're looking for."}, "annotate": {"type": "boolean", "default": false, "description": "If true, overlay numbered [N] labels on interactive elements. Each [N] maps to ref @eN for subsequent browser commands. Useful for QA and spatial reasoning about page layout."}}, "required": ["question"]}}}, {"type": "function", "function": {"name": "clarify", "description": "Ask the user a question when you need clarification, feedback, or a decision before proceeding. Supports two modes:\n\n1. **Multiple choice** — provide up to 4 choices. The user picks one or types their own answer via a 5th 'Other' option.\n2. **Open-ended** — omit choices entirely. The user types a free-form response.\n\nUse this tool when:\n- The task is ambiguous and you need the user to choose an approach\n- You want post-task feedback ('How did that work out?')\n- You want to offer to save a skill or update memory\n- A decision has meaningful trade-offs the user should weigh in on\n\nDo NOT use this tool for simple yes/no confirmation of dangerous commands (the terminal tool handles that). Prefer making a reasonable default choice yourself when the decision is low-stakes.", "parameters": {"type": "object", "properties": {"question": {"type": "string", "description": "The question to present to the user."}, "choices": {"type": "array", "items": {"type": "string"}, "maxItems": 4, "description": "Up to 4 answer choices. Omit this parameter entirely to ask an open-ended question. When provided, the UI automatically appends an 'Other (type your answer)' option."}}, "required": ["question"]}}}, {"type": "function", "function": {"name": "cronjob", "description": "Manage scheduled cron jobs with a single compressed tool.\n\nUse action='create' to schedule a new job from a prompt or one or more skills.\nUse action='list' to inspect jobs.\nUse action='update', 'pause', 'resume', 'remove', or 'run' to manage an existing job.\n\nTo stop a job the user no longer wants: first action='list' to find the job_id, then action='remove' with that job_id. Never guess job IDs — always list first.\n\nJobs run in a fresh session with no current-chat context, so prompts must be self-contained.\nIf skills are provided on create, the future cron run loads those skills in order, then follows the prompt as the task instruction.\nOn update, passing skills=[] clears attached skills.\n\nNOTE: The agent's final response is auto-delivered to the target. Put the primary\nuser-facing content in the final response. Cron jobs run autonomously with no user\npresent — they cannot ask questions or request clarification.\n\nImportant safety rule: cron-run sessions should not recursively schedule more cron jobs.", "parameters": {"type": "object", "properties": {"action": {"type": "string", "description": "One of: create, list, update, pause, resume, remove, run"}, "job_id": {"type": "string", "description": "Required for update/pause/resume/remove/run"}, "prompt": {"type": "string", "description": "For create: the full self-contained prompt. If skills are also provided, this becomes the task instruction paired with those skills."}, "schedule": {"type": "string", "description": "For create/update: '30m', 'every 2h', '0 9 * * *', or ISO timestamp"}, "name": {"type": "string", "description": "Optional human-friendly name"}, "repeat": {"type": "integer", "description": "Optional repeat count. Omit for defaults (once for one-shot, forever for recurring)."}, "deliver": {"type": "string", "description": "Omit this parameter to auto-deliver back to the current chat and topic (recommended). Auto-detection preserves thread/topic context. Only set explicitly when the user asks to deliver somewhere OTHER than the current conversation. Values: 'origin' (same as omitting), 'local' (no delivery, save only), 'all' (fan out to every connected home channel), or platform:chat_id:thread_id for a specific destination. Combine with comma: 'origin,all' delivers to the origin plus every other connected channel. Examples: 'telegram:-1001234567890:17585', 'discord:#engineering', 'sms:+15551234567', 'all'. WARNING: 'platform:chat_id' without :thread_id loses topic targeting. 'all' resolves at fire time, so a job created before a channel was wired up will pick it up automatically once connected."}, "skills": {"type": "array", "items": {"type": "string"}, "description": "Optional ordered list of skill names to load before executing the cron prompt. On update, pass an empty array to clear attached skills."}, "model": {"type": "object", "description": "Optional per-job model override. If provider is omitted, the current main provider is pinned at creation time so the job stays stable.", "properties": {"provider": {"type": "string", "description": "Provider name (e.g. 'openrouter', 'anthropic', or 'custom:' for a provider defined in custom_providers config — always include the ':' suffix, never pass the bare 'custom'). Omit to use and pin the current provider."}, "model": {"type": "string", "description": "Model name (e.g. 'anthropic/claude-sonnet-4', 'claude-sonnet-4')"}}, "required": ["model"]}, "script": {"type": "string", "description": "Optional path to a script that runs each tick. In the default mode its stdout is injected into the agent's prompt as context (data-collection / change-detection pattern). With no_agent=True, the script IS the job and its stdout is delivered verbatim (classic watchdog pattern). Relative paths resolve under ~/.hermes/scripts/. ``.sh``/``.bash`` extensions run via bash, everything else via Python. On update, pass empty string to clear."}, "no_agent": {"type": "boolean", "default": false, "description": "Default: False (LLM-driven job — the agent runs the prompt each tick). Set True to skip the LLM entirely: the scheduler just runs ``script`` on schedule and delivers its stdout verbatim. No tokens, no agent loop, no model override honoured. \n\nREQUIREMENTS when True: ``script`` MUST be set (``prompt`` and ``skills`` are ignored). \n\nDELIVERY SEMANTICS when True: (a) non-empty stdout is sent verbatim as the message; (b) EMPTY stdout means SILENT — nothing is sent to the user and they won't see anything happened, so design your script to stay quiet when there's nothing to report (the watchdog pattern); (c) non-zero exit / timeout sends an error alert so a broken watchdog can't fail silently. \n\nWHEN TO USE True: recurring script-only pings where the script itself produces the exact message text (memory/disk/GPU watchdogs, threshold alerts, heartbeats, CI notifications, API pollers with a fixed output shape). WHEN TO USE False (default): anything that needs reasoning — summarize a feed, draft a daily briefing, pick interesting items, rephrase data for a human, follow conditional logic based on content."}, "context_from": {"type": "array", "items": {"type": "string"}, "description": "Optional job ID or list of job IDs whose most recent completed output is injected into the prompt as context before each run. Use this to chain cron jobs: job A collects data, job B processes it. Each entry must be a valid job ID (from cronjob action='list'). Note: injects the most recent completed output — does not wait for upstream jobs running in the same tick. On update, pass an empty array to clear."}, "enabled_toolsets": {"type": "array", "items": {"type": "string"}, "description": "Optional list of toolset names to restrict the job's agent to (e.g. [\"web\", \"terminal\", \"file\", \"delegation\"]). When set, only tools from these toolsets are loaded, significantly reducing input token overhead. When omitted, all default tools are loaded. Infer from the job's prompt — e.g. use \"web\" if it calls web_search, \"terminal\" if it runs scripts, \"file\" if it reads files, \"delegation\" if it calls delegate_task. On update, pass an empty array to clear."}, "workdir": {"type": "string", "description": "Optional absolute path to run the job from. When set, AGENTS.md / CLAUDE.md / .cursorrules from that directory are injected into the system prompt, and the terminal/file/code_exec tools use it as their working directory — useful for running a job inside a specific project repo. Must be an absolute path that exists. When unset (default), preserves the original behaviour: no project context files, tools use the scheduler's cwd. On update, pass an empty string to clear. Jobs with workdir run sequentially (not parallel) to keep per-job directories isolated."}}, "required": ["action"]}}}, {"type": "function", "function": {"name": "delegate_task", "description": "Spawn one or more subagents to work on tasks in isolated contexts. Each subagent gets its own conversation, terminal session, and toolset. Only the final summary is returned -- intermediate tool results never enter your context window.\n\nTWO MODES (one of 'goal' or 'tasks' is required):\n1. Single task: provide 'goal' (+ optional context, toolsets)\n2. Batch (parallel): provide 'tasks' array with up to 3 items concurrently for this user (configured via delegation.max_concurrent_children in config.yaml). All run in parallel and results are returned together. Nested delegation is OFF for this user (max_spawn_depth=1): every child is a leaf and cannot delegate further. Raise delegation.max_spawn_depth in config.yaml to enable nesting.\n\nWHEN TO USE delegate_task:\n- Reasoning-heavy subtasks (debugging, code review, research synthesis)\n- Tasks that would flood your context with intermediate data\n- Parallel independent workstreams (research A and B simultaneously)\n\nWHEN NOT TO USE (use these instead):\n- Mechanical multi-step work with no reasoning needed -> use execute_code\n- Single tool call -> just call the tool directly\n- Tasks needing user interaction -> subagents cannot use clarify\n- Durable long-running work that must outlive the current turn -> use cronjob (action='create') or terminal(background=True, notify_on_complete=True) instead. delegate_task runs SYNCHRONOUSLY inside the parent turn: if the parent is interrupted (user sends a new message, /stop, /new) the child is cancelled with status='interrupted' and its work is discarded. Children cannot continue in the background.\n\nIMPORTANT:\n- Subagents have NO memory of your conversation. Pass all relevant info (file paths, error messages, constraints) via the 'context' field.\n- If the user is writing in a non-English language, or asked for output in a specific language / tone / style, say so in 'context' (e.g. \"respond in Chinese\", \"return output in Japanese\"). Otherwise subagents default to English and their summaries will contaminate your final reply with the wrong language.\n- Subagent summaries are SELF-REPORTS, not verified facts. A subagent that claims \"uploaded successfully\" or \"file written\" may be wrong. For operations with external side-effects (HTTP POST/PUT, remote writes, file creation at shared paths, publishing), require the subagent to return a verifiable handle (URL, ID, absolute path, HTTP status) and verify it yourself — fetch the URL, stat the file, read back the content — before telling the user the operation succeeded.\n- Leaf subagents (role='leaf', the default) CANNOT call: delegate_task, clarify, memory, send_message, execute_code.\n- Orchestrator subagents (role='orchestrator') retain delegate_task so they can spawn their own workers, but still cannot use clarify, memory, send_message, or execute_code. Orchestrators are bounded by max_spawn_depth=1 for this user and can be disabled globally via delegation.orchestrator_enabled=false.\n- Each subagent gets its own terminal session (separate working directory and state).\n- Results are always returned as an array, one entry per task.", "parameters": {"type": "object", "properties": {"goal": {"type": "string", "description": "What the subagent should accomplish. Be specific and self-contained -- the subagent knows nothing about your conversation history."}, "context": {"type": "string", "description": "Background information the subagent needs: file paths, error messages, project structure, constraints. The more specific you are, the better the subagent performs."}, "toolsets": {"type": "array", "items": {"type": "string"}, "description": "Toolsets to enable for this subagent. Default: inherits your enabled toolsets. Available toolsets: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'vision', 'web', 'yuanbao'. Common patterns: ['terminal', 'file'] for code work, ['web'] for research, ['browser'] for web interaction, ['terminal', 'file', 'web'] for full-stack tasks."}, "tasks": {"type": "array", "items": {"type": "object", "properties": {"goal": {"type": "string", "description": "Task goal"}, "context": {"type": "string", "description": "Task-specific context"}, "toolsets": {"type": "array", "items": {"type": "string"}, "description": "Toolsets for this specific task. Available: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'vision', 'web', 'yuanbao'. Use 'web' for network access, 'terminal' for shell, 'browser' for web interaction."}, "acp_command": {"type": "string", "description": "Per-task ACP command override (e.g. 'copilot'). Overrides the top-level acp_command for this task only. Do NOT set unless the user explicitly told you an ACP CLI is installed."}, "acp_args": {"type": "array", "items": {"type": "string"}, "description": "Per-task ACP args override. Leave empty unless acp_command is set."}, "role": {"type": "string", "enum": ["leaf", "orchestrator"], "description": "Per-task role override. See top-level 'role' for semantics."}}, "required": ["goal"]}, "description": "Batch mode: tasks to run in parallel (up to 3 for this user, set via delegation.max_concurrent_children). Each gets its own subagent with isolated context and terminal session. When provided, top-level goal/context/toolsets are ignored."}, "role": {"type": "string", "enum": ["leaf", "orchestrator"], "description": "Role of the child agent. 'leaf' (default) = focused worker, cannot delegate further. 'orchestrator' = can use delegate_task to spawn its own workers. Nesting is OFF for this user (max_spawn_depth=1); 'orchestrator' is silently forced to 'leaf'. Raise delegation.max_spawn_depth in config.yaml to enable."}, "acp_command": {"type": "string", "description": "Override ACP command for child agents (e.g. 'copilot'). When set, children use ACP subprocess transport instead of inheriting the parent's transport. Requires an ACP-compatible CLI (currently GitHub Copilot CLI via 'copilot --acp --stdio'). See agent/copilot_acp_client.py for the implementation. IMPORTANT: Do NOT set this unless the user has explicitly told you a specific ACP-compatible CLI is installed and configured. Leave empty to use the parent's default transport (Hermes subagents)."}, "acp_args": {"type": "array", "items": {"type": "string"}, "description": "Arguments for the ACP command (default: ['--acp', '--stdio']). Only used when acp_command is set. Leave empty unless acp_command is explicitly provided."}}}}}, {"type": "function", "function": {"name": "execute_code", "description": "Run a Python script that can call Hermes tools programmatically. Use this when you need 3+ tool calls with processing logic between them, need to filter/reduce large tool outputs before they enter your context, need conditional branching (if X then Y else Z), or need to loop (fetch N pages, process N files, retry on failure).\n\nUse normal tool calls instead when: single tool call with no processing, you need to see the full result and apply complex reasoning, or the task requires interactive user input.\n\nAvailable via `from hermes_tools import ...`:\n\n read_file(path: str, offset: int = 1, limit: int = 500) -> dict\n Lines are 1-indexed. Returns {\"content\": \"...\", \"total_lines\": N}\n write_file(path: str, content: str) -> dict\n Always overwrites the entire file.\n search_files(pattern: str, target=\"content\", path=\".\", file_glob=None, limit=50) -> dict\n target: \"content\" (search inside files) or \"files\" (find files by name). Returns {\"matches\": [...]}\n patch(path: str, old_string: str, new_string: str, replace_all: bool = False) -> dict\n Replaces old_string with new_string in the file.\n terminal(command: str, timeout=None, workdir=None) -> dict\n Foreground only (no background/pty). Returns {\"output\": \"...\", \"exit_code\": N}\n\nLimits: 5-minute timeout, 50KB stdout cap, max 50 tool calls per script. terminal() is foreground-only (no background or pty).\n\nScripts run in the session's working directory with the active venv's python, so project deps (pandas, etc.) and relative paths work like in terminal().\n\nPrint your final result to stdout. Use Python stdlib (json, re, math, csv, datetime, collections, etc.) for processing between tool calls.\n\nAlso available (no import needed — built into hermes_tools):\n json_parse(text: str) — json.loads with strict=False; use for terminal() output with control chars\n shell_quote(s: str) — shlex.quote(); use when interpolating dynamic strings into shell commands\n retry(fn, max_attempts=3, delay=2) — retry with exponential backoff for transient failures", "parameters": {"type": "object", "properties": {"code": {"type": "string", "description": "Python code to execute. Import tools with `from hermes_tools import terminal, ...` and print your final result to stdout."}}, "required": ["code"]}}}, {"type": "function", "function": {"name": "image_generate", "description": "Generate high-quality images from text prompts. The underlying backend (FAL, OpenAI, etc.) and model are user-configured and not selectable by the agent. Returns either a URL or an absolute file path in the `image` field; display it with markdown ![description](url-or-path) and the gateway will deliver it.", "parameters": {"type": "object", "properties": {"prompt": {"type": "string", "description": "The text prompt describing the desired image. Be detailed and descriptive."}, "aspect_ratio": {"type": "string", "enum": ["landscape", "square", "portrait"], "description": "The aspect ratio of the generated image. 'landscape' is 16:9 wide, 'portrait' is 16:9 tall, 'square' is 1:1.", "default": "landscape"}}, "required": ["prompt"]}}}, {"type": "function", "function": {"name": "mcp_openclaw_attachments_fetch", "description": "List non-text attachments for a message in one OpenClaw conversation.", "parameters": {"$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": {"session_key": {"type": "string", "minLength": 1}, "message_id": {"type": "string", "minLength": 1}, "limit": {"type": "integer", "minimum": 1, "maximum": 200}}, "required": ["session_key", "message_id"]}}}, {"type": "function", "function": {"name": "mcp_openclaw_conversation_get", "description": "Get one OpenClaw conversation by session key.", "parameters": {"$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": {"session_key": {"type": "string", "minLength": 1}}, "required": ["session_key"]}}}, {"type": "function", "function": {"name": "mcp_openclaw_conversations_list", "description": "List OpenClaw channel-backed conversations available through session routes.", "parameters": {"$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": {"limit": {"type": "integer", "minimum": 1, "maximum": 500}, "search": {"type": "string"}, "channel": {"type": "string"}, "includeDerivedTitles": {"type": "boolean"}, "includeLastMessage": {"type": "boolean"}}}}}, {"type": "function", "function": {"name": "mcp_openclaw_events_poll", "description": "Poll queued OpenClaw conversation events since a cursor.", "parameters": {"$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": {"after_cursor": {"type": "integer", "minimum": 0, "maximum": 9007199254740991}, "session_key": {"type": "string"}, "limit": {"type": "integer", "minimum": 1, "maximum": 200}}}}}, {"type": "function", "function": {"name": "mcp_openclaw_events_wait", "description": "Wait for the next queued OpenClaw conversation event.", "parameters": {"$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": {"after_cursor": {"type": "integer", "minimum": 0, "maximum": 9007199254740991}, "session_key": {"type": "string"}, "timeout_ms": {"type": "integer", "minimum": 1, "maximum": 300000}}}}}, {"type": "function", "function": {"name": "mcp_openclaw_messages_read", "description": "Read recent messages for one OpenClaw conversation.", "parameters": {"$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": {"session_key": {"type": "string", "minLength": 1}, "limit": {"type": "integer", "minimum": 1, "maximum": 200}}, "required": ["session_key"]}}}, {"type": "function", "function": {"name": "mcp_openclaw_messages_send", "description": "Send a message back through the same OpenClaw conversation route.", "parameters": {"$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": {"session_key": {"type": "string", "minLength": 1}, "text": {"type": "string", "minLength": 1}}, "required": ["session_key", "text"]}}}, {"type": "function", "function": {"name": "mcp_openclaw_permissions_list_open", "description": "List open OpenClaw exec or plugin approval requests visible through the Gateway.", "parameters": {"$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": {}}}}, {"type": "function", "function": {"name": "mcp_openclaw_permissions_respond", "description": "Allow or deny one pending OpenClaw exec or plugin approval request.", "parameters": {"$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": {"kind": {"type": "string", "enum": ["exec", "plugin"]}, "id": {"type": "string", "minLength": 1}, "decision": {"type": "string", "enum": ["allow-once", "allow-always", "deny"]}}, "required": ["kind", "id", "decision"]}}}, {"type": "function", "function": {"name": "memory", "description": "Save durable information to persistent memory that survives across sessions. Memory is injected into future turns, so keep it compact and focused on facts that will still matter later.\n\nWHEN TO SAVE (do this proactively, don't wait to be asked):\n- User corrects you or says 'remember this' / 'don't do that again'\n- User shares a preference, habit, or personal detail (name, role, timezone, coding style)\n- You discover something about the environment (OS, installed tools, project structure)\n- You learn a convention, API quirk, or workflow specific to this user's setup\n- You identify a stable fact that will be useful again in future sessions\n\nPRIORITY: User preferences and corrections > environment facts > procedural knowledge. The most valuable memory prevents the user from having to repeat themselves.\n\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts.\nIf you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\n\nTWO TARGETS:\n- 'user': who the user is -- name, role, preferences, communication style, pet peeves\n- 'memory': your notes -- environment facts, project conventions, tool quirks, lessons learned\n\nACTIONS: add (new entry), replace (update existing -- old_text identifies it), remove (delete -- old_text identifies it).\n\nSKIP: trivial/obvious info, things easily re-discovered, raw data dumps, and temporary task state.", "parameters": {"type": "object", "properties": {"action": {"type": "string", "enum": ["add", "replace", "remove"], "description": "The action to perform."}, "target": {"type": "string", "enum": ["memory", "user"], "description": "Which memory store: 'memory' for personal notes, 'user' for user profile."}, "content": {"type": "string", "description": "The entry content. Required for 'add' and 'replace'."}, "old_text": {"type": "string", "description": "Short unique substring identifying the entry to replace or remove."}}, "required": ["action", "target"]}}}, {"type": "function", "function": {"name": "patch", "description": "Targeted find-and-replace edits in files. Use this instead of sed/awk in terminal. Uses fuzzy matching (9 strategies) so minor whitespace/indentation differences won't break it. Returns a unified diff. Auto-runs syntax checks after editing.\n\nREPLACE MODE (mode='replace', default): find a unique string and replace it. REQUIRED PARAMETERS: mode, path, old_string, new_string.\nPATCH MODE (mode='patch'): apply V4A multi-file patches for bulk changes. REQUIRED PARAMETERS: mode, patch.", "parameters": {"type": "object", "properties": {"mode": {"type": "string", "enum": ["replace", "patch"], "description": "Edit mode. 'replace' (default): requires path + old_string + new_string. 'patch': requires patch content only.", "default": "replace"}, "path": {"type": "string", "description": "REQUIRED when mode='replace'. File path to edit."}, "old_string": {"type": "string", "description": "REQUIRED when mode='replace'. Exact text to find and replace. Must be unique in the file unless replace_all=true. Include surrounding context lines to ensure uniqueness."}, "new_string": {"type": "string", "description": "REQUIRED when mode='replace'. Replacement text. Pass empty string '' to delete the matched text."}, "replace_all": {"type": "boolean", "description": "Replace all occurrences instead of requiring a unique match (default: false)", "default": false}, "patch": {"type": "string", "description": "REQUIRED when mode='patch'. V4A format patch content. Format:\n*** Begin Patch\n*** Update File: path/to/file\n@@ context hint @@\n context line\n-removed line\n+added line\n*** End Patch"}}, "required": ["mode"]}}}, {"type": "function", "function": {"name": "process", "description": "Manage background processes started with terminal(background=true). Actions: 'list' (show all), 'poll' (check status + new output), 'log' (full output with pagination), 'wait' (block until done or timeout), 'kill' (terminate), 'write' (send raw stdin data without newline), 'submit' (send data + Enter, for answering prompts), 'close' (close stdin/send EOF).", "parameters": {"type": "object", "properties": {"action": {"type": "string", "enum": ["list", "poll", "log", "wait", "kill", "write", "submit", "close"], "description": "Action to perform on background processes"}, "session_id": {"type": "string", "description": "Process session ID (from terminal background output). Required for all actions except 'list'."}, "data": {"type": "string", "description": "Text to send to process stdin (for 'write' and 'submit' actions)"}, "timeout": {"type": "integer", "description": "Max seconds to block for 'wait' action. Returns partial output on timeout.", "minimum": 1}, "offset": {"type": "integer", "description": "Line offset for 'log' action (default: last 200 lines)"}, "limit": {"type": "integer", "description": "Max lines to return for 'log' action", "minimum": 1}}, "required": ["action"]}}}, {"type": "function", "function": {"name": "read_file", "description": "Read a text file with line numbers and pagination. Use this instead of cat/head/tail in terminal. Output format: 'LINE_NUM|CONTENT'. Suggests similar filenames if not found. Use offset and limit for large files. Reads exceeding ~100K characters are rejected; use offset and limit to read specific sections of large files. NOTE: Cannot read images or binary files — use vision_analyze for images.", "parameters": {"type": "object", "properties": {"path": {"type": "string", "description": "Path to the file to read (absolute, relative, or ~/path)"}, "offset": {"type": "integer", "description": "Line number to start reading from (1-indexed, default: 1)", "default": 1, "minimum": 1}, "limit": {"type": "integer", "description": "Maximum number of lines to read (default: 500, max: 2000)", "default": 500, "maximum": 2000}}, "required": ["path"]}}}, {"type": "function", "function": {"name": "search_files", "description": "Search file contents or find files by name. Use this instead of grep/rg/find/ls in terminal. Ripgrep-backed, faster than shell equivalents.\n\nContent search (target='content'): Regex search inside files. Output modes: full matches with line numbers, file paths only, or match counts.\n\nFile search (target='files'): Find files by glob pattern (e.g., '*.py', '*config*'). Also use this instead of ls — results sorted by modification time.", "parameters": {"type": "object", "properties": {"pattern": {"type": "string", "description": "Regex pattern for content search, or glob pattern (e.g., '*.py') for file search"}, "target": {"type": "string", "enum": ["content", "files"], "description": "'content' searches inside file contents, 'files' searches for files by name", "default": "content"}, "path": {"type": "string", "description": "Directory or file to search in (default: current working directory)", "default": "."}, "file_glob": {"type": "string", "description": "Filter files by pattern in grep mode (e.g., '*.py' to only search Python files)"}, "limit": {"type": "integer", "description": "Maximum number of results to return (default: 50)", "default": 50}, "offset": {"type": "integer", "description": "Skip first N results for pagination (default: 0)", "default": 0}, "output_mode": {"type": "string", "enum": ["content", "files_only", "count"], "description": "Output format for grep mode: 'content' shows matching lines with line numbers, 'files_only' lists file paths, 'count' shows match counts per file", "default": "content"}, "context": {"type": "integer", "description": "Number of context lines before and after each match (grep mode only)", "default": 0}}, "required": ["pattern"]}}}, {"type": "function", "function": {"name": "send_message", "description": "Send a message to a connected messaging platform, or list available targets.\n\nIMPORTANT: When the user asks to send to a specific channel or person (not just a bare platform name), call send_message(action='list') FIRST to see available targets, then send to the correct one.\nIf the user just says a platform name like 'send to telegram', send directly to the home channel without listing first.", "parameters": {"type": "object", "properties": {"action": {"type": "string", "enum": ["send", "list"], "description": "Action to perform. 'send' (default) sends a message. 'list' returns all available channels/contacts across connected platforms."}, "target": {"type": "string", "description": "Delivery target. Format: 'platform' (uses home channel), 'platform:#channel-name', 'platform:chat_id', or 'platform:chat_id:thread_id' for Telegram topics and Discord threads. Examples: 'telegram', 'telegram:-1001234567890:17585', 'discord:999888777:555444333', 'discord:#bot-home', 'slack:#engineering', 'signal:+155****4567', 'matrix:!roomid:server.org', 'matrix:@user:server.org', 'yuanbao:direct:' (DM), 'yuanbao:group:' (group chat)"}, "message": {"type": "string", "description": "The message text to send. To send an image or file, include MEDIA: (e.g. 'MEDIA:/tmp/hermes/cache/img_xxx.jpg') in the message — the platform will deliver it as a native media attachment."}}}}}, {"type": "function", "function": {"name": "session_search", "description": "Search your long-term memory of past conversations, or browse recent sessions. This is your recall -- every past session is searchable, and this tool summarizes what happened.\n\nTWO MODES:\n1. Recent sessions (no query): Call with no arguments to see what was worked on recently. Returns titles, previews, and timestamps. Zero LLM cost, instant. Start here when the user asks what were we working on or what did we do recently.\n2. Keyword search (with query): Search for specific topics across all past sessions. Returns LLM-generated summaries of matching sessions.\n\nUSE THIS PROACTIVELY when:\n- The user says 'we did this before', 'remember when', 'last time', 'as I mentioned'\n- The user asks about a topic you worked on before but don't have in current context\n- The user references a project, person, or concept that seems familiar but isn't in memory\n- You want to check if you've solved a similar problem before\n- The user asks 'what did we do about X?' or 'how did we fix Y?'\n\nDon't hesitate to search when it is actually cross-session -- it's fast and cheap. Better to search and confirm than to guess or ask the user to repeat themselves.\n\nSearch syntax: keywords joined with OR for broad recall (elevenlabs OR baseten OR funding), phrases for exact match (\"docker networking\"), boolean (python NOT java), prefix (deploy*). IMPORTANT: Use OR between keywords for best results — FTS5 defaults to AND which misses sessions that only mention some terms. If a broad OR query returns nothing, try individual keyword searches in parallel. Returns summaries of the top matching sessions.", "parameters": {"type": "object", "properties": {"query": {"type": "string", "description": "Search query — keywords, phrases, or boolean expressions to find in past sessions. Omit this parameter entirely to browse recent sessions instead (returns titles, previews, timestamps with no LLM cost)."}, "role_filter": {"type": "string", "description": "Optional: only search messages from specific roles (comma-separated). E.g. 'user,assistant' to skip tool outputs."}, "limit": {"type": "integer", "description": "Max sessions to summarize (default: 3, max: 5).", "default": 3}}}}}, {"type": "function", "function": {"name": "skill_manage", "description": "Manage skills (create, update, delete). Skills are your procedural memory — reusable approaches for recurring task types. New skills go to ~/.hermes/skills/; existing skills can be modified wherever they live.\n\nActions: create (full SKILL.md + optional category), patch (old_string/new_string — preferred for fixes), edit (full SKILL.md rewrite — major overhauls only), delete, write_file, remove_file.\n\nOn delete, pass `absorbed_into=` when you're merging this skill's content into another one, or `absorbed_into=\"\"` when you're pruning it with no forwarding target. This lets the curator tell consolidation from pruning without guessing, so downstream consumers (cron jobs that reference the old skill name, etc.) get updated correctly. The target you name in `absorbed_into` must already exist — create/patch the umbrella first, then delete.\n\nCreate when: complex task succeeded (5+ calls), errors overcome, user-corrected approach worked, non-trivial workflow discovered, or user asks you to remember a procedure.\nUpdate when: instructions stale/wrong, OS-specific failures, missing steps or pitfalls found during use. If you used a skill and hit issues not covered by it, patch it immediately.\n\nAfter difficult/iterative tasks, offer to save as a skill. Skip for simple one-offs. Confirm with user before creating/deleting.\n\nGood skills: trigger conditions, numbered steps with exact commands, pitfalls section, verification steps. Use skill_view() to see format examples.\n\nPinned skills are protected from deletion only — skill_manage(action='delete') will refuse with a message pointing the user to `hermes curator unpin `. Patches and edits go through on pinned skills so you can still improve them as pitfalls come up; pin only guards against irrecoverable loss.", "parameters": {"type": "object", "properties": {"action": {"type": "string", "enum": ["create", "patch", "edit", "delete", "write_file", "remove_file"], "description": "The action to perform."}, "name": {"type": "string", "description": "Skill name (lowercase, hyphens/underscores, max 64 chars). Must match an existing skill for patch/edit/delete/write_file/remove_file."}, "content": {"type": "string", "description": "Full SKILL.md content (YAML frontmatter + markdown body). Required for 'create' and 'edit'. For 'edit', read the skill first with skill_view() and provide the complete updated text."}, "old_string": {"type": "string", "description": "Text to find in the file (required for 'patch'). Must be unique unless replace_all=true. Include enough surrounding context to ensure uniqueness."}, "new_string": {"type": "string", "description": "Replacement text (required for 'patch'). Can be empty string to delete the matched text."}, "replace_all": {"type": "boolean", "description": "For 'patch': replace all occurrences instead of requiring a unique match (default: false)."}, "category": {"type": "string", "description": "Optional category/domain for organizing the skill (e.g., 'devops', 'data-science', 'mlops'). Creates a subdirectory grouping. Only used with 'create'."}, "file_path": {"type": "string", "description": "Path to a supporting file within the skill directory. For 'write_file'/'remove_file': required, must be under references/, templates/, scripts/, or assets/. For 'patch': optional, defaults to SKILL.md if omitted."}, "file_content": {"type": "string", "description": "Content for the file. Required for 'write_file'."}, "absorbed_into": {"type": "string", "description": "For 'delete' only — declares intent so the curator can tell consolidation from pruning without guessing. Pass the umbrella skill name when this skill's content was merged into another (the target must already exist). Pass an empty string when the skill is truly stale and being pruned with no forwarding target. Omitting the arg on delete is supported for backward compatibility but downstream tooling (e.g. cron-job skill reference rewriting) will have to guess at intent."}}, "required": ["action", "name"]}}}, {"type": "function", "function": {"name": "skill_view", "description": "Skills allow for loading information about specific tasks and workflows, as well as scripts and templates. Load a skill's full content or access its linked files (references, templates, scripts). First call returns SKILL.md content plus a 'linked_files' dict showing available references/templates/scripts. To access those, call again with file_path parameter.", "parameters": {"type": "object", "properties": {"name": {"type": "string", "description": "The skill name (use skills_list to see available skills). For plugin-provided skills, use the qualified form 'plugin:skill' (e.g. 'superpowers:writing-plans')."}, "file_path": {"type": "string", "description": "OPTIONAL: Path to a linked file within the skill (e.g., 'references/api.md', 'templates/config.yaml', 'scripts/validate.py'). Omit to get the main SKILL.md content."}}, "required": ["name"]}}}, {"type": "function", "function": {"name": "skills_list", "description": "List available skills (name + description). Use skill_view(name) to load full content.", "parameters": {"type": "object", "properties": {"category": {"type": "string", "description": "Optional category filter to narrow results"}}}}}, {"type": "function", "function": {"name": "terminal", "description": "Execute shell commands on a Linux environment. Filesystem usually persists between calls.\n\nDo NOT use cat/head/tail to read files — use read_file instead.\nDo NOT use grep/rg/find to search — use search_files instead.\nDo NOT use ls to list directories — use search_files(target='files') instead.\nDo NOT use sed/awk to edit files — use patch instead.\nDo NOT use echo/cat heredoc to create files — use write_file instead.\nReserve terminal for: builds, installs, git, processes, scripts, network, package managers, and anything that needs a shell.\n\nForeground (default): Commands return INSTANTLY when done, even if the timeout is high. Set timeout=300 for long builds/scripts — you'll still get the result in seconds if it's fast. Prefer foreground for short commands.\nBackground: Set background=true to get a session_id. Two patterns:\n (1) Long-lived processes that never exit (servers, watchers).\n (2) Long-running tasks with notify_on_complete=true — you can keep working on other things and the system auto-notifies you when the task finishes. Great for test suites, builds, deployments, or anything that takes more than a minute.\nFor servers/watchers, do NOT use shell-level background wrappers (nohup/disown/setsid/trailing '&') in foreground mode. Use background=true so Hermes can track lifecycle and output.\nAfter starting a server, verify readiness with a health check or log signal, then run tests in a separate terminal() call. Avoid blind sleep loops.\nUse process(action=\"poll\") for progress checks, process(action=\"wait\") to block until done.\nWorking directory: Use 'workdir' for per-command cwd.\nPTY mode: Set pty=true for interactive CLI tools (Codex, Claude Code, Python REPL).\n\nDo NOT use vim/nano/interactive tools without pty=true — they hang without a pseudo-terminal. Pipe git output to cat if it might page.\n", "parameters": {"type": "object", "properties": {"command": {"type": "string", "description": "The command to execute on the VM"}, "background": {"type": "boolean", "description": "Run the command in the background. Two patterns: (1) Long-lived processes that never exit (servers, watchers). (2) Long-running tasks paired with notify_on_complete=true — you can keep working and get notified when the task finishes. For short commands, prefer foreground with a generous timeout instead.", "default": false}, "timeout": {"type": "integer", "description": "Max seconds to wait (default: 180, foreground max: 600). Returns INSTANTLY when command finishes — set high for long tasks, you won't wait unnecessarily. Foreground timeout above 600s is rejected; use background=true for longer commands.", "minimum": 1}, "workdir": {"type": "string", "description": "Working directory for this command (absolute path). Defaults to the session working directory."}, "pty": {"type": "boolean", "description": "Run in pseudo-terminal (PTY) mode for interactive CLI tools like Codex, Claude Code, or Python REPL. Only works with local and SSH backends. Default: false.", "default": false}, "notify_on_complete": {"type": "boolean", "description": "When true (and background=true), you'll be automatically notified exactly once when the process finishes. **This is the right choice for almost every long-running task** — tests, builds, deployments, multi-item batch jobs, anything that takes over a minute and has a defined end. Use this and keep working on other things; the system notifies you on exit. MUTUALLY EXCLUSIVE with watch_patterns — when both are set, watch_patterns is dropped.", "default": false}, "watch_patterns": {"type": "array", "items": {"type": "string"}, "description": "Strings to watch for in background process output. HARD RATE LIMIT: at most 1 notification per 15 seconds per process — matches arriving inside the cooldown are dropped. After 3 consecutive 15-second windows with dropped matches, watch_patterns is automatically disabled for that process and promoted to notify_on_complete behavior (one notification on exit, no more mid-process spam). USE ONLY for truly rare, one-shot mid-process signals on LONG-LIVED processes that will never exit on their own — e.g. ['Application startup complete'] on a server so you know when to hit its endpoint, or ['migration done'] on a daemon. DO NOT use for: (1) end-of-run markers like 'DONE'/'PASS' — use notify_on_complete instead; (2) error patterns like 'ERROR'/'Traceback' in loops or multi-item batch jobs — they fire on every iteration and you'll hit the strike limit fast; (3) anything you'd ever combine with notify_on_complete. When in doubt, choose notify_on_complete. MUTUALLY EXCLUSIVE with notify_on_complete — set one, not both."}}, "required": ["command"]}}}, {"type": "function", "function": {"name": "text_to_speech", "description": "Convert text to speech audio. Returns a MEDIA: path that the platform delivers as native audio. Compatible providers render as a voice bubble on Telegram; otherwise audio is sent as a regular attachment. In CLI mode, saves to ~/voice-memos/. Voice and provider are user-configured (built-in providers like edge/openai or custom command providers under tts.providers.), not model-selected.", "parameters": {"type": "object", "properties": {"text": {"type": "string", "description": "The text to convert to speech. Provider-specific character caps apply and are enforced automatically (OpenAI 4096, xAI 15000, MiniMax 10000, ElevenLabs 5k-40k depending on model); over-long input is truncated."}, "output_path": {"type": "string", "description": "Optional custom file path to save the audio. Defaults to ~/.hermes/audio_cache/.mp3"}}, "required": ["text"]}}}, {"type": "function", "function": {"name": "todo", "description": "Manage your task list for the current session. Use for complex tasks with 3+ steps or when the user provides multiple tasks. Call with no parameters to read the current list.\n\nWriting:\n- Provide 'todos' array to create/update items\n- merge=false (default): replace the entire list with a fresh plan\n- merge=true: update existing items by id, add any new ones\n\nEach item: {id: string, content: string, status: pending|in_progress|completed|cancelled}\nList order is priority. Only ONE item in_progress at a time.\nMark items completed immediately when done. If something fails, cancel it and add a revised item.\n\nAlways returns the full current list.", "parameters": {"type": "object", "properties": {"todos": {"type": "array", "description": "Task items to write. Omit to read current list.", "items": {"type": "object", "properties": {"id": {"type": "string", "description": "Unique item identifier"}, "content": {"type": "string", "description": "Task description"}, "status": {"type": "string", "enum": ["pending", "in_progress", "completed", "cancelled"], "description": "Current status"}}, "required": ["id", "content", "status"]}}, "merge": {"type": "boolean", "description": "true: update existing items by id, add new ones. false (default): replace the entire list.", "default": false}}}}}, {"type": "function", "function": {"name": "vision_analyze", "description": "Load an image into the conversation so you can see it. Accepts a URL, local file path, or data URL. When your active model has native vision, the image is attached to your context directly and you read the pixels yourself on the next turn — call this any time the user references an image (filepath in their message, URL in tool output, screenshot from the browser, etc.). For non-vision models, falls back to an auxiliary vision model that returns a text description.", "parameters": {"type": "object", "properties": {"image_url": {"type": "string", "description": "Image URL (http/https), local file path, or data: URL to load."}, "question": {"type": "string", "description": "Your specific question or request about the image. Optional context the model uses on the next turn after seeing the image."}}, "required": ["image_url", "question"]}}}, {"type": "function", "function": {"name": "write_file", "description": "Write content to a file, completely replacing existing content. Use this instead of echo/cat heredoc in terminal. Creates parent directories automatically. OVERWRITES the entire file — use 'patch' for targeted edits. Auto-runs syntax checks on .py/.json/.yaml/.toml and other linted languages; only NEW errors introduced by this write are surfaced (pre-existing errors are filtered out).", "parameters": {"type": "object", "properties": {"path": {"type": "string", "description": "Path to the file to write (will be created if it doesn't exist, overwritten if it does)"}, "content": {"type": "string", "description": "Complete content to write to the file"}}, "required": ["path", "content"]}}}], "model": "gpt-5.5", "platform": "telegram", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "user", "content": "Hallo Jarvis. Eine frage: was kann ich von melner seite her tun um den tokenverbrauch zu reduzieren? Ab und zu die session neu starten? Oder brauche. Wor verschiedene kanäle? Oder sollen wir openclaw wieder ativieren, da dieser als separster worker tokenoptimierte handelt und nicht den ganzen nontext lädt? Recherchiere im internet. Hast du die übersicht pber jnsere token statistik? Sind wir bereits sparsamer? Wird weniger kontext geladen, wenn das thema dies nicht benötigt?", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "assistant", "content": "", "reasoning": "**Researching Hermes configuration**\n\nI see the user is asking about Hermes configuration, specifically about the hermes-agent and possibly the token optimizer too. I need to load the hermes-agent and check on the token-optimizer's relevance. It's clear I'll need to do some internet research, maybe inspect local stats as well. I don’t have a specific web search tool, so I might need to use a browser or terminal curl to gather current facts. Focusing on skills first seems to be the best approach.", "finish_reason": "tool_calls", "reasoning_content": "**Researching Hermes configuration**\n\nI see the user is asking about Hermes configuration, specifically about the hermes-agent and possibly the token optimizer too. I need to load the hermes-agent and check on the token-optimizer's relevance. It's clear I'll need to do some internet research, maybe inspect local stats as well. I don’t have a specific web search tool, so I might need to use a browser or terminal curl to gather current facts. Focusing on skills first seems to be the best approach.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqBXzxoYLQqi9cy4IAC5CSjf5CB1lC503ksLt6kamKmsEqrMYJyeTE8s68NZLEOR_0RHhC55LNboA_i1bzltg3wWKjFENvlLAisb1yR1lSBcaPFec6TzH1A6cFC657ZryPhkz4XzM6jS6it5Q66zOuPjn2GQaGObitrZ_J5s3lTVoQuC4PkhPH2p5KQiRQ5xKtPZMn5Ztd8oBvw6bTQXUVGt7JXefjTauLtEc4VWvR7CDDZaIkSDz4AtOHNywI3YAvPDYa-5J__UMHS0GT88u18JgUG7IofB_gsISakvXwUO_P6bk0I3gtNmNqtP_tD6bc-ew_OhVLBfqb7yr9X3PHNNlRDzYQqfuzdydly5J10ZhTv7P1mk7avvVTO4Ge_HL5S9rC6e7744mCyt9W3j8pf3AS27l78WEaEpZMyV2JjBr5FiEhq5KynBKECscuSs_5NVe07jMd0qC8AxPFNBp0Eea0E50vX--pTfjUF2tOqkpwv8MPV9FNPaA5cpKKg9uSuyY1bHv3iMCDtjwE--4OVwkiN9Mx5t4jRx4AF9fxEiPSVLBYDlW9am-1Lehb8wVKWz4ZM9V7ppok1de0i012mHpkvDCzmxYZZpM52RrAiHwXvGI0JHjNJ8umOSNaIRRsv4VIcTA2WgioTspm4UnFXvKyXSDqorz83flMgFMHFl9SgvHWW84uUlFeZtLHUl49bw8YcMVSD5tebom7wjErkHYCqCGpc4rPIzwjMqjoFrbecv2k51QYiQKLF-QgHhM9jXNOofcOPvlhGXgAlKRnyc_n--lCZinajToSHlNj6Vn6gafHMXjOommpfPqP8i4R4P3_0hFPADAOujNFAszI3T0nZ2SCenTygoiodAx6gK5SGJKzV_ZuZw_JC7jNmxKOU2ZNRFzy2vExtlEZxPmPhl8obQ_7F0lJBLf_nvpfjfz20iQcJyXaW7acxS20FykaqzIRiOU9tXKa7XIAgHiS5LPpXLTyLIl9hdqmiwD57rU0r52sdK6tXLfCaowENrT_fVnvr1BXD0uhXq7GBbDOxH3T5t_NNzvoulg4cNhhaSO5FDkYniAPLpRr7_eKDtZgUdgxhZ2OxXzXpmbGw55kjxyc6YxY78Xm30giUvWZYdmfpPd4Js-_hcqh0zoQdG_DNBqTtO0el8dy5HieDZOBboGz3KqS9hMHR1-Kt94EztcOA0PVFm2ZSfv0Oj1iQxLAX1xGXpNeG7m0CQqV6HTcGNs76ORhR0qBCERAfajl8am9NDvnC1tPAlOszQe_aVtIPS6iILYFC69LoOC8zFZeojMiWseIymezmSthaMcBYT7gdyLichaU5iM6WSNOhbnp6aGR", "id": "rs_0f45421ffff9affb016a057ced004081919d2d4087d6905e2c", "summary": [{"type": "summary_text", "text": "**Researching Hermes configuration**\n\nI see the user is asking about Hermes configuration, specifically about the hermes-agent and possibly the token optimizer too. I need to load the hermes-agent and check on the token-optimizer's relevance. It's clear I'll need to do some internet research, maybe inspect local stats as well. I don’t have a specific web search tool, so I might need to use a browser or terminal curl to gather current facts. Focusing on skills first seems to be the best approach."}]}], "tool_calls": [{"id": "call_rUr2niL84iH4ngpBgm5dFIVs", "call_id": "call_rUr2niL84iH4ngpBgm5dFIVs", "response_item_id": "fc_0f45421ffff9affb016a057cf171208191ae65f8da9654dea4", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"hermes-agent\"}"}}, {"id": "call_jp5AUKauIglhhxo1oHx4iAfM", "call_id": "call_jp5AUKauIglhhxo1oHx4iAfM", "response_item_id": "fc_0f45421ffff9affb016a057cf171308191be7a34590c8da5ac", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"token-optimizer\"}"}}], "timestamp": "2026-05-14T09:45:30.357460"} {"role": "tool", "name": "skill_view", "content": "{\"success\": true, \"name\": \"hermes-agent\", \"description\": \"Configure, extend, or contribute to Hermes Agent.\", \"tags\": [\"hermes\", \"setup\", \"configuration\", \"multi-agent\", \"spawning\", \"cli\", \"gateway\", \"development\"], \"related_skills\": [\"claude-code\", \"codex\", \"opencode\"], \"content\": \"---\\nname: hermes-agent\\ndescription: \\\"Configure, extend, or contribute to Hermes Agent.\\\"\\nversion: 2.1.0\\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 10+ 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 (ID can be a hub identifier OR a direct https://…/SKILL.md URL; pass --name to override when frontmatter has no name)\\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, BlueBubbles (iMessage), Weixin (WeChat), API Server, Webhooks. Open WebUI connects via the API Server adapter.\\n\\nPlatform docs: https://hermes-agent.nousresearch.com/docs/user-guide/messaging/\\n\\n**Telegram setup:** See `references/telegram-gateway-setup.md` for the complete step-by-step configuration workflow.\\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 (requires honcho plugin)\\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. New commands land fairly\\noften; if something below looks stale, run `/help` in-session for the\\nauthoritative list or see the [live slash commands reference](https://hermes-agent.nousresearch.com/docs/reference/slash-commands).\\nThe registry of record is `hermes_cli/commands.py` — every consumer\\n(autocomplete, Telegram menu, Slack mapping, `/help`) derives from it.\\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/snapshot [sub] Create or restore state snapshots of Hermes config/state (CLI)\\n/background Run prompt in background\\n/queue Queue for next turn\\n/steer Inject a message after the next tool call without interrupting\\n/agents (/tasks) Show active agents and running tasks\\n/resume [name] Resume a named session\\n/goal [text|sub] Set a standing goal Hermes works on across turns until achieved\\n (subcommands: status, pause, resume, clear)\\n/redraw Force a full UI repaint (CLI)\\n```\\n\\n### Configuration\\n```\\n/config Show config (CLI)\\n/model [name] Show or change model\\n/personality [name] Set personality\\n/reasoning [level] Set reasoning (none|minimal|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/busy [sub] Control what Enter does while Hermes is working (CLI)\\n (subcommands: queue, steer, interrupt, status)\\n/indicator [style] Pick the TUI busy-indicator style (CLI)\\n (styles: kaomoji, emoji, unicode, ascii)\\n/footer [on|off] Toggle gateway runtime-metadata footer on final replies\\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/reload-skills Re-scan ~/.hermes/skills/ for added/removed skills\\n/reload Reload .env variables into the running session (CLI)\\n/reload-mcp Reload MCP servers\\n/cron Manage cron jobs (CLI)\\n/curator [sub] Background skill maintenance (status, run, pin, archive, …)\\n/kanban [sub] Multi-profile collaboration board (tasks, links, comments)\\n/plugins List plugins (CLI)\\n```\\n\\n### Gateway\\n```\\n/approve Approve a pending command (gateway)\\n/deny Deny a pending command (gateway)\\n/restart Restart gateway (gateway)\\n/sethome Set current chat as home channel (gateway)\\n/update Update Hermes to latest (gateway)\\n/topic [sub] Enable or inspect Telegram DM topic sessions (gateway)\\n/platforms (/gateway) Show platform connection status (gateway)\\n```\\n\\n### Utility\\n```\\n/branch (/fork) Branch the current session\\n/fast Toggle priority/fast processing\\n/browser Open CDP browser connection\\n/history Show conversation history (CLI)\\n/save Save conversation to file (CLI)\\n/copy [N] Copy the last assistant response to clipboard (CLI)\\n/paste Attach clipboard image (CLI)\\n/image Attach local image file (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/gquota Show Google Gemini Code Assist quota usage (CLI)\\n/status Session info (gateway)\\n/profile Active profile info\\n/debug Upload debug report (system info + logs) and get shareable links\\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_HOME/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/mistral) |\\n| `tts` | `provider` (edge/elevenlabs/openai/minimax/mistral/neutts) |\\n| `memory` | `memory_enabled`, `user_profile_enabled`, `provider` |\\n| `security` | `tirith_enabled`, `website_blocklist` |\\n| `delegation` | `model`, `provider`, `base_url`, `api_key`, `max_iterations` (50), `reasoning_effort` |\\n| `checkpoints` | `enabled`, `max_snapshots` (50) |\\n\\nFull config reference: https://hermes-agent.nousresearch.com/docs/user-guide/configuration\\n\\n### Providers\\n\\n20+ 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 auth` |\\n| OpenAI Codex | OAuth | `hermes auth` |\\n| GitHub Copilot | Token | `COPILOT_GITHUB_TOKEN` |\\n| Google Gemini | API key | `GOOGLE_API_KEY` or `GEMINI_API_KEY` |\\n| DeepSeek | API key | `DEEPSEEK_API_KEY` |\\n| xAI / Grok | API key | `XAI_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| MiniMax CN | API key | `MINIMAX_CN_API_KEY` |\\n| Kimi / Moonshot | API key | `KIMI_API_KEY` |\\n| Alibaba / DashScope | API key | `DASHSCOPE_API_KEY` |\\n| Xiaomi MiMo | API key | `XIAOMI_API_KEY` |\\n| Kilo Code | API key | `KILOCODE_API_KEY` |\\n| AI Gateway (Vercel) | API key | `AI_GATEWAY_API_KEY` |\\n| OpenCode Zen | API key | `OPENCODE_ZEN_API_KEY` |\\n| OpenCode Go | API key | `OPENCODE_GO_API_KEY` |\\n| Qwen OAuth | OAuth | `hermes login --provider qwen-oauth` |\\n| Custom endpoint | Config | `model.base_url` + `model.api_key` in config.yaml |\\n| GitHub Copilot ACP | External | `COPILOT_CLI_PATH` or Copilot CLI |\\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| `search` | Web search only (subset of `web`) |\\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| `video` | Video analysis and 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| `messaging` | Cross-platform message sending |\\n| `todo` | In-session task planning and tracking |\\n| `kanban` | Multi-agent work-queue tools (gated to workers) |\\n| `debugging` | Extra introspection/debug tools (off by default) |\\n| `safe` | Minimal, low-risk toolset for locked-down sessions |\\n| `spotify` | Spotify playback and playlist control |\\n| `homeassistant` | Smart home control (off by default) |\\n| `discord` | Discord integration tools |\\n| `discord_admin` | Discord admin/moderation tools |\\n| `feishu_doc` | Feishu (Lark) document tools |\\n| `feishu_drive` | Feishu (Lark) drive tools |\\n| `yuanbao` | Yuanbao integration tools |\\n| `rl` | Reinforcement learning tools (off by default) |\\n| `moa` | Mixture of Agents (off by default) |\\n\\nFull enumeration lives in `toolsets.py` as the `TOOLSETS` dict; `_HERMES_CORE_TOOLS` is the default bundle most platforms inherit from.\\n\\nTool changes take effect on `/reset` (new session). They do NOT apply mid-conversation to preserve prompt caching.\\n\\n---\\n\\n## Security & Privacy Toggles\\n\\nCommon \\\"why is Hermes doing X to my output / tool calls / commands?\\\" toggles — and the exact commands to change them. Most of these need a fresh session (`/reset` in chat, or start a new `hermes` invocation) because they're read once at startup.\\n\\n### Secret redaction in tool output\\n\\nSecret redaction is **off by default** — tool output (terminal stdout, `read_file`, web content, subagent summaries, etc.) passes through unmodified. If the user wants Hermes to auto-mask strings that look like API keys, tokens, and secrets before they enter the conversation context and logs:\\n\\n```bash\\nhermes config set security.redact_secrets true # enable globally\\n```\\n\\n**Restart required.** `security.redact_secrets` is snapshotted at import time — toggling it mid-session (e.g. via `export HERMES_REDACT_SECRETS=true` from a tool call) will NOT take effect for the running process. Tell the user to run `hermes config set security.redact_secrets true` in a terminal, then start a new session. This is deliberate — it prevents an LLM from flipping the toggle on itself mid-task.\\n\\nDisable again with:\\n```bash\\nhermes config set security.redact_secrets false\\n```\\n\\n### PII redaction in gateway messages\\n\\nSeparate from secret redaction. When enabled, the gateway hashes user IDs and strips phone numbers from the session context before it reaches the model:\\n\\n```bash\\nhermes config set privacy.redact_pii true # enable\\nhermes config set privacy.redact_pii false # disable (default)\\n```\\n\\n### Command approval prompts\\n\\nBy default (`approvals.mode: manual`), Hermes prompts the user before running shell commands flagged as destructive (`rm -rf`, `git reset --hard`, etc.). The modes are:\\n\\n- `manual` — always prompt (default)\\n- `smart` — use an auxiliary LLM to auto-approve low-risk commands, prompt on high-risk\\n- `off` — skip all approval prompts (equivalent to `--yolo`)\\n\\n```bash\\nhermes config set approvals.mode smart # recommended middle ground\\nhermes config set approvals.mode off # bypass everything (not recommended)\\n```\\n\\nPer-invocation bypass without changing config:\\n- `hermes --yolo …`\\n- `export HERMES_YOLO_MODE=1`\\n\\nNote: YOLO / `approvals.mode: off` does NOT turn off secret redaction. They are independent.\\n\\n### Shell hooks allowlist\\n\\nSome shell-hook integrations require explicit allowlisting before they fire. Managed via `~/.hermes/shell-hooks-allowlist.json` — prompted interactively the first time a hook wants to run.\\n\\n### Disabling the web/browser/image-gen tools\\n\\nTo keep the model away from network or media tools entirely, open `hermes tools` and toggle per-platform. Takes effect on next session (`/reset`). See the Tools & Skills section above.\\n\\n---\\n\\n### Voice & Transcription\\n\\n### STT (Voice → Text)\\n\\nVoice messages from messaging platforms are auto-transcribed.\\n\\n**⚠️ Pitfall: faster-whisper must be installed for local STT to work.** The config may show `provider: local` but if `faster-whisper` is not installed in the venv, STT silently fails. Always verify with `pip show faster-whisper` after configuring local STT.\\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`\\n4. **Mistral Voxtral** — set `MISTRAL_API_KEY`\\n\\nConfig:\\n```yaml\\nstt:\\n enabled: true\\n provider: local # local, groq, openai, mistral\\n local:\\n model: small # tiny, base, small, medium, large-v3 — use 'small' or higher for German\\n language: de # always set explicitly for German — auto-detect is unreliable\\n```\\n\\n### Pitfalls\\n- **faster-whisper must be installed** — config shows `provider: local` but STT silently fails if the package is missing\\n- **Use `small` model minimum for German** — `base` is too weak\\n- **Set `language: de` explicitly** — auto-detect is unreliable\\n- **Swiss German (dialect) is NOT supported** — Whisper transcribes dialect poorly; user should speak Standard German\\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| MiniMax | `MINIMAX_API_KEY` | Paid |\\n| Mistral (Voxtral) | `MISTRAL_API_KEY` | Paid |\\n| NeuTTS (local) | None (`pip install neutts[all]` + `espeak-ng`) | Free |\\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## Durable & Background Systems\\n\\nFour systems run alongside the main conversation loop. Quick reference\\nhere; full developer notes live in `AGENTS.md`, user-facing docs under\\n`website/docs/user-guide/features/`.\\n\\n### Delegation (`delegate_task`)\\n\\nSynchronous subagent spawn — the parent waits for the child's summary\\nbefore continuing its own loop. Isolated context + terminal session.\\n\\n- **Single:** `delegate_task(goal, context, toolsets)`.\\n- **Batch:** `delegate_task(tasks=[{goal, ...}, ...])` runs children in\\n parallel, capped by `delegation.max_concurrent_children` (default 3).\\n- **Roles:** `leaf` (default; cannot re-delegate) vs `orchestrator`\\n (can spawn its own workers, bounded by `delegation.max_spawn_depth`).\\n- **Not durable.** If the parent is interrupted, the child is\\n cancelled. For work that must outlive the turn, use `cronjob` or\\n `terminal(background=True, notify_on_complete=True)`.\\n\\nConfig: `delegation.*` in `config.yaml`.\\n\\n### Cron (scheduled jobs)\\n\\nDurable scheduler — `cron/jobs.py` + `cron/scheduler.py`. Drive it via\\nthe `cronjob` tool, the `hermes cron` CLI (`list`, `add`, `edit`,\\n`pause`, `resume`, `run`, `remove`), or the `/cron` slash command.\\n\\n- **Schedules:** duration (`\\\"30m\\\"`, `\\\"2h\\\"`), \\\"every\\\" phrase\\n (`\\\"every monday 9am\\\"`), 5-field cron (`\\\"0 9 * * *\\\"`), or ISO timestamp.\\n- **Per-job knobs:** `skills`, `model`/`provider` override, `script`\\n (pre-run data collection; `no_agent=True` makes the script the whole\\n job), `context_from` (chain job A's output into job B), `workdir`\\n (run in a specific dir with its `AGENTS.md` / `CLAUDE.md` loaded),\\n multi-platform delivery.\\n- **Invariants:** 3-minute hard interrupt per run, `.tick.lock` file\\n prevents duplicate ticks across processes, cron sessions pass\\n `skip_memory=True` by default, and cron deliveries are framed with a\\n header/footer instead of being mirrored into the target gateway\\n session (keeps role alternation intact).\\n\\nUser docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/cron\\n\\n### Curator (skill lifecycle)\\n\\nBackground maintenance for agent-created skills. Tracks usage, marks\\nidle skills stale, archives stale ones, keeps a pre-run tar.gz backup\\nso nothing is lost.\\n\\n- **CLI:** `hermes curator ` — `status`, `run`, `pause`, `resume`,\\n `pin`, `unpin`, `archive`, `restore`, `prune`, `backup`, `rollback`.\\n- **Slash:** `/curator ` mirrors the CLI.\\n- **Scope:** only touches skills with `created_by: \\\"agent\\\"` provenance.\\n Bundled + hub-installed skills are off-limits. **Never deletes** —\\n max destructive action is archive. Pinned skills are exempt from\\n every auto-transition and every LLM review pass.\\n- **Telemetry:** sidecar at `~/.hermes/skills/.usage.json` holds\\n per-skill `use_count`, `view_count`, `patch_count`,\\n `last_activity_at`, `state`, `pinned`.\\n\\nConfig: `curator.*` (`enabled`, `interval_hours`, `min_idle_hours`,\\n`stale_after_days`, `archive_after_days`, `backup.*`).\\nUser docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/curator\\n\\n### Kanban (multi-agent work queue)\\n\\nDurable SQLite board for multi-profile / multi-worker collaboration.\\nUsers drive it via `hermes kanban `; dispatcher-spawned workers\\nsee a focused `kanban_*` toolset gated by `HERMES_KANBAN_TASK` so the\\nschema footprint is zero outside worker processes.\\n\\n- **CLI verbs (common):** `init`, `create`, `list` (alias `ls`),\\n `show`, `assign`, `link`, `unlink`, `comment`, `complete`, `block`,\\n `unblock`, `archive`, `tail`. Less common: `watch`, `stats`, `runs`,\\n `log`, `dispatch`, `daemon`, `gc`.\\n- **Worker toolset:** `kanban_show`, `kanban_complete`, `kanban_block`,\\n `kanban_heartbeat`, `kanban_comment`, `kanban_create`, `kanban_link`.\\n- **Dispatcher** runs inside the gateway by default\\n (`kanban.dispatch_in_gateway: true`) — reclaims stale claims,\\n promotes ready tasks, atomically claims, spawns assigned profiles.\\n Auto-blocks a task after ~5 consecutive spawn failures.\\n- **Isolation:** board is the hard boundary (workers get\\n `HERMES_KANBAN_BOARD` pinned in env); tenant is a soft namespace\\n within a board for workspace-path + memory-key isolation.\\n\\nUser docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/kanban\\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. In gateway: `/restart`. In CLI: exit and relaunch.\\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\\n4. **Copilot 403**: `gh auth login` tokens do NOT work for Copilot API. You must use the Copilot-specific OAuth device code flow via `hermes model` → GitHub Copilot.\\n\\n### Changes not taking effect\\n- **Tools/skills:** `/reset` starts a new session with updated toolset\\n- **Config changes:** In gateway: `/restart`. In CLI: exit and relaunch.\\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### Gateway issues\\nCheck logs first:\\n```bash\\ngrep -i \\\"failed to send\\\\|error\\\" ~/.hermes/logs/gateway.log | tail -20\\n```\\n\\nCommon gateway problems:\\n- **Gateway dies on SSH logout**: Enable linger: `sudo loginctl enable-linger $USER`\\n- **Gateway dies on WSL2 close**: WSL2 requires `systemd=true` in `/etc/wsl.conf` for systemd services to work. Without it, gateway falls back to `nohup` (dies when session closes).\\n- **Gateway crash loop**: Reset the failed state: `systemctl --user reset-failed hermes-gateway`\\n\\n### Platform-specific issues\\n- **Discord bot silent**: Must enable **Message Content Intent** in Bot → Privileged Gateway Intents.\\n- **Slack bot only works in DMs**: Must subscribe to `message.channels` event. Without it, the bot ignores public channels.\\n- **Windows HTTP 400 \\\"No models provided\\\"**: Config file encoding issue (BOM). Ensure `config.yaml` is saved as UTF-8 without BOM.\\n\\n### Auxiliary models not working\\nIf `auxiliary` tasks (vision, compression, session_search) fail silently, the `auto` provider can't find a backend. Either set `OPENROUTER_API_KEY` or `GOOGLE_API_KEY`, or explicitly configure each auxiliary task's provider:\\n```bash\\nhermes config set auxiliary.vision.provider \\nhermes config set auxiliary.vision.model \\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, context compression, memory, model routing, credential pooling, skill dispatch\\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 to `toolsets.py`** → `_HERMES_CORE_TOOLS` list.\\n\\nAuto-discovery: any `tools/*.py` file with a top-level `registry.register()` call is imported automatically — no manual list needed.\\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\\npython -m pytest tests/ -o 'addopts=' -q # Full suite\\npython -m pytest tests/tools/ -q # Specific area\\n```\\n\\n- Tests auto-redirect `HERMES_HOME` to temp dirs — never touch real `~/.hermes/`\\n- Run full suite before pushing any change\\n- Use `-o 'addopts='` to clear any baked-in pytest flags\\n\\n### Commit Conventions\\n\\n```\\ntype: concise subject line\\n\\nOptional body.\\n```\\n\\nTypes: `fix:`, `feat:`, `refactor:`, `docs:`, `chore:`\\n\\n### Key Rules\\n\\n- **Never break prompt caching** — don't change context, tools, or system prompt mid-conversation\\n- **Message role alternation** — never two assistant or two user messages in a row\\n- Use `get_hermes_home()` from `hermes_constants` for all paths (profile-safe)\\n- Config values go in `config.yaml`, secrets go in `.env`\\n- New tools need a `check_fn` so they only appear when requirements are met\\n\", \"path\": \"autonomous-ai-agents/hermes-agent/SKILL.md\", \"skill_dir\": \"/home/agent/.hermes/skills/autonomous-ai-agents/hermes-agent\", \"linked_files\": {\"references\": [\"references/telegram-gateway-setup.md\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\", \"metadata\": {\"hermes\": {\"tags\": [\"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_rUr2niL84iH4ngpBgm5dFIVs", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "tool", "name": "skill_view", "content": "{\"success\": false, \"error\": \"Skill 'token-optimizer' not found.\", \"available_skills\": [\"cronjob\", \"dogfood\", \"edge-tts\", \"health-management\", \"jarvis-routing-policy\", \"yazio-integration\", \"yuanbao\", \"claude-code\", \"codex\", \"hermes-agent\", \"opencode\", \"architecture-diagram\", \"ascii-art\", \"ascii-video\", \"baoyu-comic\", \"baoyu-infographic\", \"claude-design\", \"comfyui\", \"design-md\", \"excalidraw\"], \"hint\": \"Use skills_list to see all available skills\"}", "tool_call_id": "call_jp5AUKauIglhhxo1oHx4iAfM", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqBXz-dktW4XXYNhaW7W74rBvknfpwUvK3NgBwyhAwjhu1t2-G3U59HpdT6P-FI8rJxnQ267SAKq4unaE74a75gAFvzPrwySwrOSTwrbDATODCBwFNUwSK8h265DMsWxfCb-N9gAWjJ2Voh_SHfcKsZkNH5e_g3z3wWRNmtXh6EjD93Ut8bx9HU1qlBO-H5da2fcOjEDLHc3CPwW_KnR2r5MBay-xC99Uj_6eIc_Usn61GF5Ty7L4HU7Aqn4Uaz8XbPXdgyGNRV_TU858kHnTct7dMb7iyX1vi-ScSHSsytnDZKeC6a0Jv91R6zdKwpvqErBHNoc-wKQESbMnUDHadbOZQ6mK4mnRT1h7oCCfFs553UIuT7oD1HQ8iAuGKUW_mbUQ1g2_KCcszDyK3u-EAHdHDAabFL5N5evv149mgKehx8AKdEeIPxQyILdMl3_ITs6YxM2jhKPU6xC913wUyJsXr2Z-aYACEFz2tM--k8q_he-Vilu5Udrms3Bq1iKYCjWe1Pmgfl8MJdUrYd9l4skVx2qcRCA7YWMV1sojjz3EQlZIvsCIDlLK7x9VZvoinnQSulzhILzybjJvzzlZp7uYdwjA-nLfBStPeVRaChksmbmbAm7Q38y2YUxBStS3Jxmiq0Y8zkKQOKpr9Zeg9u-GlgQppZzNwa-PDi2D3Uwp-wiuilCzD1epHH4A0q7eEqo3Z4FdsqoVAoftw_sFaUfeuuYTFmGqF4RUkr180WvmM7JGIN-ayOnI7mKGElqJMhyzar8x9wBrjXoxIVfXM3-mkSsldnX0cbj_lLfR6Ed90fW-p68ay-mRBMpdHgEovPQ38iZH9Cj-B1CpBB1X6DbMh0Vk-IAplnxw10w7dpVwHagzsEk2d0xzOYpZZ1wHGwjvjf4USENPdvuSw2M4vGP0etfEih5DhMHR3MiP6boVeePSOgJcbvnkye9dy8ML85JSICJcT0CBApqZDvymniUQwvFbhoMxIxMowm4GiyitUKgYQZ_p9pqTO87obOK7AgYi25FpYhVyCfEbq8YwS2jlcGENM_rcjOzxx3_I0nBMQYiQp5zVUTXW0MMNz2bzRctuuA2xfz7wOuYdb1ffkupBTwIwap4beTPwjvE8uQ9lKToANU0B26zMTT0sldb3z6vLppkUsx95lcar5JqjpWupSj9e5W-MopFhj93AyWOP_VkTBOhyiq7YJhQvPX1PAZ0z55qdgEIYDrp94XkWUubzwB-8EG9Jg7DeTgXuioMpA5tABPcqI_ApRekbcj113ICNok-6XOZsRZFZweAL3EfJHE3BPTpSuFpcKRv2D5aZh62hZKBaCM9szCRF4dJg4QibTN084H4Mh_C0WHPUMy9Xd2a6lCeb8TNXg-YxFcCHb0TuAOiy8uDIvgS187YHvc6NFa_-ZUctCeUH7h4fIjxiEQJHwMn997mdyhVFVD7qzPwAbJJ5LKS4GpdbST2ObuquMd5pSUb2GLImV_WZw295NNe0DLCi9LVgWA4753FruHfHJYM07jjy5he0DEEw5udxiyrYcYvoImhBYb-tAGdvCDg==", "id": "rs_0cb6f0b9fe50168a016a057cf2ed848191b08e9b923ce35794", "summary": []}], "tool_calls": [{"id": "call_sLICGFaJTeurzyGLH4LaD2h0", "call_id": "call_sLICGFaJTeurzyGLH4LaD2h0", "response_item_id": "fc_0cb6f0b9fe50168a016a057cfee5508191b0375458e4c58c26", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"hermes insights --days 14\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}, {"id": "call_ngKbVNKCrZksyuLtcBVb1sV7", "call_id": "call_ngKbVNKCrZksyuLtcBVb1sV7", "response_item_id": "fc_0cb6f0b9fe50168a016a057cfee56081919a85aa9d9b2a0eee", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"hermes sessions stats\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}, {"id": "call_n8BLh8A93TvLhBLsXwec5ITK", "call_id": "call_n8BLh8A93TvLhBLsXwec5ITK", "response_item_id": "fc_0cb6f0b9fe50168a016a057cfee568819183e02ca89102f53f", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nimport yaml, pathlib\\np=pathlib.Path.home()/'.hermes/config.yaml'\\nprint('CONFIG',p)\\ntry:\\n d=yaml.safe_load(p.read_text()) or {}\\n for k in ['compression','memory','gateway','delegation','model','auxiliary','skills','tools','toolsets']:\\n if k in d: print('\\\\n['+k+']\\\\n', yaml.safe_dump(d[k], sort_keys=False, allow_unicode=True)[:4000])\\nexcept Exception as e: print('ERR',e)\\nPY\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}, {"id": "call_wlxZIQuMlkaPUekyhr0K4ScP", "call_id": "call_wlxZIQuMlkaPUekyhr0K4ScP", "response_item_id": "fc_0cb6f0b9fe50168a016a057cfee57081919c4de8511052bc0d", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nimport urllib.request\\nurls=[\\n 'https://hermes-agent.nousresearch.com/docs/user-guide/features/context-compression',\\n 'https://hermes-agent.nousresearch.com/docs/reference/slash-commands',\\n 'https://hermes-agent.nousresearch.com/docs/user-guide/features/sessions',\\n 'https://hermes-agent.nousresearch.com/docs/user-guide/configuration'\\n]\\nfor u in urls:\\n print('\\\\nURL',u)\\n try:\\n data=urllib.request.urlopen(u,timeout=20).read(200000).decode('utf-8','ignore')\\n # crude strip\\n import re\\n txt=re.sub('',' ',data,flags=re.S)\\n txt=re.sub('',' ',txt,flags=re.S)\\n txt=re.sub('<[^>]+>',' ',txt)\\n txt=re.sub(r'\\\\s+',' ',txt)\\n for term in ['compression','compress','context','token','usage','insights','session','tool']:\\n i=txt.lower().find(term)\\n if i!=-1: print(txt[max(0,i-250):i+600]) ; break\\n except Exception as e: print('ERR',e)\\nPY\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}], "timestamp": "2026-05-14T09:45:30.357460"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"╔══════════════════════════════════════════════════════════╗\\n ║ 📊 Hermes Insights ║\\n ║ Last 14 days ║\\n ╚══════════════════════════════════════════════════════════╝\\n\\n Period: May 07, 2026 — May 14, 2026\\n\\n 📋 Overview\\n ────────────────────────────────────────────────────────\\n Sessions: 94 Messages: 7,538\\n Tool calls: 3,448 User messages: 362\\n Input tokens: 6,402,441 Output tokens: 559,685\\n Total tokens: 112,447,370\\n Active time: ~6.9d Avg session: ~1h 51m\\n Avg msgs/session: 80.2\\n\\n 🤖 Models Used\\n ────────────────────────────────────────────────────────\\n Model Sessions Tokens\\n qwen-3.6-agent 48 69,405,496\\n gpt-5.5 16 39,737,089\\n openrouter 29 3,304,785\\n auto 1 0\\n\\n 📱 Platforms\\n ────────────────────────────────────────────────────────\\n Platform Sessions Messages Tokens\\n telegram 49 7,005 106,314,554\\n cron 43 427 4,024,879\\n cli 2 106 2,107,937\\n\\n 🔧 Top Tools\\n ────────────────────────────────────────────────────────\\n Tool Calls %\\n execute_code 1,268 36.8%\\n terminal 692 20.1%\\n patch 239 6.9%\\n todo 216 6.3%\\n skill_view 158 4.6%\\n write_file 153 4.4%\\n browser_navigate 149 4.3%\\n search_files 93 2.7%\\n browser_console 91 2.6%\\n read_file 88 2.6%\\n memory 71 2.1%\\n skill_manage 58 1.7%\\n cronjob 58 1.7%\\n browser_snapshot 23 0.7%\\n browser_click 20 0.6%\\n ... and 17 more tools\\n\\n 🧠 Top Skills\\n ────────────────────────────────────────────────────────\\n Skill Loads Edits Last used\\n health-data-management 41 52 May 12\\n hermes-agent 14 0 May 13\\n cronjob 11 0 May 13\\n google-workspace 11 0 May 12\\n yazio-integration 7 0 May 12\\n gog 7 0 May 12\\n openclaw-imports:gog 6 0 May 09\\n openclaw-imports:sherpa-onnx 6 0 May 07\\n health-management 3 3 May 12\\n github-repo-management 5 0 May 12\\n Distinct skills: 29 Loads: 158 Edits: 58\\n\\n 📅 Activity Patterns\\n ────────────────────────────────────────────────────────\\n Mon █████ 8\\n Tue ████████████ 17\\n Wed ███ 5\\n Thu █████████ 13\\n Fri ███████ 11\\n Sat █████████████ 19\\n Sun ███████████████ 21\\n\\n Peak hours: 5AM (9), 9AM (9), 10PM (8), 8PM (7), 11PM (6)\\n Active days: 8\\n Best streak: 8 consecutive days\\n\\n 🏆 Notable Sessions\\n ────────────────────────────────────────────────────────\\n Longest session 21h 54m (May 13, 20260513_114750_)\\n Most messages 346 msgs (May 12, 20260512_225913_)\\n Most tokens 449,873 tokens (May 12, 20260512_112553_)\\n Most tool calls 161 calls (May 12, 20260512_225913_)\", \"exit_code\": 0, \"error\": null}\n\n[Subdirectory context discovered: .hermes/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\n# Prefer .venv; fall back to venv if that's what your checkout has.\nsource .venv/bin/activate # or: source venv/bin/activate\n```\n\n`scripts/run_tests.sh` probes `.venv` first, then `venv`, then\n`$HOME/.hermes/hermes-agent/venv` (for worktrees that share a venv with the\nmain checkout).\n\n## Project Structure\n\nFile counts shift constantly — don't treat the tree below as exhaustive.\nThe canonical source is the filesystem. The notes call out the load-bearing\nentry points you'll actually edit.\n\n```\nhermes-agent/\n├── run_agent.py # AIAgent class — core conversation loop (~12k LOC)\n├── model_tools.py # Tool orchestration, discover_builtin_tools(), handle_function_call()\n├── toolsets.py # Toolset definitions, _HERMES_CORE_TOOLS list\n├── cli.py # HermesCLI class — interactive CLI orchestrator (~11k LOC)\n├── hermes_state.py # SessionDB — SQLite session store (FTS5 search)\n├── hermes_constants.py # get_hermes_home(), display_hermes_home() — profile-aware paths\n├── hermes_logging.py # setup_logging() — agent.log / errors.log / gateway.log (profile-aware)\n├── batch_runner.py # Parallel batch processing\n├── agent/ # Agent internals (provider adapters, memory, caching, compression, etc.)\n├── hermes_cli/ # CLI subcommands, setup wizard, plugins loader, skin engine\n├── tools/ # Tool implementations — auto-discovered via tools/registry.py\n│ └── environments/ # Terminal backends (local, docker, ssh, modal, daytona, singularity)\n├── gateway/ # Messaging gateway — run.py + session.py + platforms/\n│ ├── platforms/ # Adapter per platform (telegram, discord, slack, whatsapp,\n│ │ # homeassistant, signal, matrix, mattermost, email, sms,\n│ │ # dingtalk, wecom, weixin, feishu, qqbot, bluebubbles,\n│ │ # yuanbao, webhook, api_server, ...). See ADDING_A_PLATFORM.md.\n│ └── builtin_hooks/ # Extension point for always-registered gateway hooks (none shipped)\n├── plugins/ # Plugin system (see \"Plugins\" section below)\n│ ├── memory/ # Memory-provider plugins (honcho, mem0, supermemory, ...)\n│ ├── context_engine/ # Context-engine plugins\n│ ├── model-providers/ # Inference backend plugins (openrouter, anthropic, gmi, ...)\n│ ├── kanban/ # Multi-agent board dispatcher + worker plugin\n│ ├── hermes-achievements/ # Gamified achievement tracking\n│ ├── observability/ # Metrics / traces / logs plugin\n│ ├── image_gen/ # Image-generation providers\n│ └── / # disk-cleanup, example-dashboard, google_meet, platforms,\n│ # spotify, strike-freedom-cockpit, ...\n├── optional-skills/ # Heavier/niche skills shipped but NOT active by default\n├── skills/ # Built-in skills bundled with the repo\n├── ui-tui/ # Ink (React) terminal UI — `hermes --tui`\n│ └── src/ # entry.tsx, app.tsx, gatewayClient.ts + app/components/hooks/lib\n├── tui_gateway/ # Python JSON-RPC backend for the TUI\n├── acp_adapter/ # ACP server (VS Code / Zed / JetBrains integration)\n├── cron/ # Scheduler — jobs.py, scheduler.py\n├── environments/ # RL training environments (Atropos)\n├── scripts/ # run_tests.sh, release.py, auxiliary scripts\n├── website/ # Docusaurus docs site\n└── tests/ # Pytest suite (~17k tests across ~900 files as of May 2026)\n```\n\n**User config:** `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys only).\n**Logs:** `~/.hermes/logs/` — `agent.log` (INFO+), `errors.log` (WARNING+),\n`gateway.log` when running the gateway. Profile-aware via `get_hermes_home()`.\nBrowse with `hermes logs [--follow] [--level ...] [--session ...]`.\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\nThe real `AIAgent.__init__` takes ~60 parameters (credentials, routing, callbacks,\nsession context, budget, credential pool, etc.). The signature below is the\nminimum subset you'll usually touch — read `run_agent.py` for the full list.\n\n```python\nclass AIAgent:\n def __init__(self,\n base_url: str = None,\n api_key: str = None,\n provider: str = None,\n api_mode: str = None, # \"chat_completions\" | \"codex_responses\" | ...\n model: str = \"\", # empty → resolved from config/provider later\n max_iterations: int = 90, # tool-calling iterations (shared with subagents)\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 credential_pool=None,\n # ... plus callbacks, thread/user/chat IDs, iteration_budget, fallback_model,\n # checkpoints config, prefill_messages, service_tier, reasoning_config, etc.\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, with\ninterrupt checks, budget tracking, and a one-turn grace call:\n\n```python\nwhile (api_call_count < self.max_iterations and self.iteration_budget.remaining > 0) \\\n or self._budget_grace_call:\n if self._interrupt_requested: break\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\", ...}`.\nReasoning 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()` f\n\n[...truncated AGENTS.md: 45,468 chars total]", "tool_call_id": "call_sLICGFaJTeurzyGLH4LaD2h0", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"Total sessions: 94\\nTotal messages: 7538\\n cli: 2 sessions\\n telegram: 49 sessions\\nDatabase size: 58.1 MB\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_ngKbVNKCrZksyuLtcBVb1sV7", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"CONFIG /home/agent/.hermes/config.yaml\\n\\n[compression]\\n enabled: true\\nthreshold: 0.5\\ntarget_ratio: 0.2\\nprotect_last_n: 20\\nhygiene_hard_message_limit: 400\\n\\n\\n[memory]\\n memory_enabled: true\\nuser_profile_enabled: true\\nmemory_char_limit: 2200\\nuser_char_limit: 1375\\nprovider: ''\\nflush_min_turns: 6\\nnudge_interval: 10\\n\\n\\n[gateway]\\n enabled: true\\nplatform: telegram\\ntelegram:\\n allowed_users:\\n - '1344779884'\\n channel_prompts: {}\\n enabled: true\\n home_channel: '1344779884'\\n reactions: false\\n\\n\\n[delegation]\\n model: ''\\nprovider: ''\\nbase_url: ''\\napi_key: ''\\ninherit_mcp_toolsets: true\\nmax_iterations: 50\\nchild_timeout_seconds: 600\\nreasoning_effort: ''\\nmax_concurrent_children: 3\\nmax_spawn_depth: 1\\norchestrator_enabled: true\\nsubagent_auto_approve: false\\n\\n\\n[model]\\n base_url: https://chatgpt.com/backend-api/codex\\ndefault: gpt-5.5\\nprovider: openai-codex\\n\\n\\n[auxiliary]\\n vision:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 120\\n extra_body: {}\\n download_timeout: 30\\nweb_extract:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 360\\n extra_body: {}\\ncompression:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 120\\n extra_body: {}\\nsession_search:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\n max_concurrency: 3\\nskills_hub:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\napproval:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\nmcp:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\ntitle_generation:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\ntriage_specifier:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 120\\n extra_body: {}\\ncurator:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 600\\n extra_body: {}\\n\\n\\n[skills]\\n external_dirs: []\\ntemplate_vars: true\\ninline_shell: false\\ninline_shell_timeout: 10\\nguard_agent_created: false\\ncreation_nudge_interval: 15\\n\\n\\n[toolsets]\\n - hermes-cli\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_n8BLh8A93TvLhBLsXwec5ITK", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"URL https://hermes-agent.nousresearch.com/docs/user-guide/features/context-compression\\nERR HTTP Error 404: Not Found\\n\\nURL https://hermes-agent.nousresearch.com/docs/reference/slash-commands\\n session /history Show conversation history /save Save the current conversation /retry Retry the last message (resend to agent) /undo Remove the last user/assistant exchange /title Set a title for the current session (usage: /title My Session Name) /compress [focus topic] Manually compress conversation context (flush memories + summarize). Optional focus topic narrows what the summary preserves. /rollback List or restore filesystem checkpoints (usage: /rollback [number]) /snapshot [create|restore <id>|prune] (alias: /snap ) Create or restore state snapshots of Hermes config/state. create [label] saves a snapshot, restore <id> reverts to it, prune [N] removes old snapshots, or list all with no args. /stop Kill all running background processes /queue <prompt> (alias: /q ) Queue a prompt for the next turn (doesn't inte\\n\\nURL https://hermes-agent.nousresearch.com/docs/user-guide/features/sessions\\nERR HTTP Error 404: Not Found\\n\\nURL https://hermes-agent.nousresearch.com/docs/user-guide/configuration\\ns & Tutorials Developer Guide Reference Using Hermes Configuration On this page Configuration All settings are stored in the ~/.hermes/ directory for easy access. Directory Structure ​ ~/.hermes/ ├── config.yaml # Settings (model, terminal, TTS, compression, etc.) ├── .env # API keys and secrets ├── auth.json # OAuth provider credentials (Nous Portal, etc.) ├── SOUL.md # Primary agent identity (slot #1 in system prompt) ├── memories/ # Persistent memory (MEMORY.md, USER.md) ├── skills/ # Agent-created skills (managed via skill_manage tool) ├── cron/ # Scheduled jobs ├── sessions/ # Gateway sessions └── logs/ # Logs (errors.log, gateway.log — secrets auto-redacted) Managing Configuration ​ hermes config # View current configuration hermes config edit # Open config.yaml in your editor hermes config set KEY VAL # Set a specific value her\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_wlxZIQuMlkaPUekyhr0K4ScP", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "assistant", "content": "", "reasoning": "**Considering data comparison**\n\nI think I need to compare \"sparsamer\" over specific days. Maybe I should check insights for days 7/30? It looks like I might have to parse daily tokens, though it seems that Hermes insights might not provide daily data. I'll need to use SQLite to dig into the sessions database. So, I should run some terminal SQLite queries and figure out the schema. That way, I can understand how to extract the information I need.", "finish_reason": "tool_calls", "reasoning_content": "**Considering data comparison**\n\nI think I need to compare \"sparsamer\" over specific days. Maybe I should check insights for days 7/30? It looks like I might have to parse daily tokens, though it seems that Hermes insights might not provide daily data. I'll need to use SQLite to dig into the sessions database. So, I should run some terminal SQLite queries and figure out the schema. That way, I can understand how to extract the information I need.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqBX0J25RJBwHnTWRODJc2b2p1FrXGP70iYiqbx1Z8RiZBrIoOe3fLb0FEav_w4qhvdDR-ISPX3bU2Lbt4VjlvL8NqsCvXbvVhpmKw5GRvpHMWFDx01QW4_doE2qMRlA3txa3cCChuhdmuvRM98nwcP2NCGoHPP0A8cuiZIotEPcWZJWWOsVrkptpaW3EtQi8lWM1NnF6VL8R0DMigN8vMs9UcUpW5RRFRcWQVs26wLuGnbZkgksj80rRTw7RcCTYuYGXP7mr5ipLSM8O47QXGESnnJvvgMc-6ZITKBJCJeYJleDxvJcwnAWerZwPJYFWq7L3tRFWafaVdIN9AV18v8TQwlOy6w206rl1CcB30EOo5F2_OWs_LYmcOo2Y5N0zYL3Qi9FQHyahStZ6SkyshlB0Zw-U1TB5tu8SXCu2nWVxz-0MaZgldmcayBNrsFbPRbLERnEJ0JoTVXWLHv516rkaaD2Pni6AmsbVKF81AjNpp65-IBWhHJpUh-k5etgPJPvenuKRcI4vcj5NjuFvolnLQzGMP635EloN09OPwztN8mIDj0eMkZF2DeajWsU2NShyF2pNX3_c1eFg0vsCX6LH00VK2nOpub9971j9N7JPofA7UaztVvRqWfN0ZLau3bAkzL_dc4b3EqoSmIgEjWBy_caQb5bsggXWjf6tsiyGOFBGJ74H1i7d5wDGKQSIUSumt3fIv5oH9G8aypD9qjSxJBb8INIHZabEfeif8MihbNTZoTGK20dO-XAWwnCQXtKYn60uQ63SXMutIH7_lByo57eELZ3NrFXFtn3K81AHBOqr1Q1We71_DhMhKnXYTja04grX8xVV3gxuM24-5_3BB4OSxSfs_ZR7efrL-DRY9cAyL804ObEDAXwoRXtAc2nk3RQz56F97-Y_FDEmnkt5_TvOnxgYiLhnXc6woKVTG8A7o_e3hJkOQ1fD_Odfi0Q1rQompY2suo4-AmxxLQQ2V4VKyZVp_8WM-XLE86pLxIdZi215Wacri8W6ssy1d3y8WSwUV_IT0hQXlpY254QAeAomAlxGikYfZIs-W2JvkYKbkCmVy9EV4aG4gdW3VjvvZuxWCaenhPm5kVNAB8Z7-X5KRPFuok9OQEz4G4wotpQYS9E-ncG1U2kBIYyuoYH94CbW-Mtnj1xkz7nnvgp_lec-ZOjtYibpAj9mbWseHF8ZuQTrjHvrBemrLi1sUP7r8", "id": "rs_0c8a58d2d593cfc4016a057d06fa80819182e3817b571e28d8", "summary": [{"type": "summary_text", "text": "**Considering data comparison**\n\nI think I need to compare \"sparsamer\" over specific days. Maybe I should check insights for days 7/30? It looks like I might have to parse daily tokens, though it seems that Hermes insights might not provide daily data. I'll need to use SQLite to dig into the sessions database. So, I should run some terminal SQLite queries and figure out the schema. That way, I can understand how to extract the information I need."}]}], "tool_calls": [{"id": "call_0Edpq9oxH0GHkf6SP8uCMSRY", "call_id": "call_0Edpq9oxH0GHkf6SP8uCMSRY", "response_item_id": "fc_0c8a58d2d593cfc4016a057d0e4704819195117562ce982a1a", "type": "function", "function": {"name": "search_files", "arguments": "{\"pattern\":\"*.db\",\"target\":\"files\",\"path\":\"/home/agent/.hermes\",\"limit\":20}"}}, {"id": "call_JydtfSSCcDE29sSGuoZO3xVv", "call_id": "call_JydtfSSCcDE29sSGuoZO3xVv", "response_item_id": "fc_0c8a58d2d593cfc4016a057d0e471881919e28cb100061bbf3", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"hermes insights --days 3 && printf '\\\\n---30d---\\\\n' && hermes insights --days 30\",\"timeout\":180,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}, {"id": "call_6uJg0pcdv73crdOdSZVgdXRC", "call_id": "call_6uJg0pcdv73crdOdSZVgdXRC", "response_item_id": "fc_0c8a58d2d593cfc4016a057d0e47548191867927cefa10ed95", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nimport urllib.request, re\\nbase='https://hermes-agent.nousresearch.com/docs'\\nfor path in ['/search?q=compression','/search?q=tokens','/user-guide/features/context-management','/user-guide/features/memory','/user-guide/gateway/telegram','/user-guide/messaging/telegram']:\\n u=base+path\\n print('\\\\nURL',u)\\n try:\\n data=urllib.request.urlopen(u,timeout=15).read(150000).decode('utf-8','ignore')\\n txt=re.sub('',' ',data,flags=re.S); txt=re.sub('',' ',txt,flags=re.S); txt=re.sub('<[^>]+>',' ',txt); txt=re.sub(r'\\\\s+',' ',txt)\\n print(txt[:2000])\\n except Exception as e: print('ERR',e)\\nPY\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}], "timestamp": "2026-05-14T09:45:30.357460"} {"role": "tool", "name": "search_files", "content": "{\"total_count\": 20, \"files\": [\"/home/agent/.hermes/state.db\", \"/home/agent/.hermes/assets/Gesundheit/health_data.db\", \"/home/agent/.hermes/kanban.db\", \"/home/agent/.hermes/hermes-agent/node_modules/camoufox-js/dist/data-files/webgl_data.db\", \"/home/agent/.hermes/state-snapshots/20260513-211310-pre-update/state.db\", \"/home/agent/.hermes/state-snapshots/20260512-204320-weekly-health/state.db\", \"/home/agent/.hermes/state-snapshots/20260512-204141-weekly-health/state.db\", \"/home/agent/.hermes/assets/Gesundheit/backups/health_data_before_apple_health_dedupe_20260512_210117.db\", \"/home/agent/.hermes/assets/Gesundheit/backups/health_data_before_vitd_report_fix_20260512_204159.db\", \"/home/agent/.hermes/assets/Gesundheit/backups/health_data_before_dashboard_event_cleanup_20260512_175800.db\", \"/home/agent/.hermes/assets/Gesundheit/backups/health_data_before_full_reprocess_20260512_172848.db\", \"/home/agent/.hermes/assets/Gesundheit/backups/health_data_before_full_reprocess_20260512_172837.db\", \"/home/agent/.hermes/assets/Gesundheit/backups/health_data_before_full_reprocess_20260512_172549.db\", \"/home/agent/.hermes/assets/Gesundheit/backups/health_data_before_full_reprocess_20260512_172535.db\", \"/home/agent/.hermes/assets/Gesundheit/backups/health_data_before_full_reprocess_20260512_172451.db\", \"/home/agent/.hermes/assets/Gesundheit/backups/health_data_before_full_reprocess_20260512_172414.db\", \"/home/agent/.hermes/assets/Gesundheit/backups/health_data_before_dashboard_v3_20260512_165556.db\", \"/home/agent/.hermes/assets/Gesundheit/backups/health_data_before_review_workflow_20260512_154748.db\", \"/home/agent/.hermes/assets/health_data.db\", \"/home/agent/.hermes/assets/Gesundheit/backups/health_data_before_review_workflow_20260512_154732.db\"]}", "tool_call_id": "call_0Edpq9oxH0GHkf6SP8uCMSRY", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"╔══════════════════════════════════════════════════════════╗\\n ║ 📊 Hermes Insights ║\\n ║ Last 3 days ║\\n ╚══════════════════════════════════════════════════════════╝\\n\\n Period: May 11, 2026 — May 14, 2026\\n\\n 📋 Overview\\n ────────────────────────────────────────────────────────\\n Sessions: 28 Messages: 3,292\\n Tool calls: 1,548 User messages: 119\\n Input tokens: 2,572,352 Output tokens: 266,190\\n Total tokens: 52,771,255\\n Active time: ~2.5d Avg session: ~2h 12m\\n Avg msgs/session: 117.6\\n\\n 🤖 Models Used\\n ────────────────────────────────────────────────────────\\n Model Sessions Tokens\\n gpt-5.5 16 39,769,553\\n qwen-3.6-agent 10 12,572,712\\n openrouter 1 428,990\\n auto 1 0\\n\\n 📱 Platforms\\n ────────────────────────────────────────────────────────\\n Platform Sessions Messages Tokens\\n telegram 17 3,202 51,854,281\\n cron 11 90 916,974\\n\\n 🔧 Top Tools\\n ────────────────────────────────────────────────────────\\n Tool Calls %\\n terminal 502 32.4%\\n todo 187 12.1%\\n patch 160 10.3%\\n execute_code 121 7.8%\\n skill_view 102 6.6%\\n browser_console 89 5.7%\\n search_files 83 5.4%\\n write_file 79 5.1%\\n read_file 52 3.4%\\n skill_manage 50 3.2%\\n browser_navigate 47 3.0%\\n cronjob 34 2.2%\\n memory 29 1.9%\\n browser_vision 5 0.3%\\n session_search 4 0.3%\\n ... and 1 more tools\\n\\n 🧠 Top Skills\\n ────────────────────────────────────────────────────────\\n Skill Loads Edits Last used\\n health-data-management 41 48 May 12\\n hermes-agent 12 0 May 13\\n cronjob 9 0 May 13\\n google-workspace 9 0 May 12\\n yazio-integration 7 0 May 12\\n github-repo-management 5 0 May 12\\n jarvis-routing-policy 3 2 May 13\\n github-auth 3 0 May 12\\n gog 3 0 May 12\\n gmail-archive 3 0 May 12\\n Distinct skills: 15 Loads: 102 Edits: 50\\n\\n 📅 Activity Patterns\\n ────────────────────────────────────────────────────────\\n Mon ███ 4\\n Tue ███████████████ 17\\n Wed ████ 5\\n Thu █ 2\\n Fri 0\\n Sat 0\\n Sun 0\\n\\n Peak hours: 5AM (4), 9AM (4), 7PM (3), 7AM (2), 11AM (2)\\n Active days: 4\\n Best streak: 4 consecutive days\\n\\n 🏆 Notable Sessions\\n ────────────────────────────────────────────────────────\\n Longest session 21h 54m (May 13, 20260513_114750_)\\n Most messages 346 msgs (May 12, 20260512_225913_)\\n Most tokens 449,873 tokens (May 12, 20260512_112553_)\\n Most tool calls 161 calls (May 12, 20260512_225913_)\\n\\n\\n---30d---\\n\\n ╔══════════════════════════════════════════════════════════╗\\n ║ 📊 Hermes Insights ║\\n ║ Last 30 days ║\\n ╚══════════════════════════════════════════════════════════╝\\n\\n Period: May 07, 2026 — May 14, 2026\\n\\n 📋 Overview\\n ────────────────────────────────────────────────────────\\n Sessions: 94 Messages: 7,538\\n Tool calls: 3,448 User messages: 362\\n Input tokens: 6,407,877 Output tokens: 560,089\\n Total tokens: 112,479,834\\n Active time: ~6.9d Avg session: ~1h 51m\\n Avg msgs/session: 80.2\\n\\n 🤖 Models Used\\n ────────────────────────────────────────────────────────\\n Model Sessions Tokens\\n qwen-3.6-agent 48 69,405,496\\n gpt-5.5 16 39,769,553\\n openrouter 29 3,304,785\\n auto 1 0\\n\\n 📱 Platforms\\n ────────────────────────────────────────────────────────\\n Platform Sessions Messages Tokens\\n telegram 49 7,005 106,347,018\\n cron 43 427 4,024,879\\n cli 2 106 2,107,937\\n\\n 🔧 Top Tools\\n ────────────────────────────────────────────────────────\\n Tool Calls %\\n execute_code 1,268 36.8%\\n terminal 692 20.1%\\n patch 239 6.9%\\n todo 216 6.3%\\n skill_view 158 4.6%\\n write_file 153 4.4%\\n browser_navigate 149 4.3%\\n search_files 93 2.7%\\n browser_console 91 2.6%\\n read_file 88 2.6%\\n memory 71 2.1%\\n skill_manage 58 1.7%\\n cronjob 58 1.7%\\n browser_snapshot 23 0.7%\\n browser_click 20 0.6%\\n ... and 17 more tools\\n\\n 🧠 Top Skills\\n ────────────────────────────────────────────────────────\\n Skill Loads Edits Last used\\n health-data-management 41 52 May 12\\n hermes-agent 14 0 May 13\\n cronjob 11 0 May 13\\n google-workspace 11 0 May 12\\n yazio-integration 7 0 May 12\\n gog 7 0 May 12\\n openclaw-imports:gog 6 0 May 09\\n openclaw-imports:sherpa-onnx 6 0 May 07\\n health-management 3 3 May 12\\n github-repo-management 5 0 May 12\\n Distinct skills: 29 Loads: 158 Edits: 58\\n\\n 📅 Activity Patterns\\n ────────────────────────────────────────────────────────\\n Mon █████ 8\\n Tue ████████████ 17\\n Wed ███ 5\\n Thu █████████ 13\\n Fri ███████ 11\\n Sat █████████████ 19\\n Sun ███████████████ 21\\n\\n Peak hours: 5AM (9), 9AM (9), 10PM (8), 8PM (7), 11PM (6)\\n Active days: 8\\n Best streak: 8 consecutive days\\n\\n 🏆 Notable Sessions\\n ────────────────────────────────────────────────────────\\n Longest session 21h 54m (May 13, 20260513_114750_)\\n Most messages 346 msgs (May 12, 20260512_225913_)\\n Most tokens 449,873 tokens (May 12, 20260512_112553_)\\n Most tool calls 161 calls (May 12, 20260512_225913_)\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_JydtfSSCcDE29sSGuoZO3xVv", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"URL https://hermes-agent.nousresearch.com/docs/search?q=compression\\n Search the documentation Skip to main content Hermes Agent Docs Skills English English 简体中文 Home GitHub Discord Search the documentation Docs Getting Started User Guide Developer Guide Reference Community Discord GitHub Discussions Skills Hub More GitHub Nous Research Built by Nous Research · MIT License · 2026 \\n\\nURL https://hermes-agent.nousresearch.com/docs/search?q=tokens\\n Search the documentation Skip to main content Hermes Agent Docs Skills English English 简体中文 Home GitHub Discord Search the documentation Docs Getting Started User Guide Developer Guide Reference Community Discord GitHub Discussions Skills Hub More GitHub Nous Research Built by Nous Research · MIT License · 2026 \\n\\nURL https://hermes-agent.nousresearch.com/docs/user-guide/features/context-management\\nERR HTTP Error 404: Not Found\\n\\nURL https://hermes-agent.nousresearch.com/docs/user-guide/features/memory\\n Persistent Memory | Hermes Agent Skip to main content Hermes Agent Docs Skills English English 简体中文 Home GitHub Discord User Stories & Use Cases Getting Started Using Hermes Features Overview Tool Gateway Core Tools & Toolsets Skills System LSP — Semantic Diagnostics Curator Persistent Memory Memory Providers Context Files Context References Personality & SOUL.md Skins & Themes Plugins Built-in Plugins Automation Media & Web Management Advanced Skills Messaging Platforms Integrations Guides & Tutorials Developer Guide Reference Features Core Persistent Memory On this page Persistent Memory Hermes Agent has bounded, curated memory that persists across sessions. This lets it remember your preferences, your projects, your environment, and things it has learned. How It Works ​ Two files make up the agent's memory: File Purpose Char Limit MEMORY.md Agent's personal notes — environment facts, conventions, things learned 2,200 chars (~800 tokens) USER.md User profile — your preferences, communication style, expectations 1,375 chars (~500 tokens) Both are stored in ~/.hermes/memories/ and are injected into the system prompt as a frozen snapshot at session start. The agent manages its own memory via the memory tool — it can add, replace, or remove entries. info Character limits keep memory focused. When memory is full, the agent consolidates or replaces entries to make room for new information. How Memory Appears in the System Prompt ​ At the start of every session, memory entries are loaded from disk and rendered into the system prompt as a frozen block: ══════════════════════════════════════════════ MEMORY (your personal notes) [67% — 1,474/2,200 chars] ══════════════════════════════════════════════ User's project is a Rust web service at ~/code/myapi using Axum + SQLx § This machine runs Ubuntu 22.04, has Docker and Podman installed § User prefers concise responses, dislikes verbose explanations The format includes: A header showing\\n\\nURL https://hermes-agent.nousresearch.com/docs/user-guide/gateway/telegram\\nERR HTTP Error 404: Not Found\\n\\nURL https://hermes-agent.nousresearch.com/docs/user-guide/messaging/telegram\\n Telegram | Hermes Agent Skip to main content Hermes Agent Docs Skills English English 简体中文 Home GitHub Discord User Stories & Use Cases Getting Started Using Hermes Features Messaging Platforms Messaging Gateway Telegram Discord Slack WhatsApp Signal Email SMS (Twilio) Home Assistant Mattermost Matrix DingTalk Feishu / Lark WeCom (Enterprise WeChat) WeCom Callback (Self-Built App) Weixin (WeChat) BlueBubbles (iMessage) QQ Bot Yuanbao Microsoft Teams Teams Meetings Microsoft Graph Webhook Listener LINE Open WebUI Webhooks Integrations Guides & Tutorials Developer Guide Reference Messaging Platforms Telegram On this page Telegram Setup Hermes Agent integrates with Telegram as a full-featured conversational bot. Once connected, you can chat with your agent from any device, send voice memos that get auto-transcribed, receive scheduled task results, and use the agent in group chats. The integration is built on python-telegram-bot and supports text, voice, images, and file attachments. Step 1: Create a Bot via BotFather ​ Every Telegram bot requires an API token issued by @BotFather , Telegram's official bot management tool. Open Telegram and search for @BotFather , or visit t.me/BotFather Send /newbot Choose a display name (e.g., "Hermes Agent") — this can be anything Choose a username — this must be unique and end in bot (e.g., my_hermes_bot ) BotFather replies with your API token . It looks like this: 123456789:ABCdefGHIjklMNOpqrSTUvwxYZ warning Keep your bot token secret. Anyone with this token can control your bot. If it leaks, revoke it immediately via /revoke in BotFather. Step 2: Customize Your Bot (Optional) ​ These BotFather commands improve the user experience. Message @BotFather and use: Command Purpose /setdescription The "What can this bot do?" text shown before a user starts chatting /setabouttext Short text on the bot's profile page /setuserpic Upload an avatar for your bot /setcommands Define the command menu (the /\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_6uJg0pcdv73crdOdSZVgdXRC", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "assistant", "content": "", "reasoning": "**Setting up SQLite schema**\n\nI'm realizing that I need SQLite for my task. First things first: I need to define the schema to organize my data properly. It's crucial to get the schema right before diving into any database operations. I should think about what tables I need, their columns, and how they'll relate to each other. Starting with a clear plan will help me avoid confusion later on! Alright, let's get this setup going!", "finish_reason": "tool_calls", "reasoning_content": "**Setting up SQLite schema**\n\nI'm realizing that I need SQLite for my task. First things first: I need to define the schema to organize my data properly. It's crucial to get the schema right before diving into any database operations. I should think about what tables I need, their columns, and how they'll relate to each other. Starting with a clear plan will help me avoid confusion later on! Alright, let's get this setup going!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqBX0Z83O8RyhZxtB5yyZw0_1Po_jGpRAgMJlCG95YcQKua65srd-HTpGHAwkVS77WF-k3ChNSlPFvyzfLolOHcCtxQNBdCOYyZ9iO0EbLKb14J-0IFmc7cKmMwj6Gx2rv-dB0xKaXV45_x4P1qLjK5X9KKxLkRD4bD77YTXqYoamYIrTFVxhNA5fCWd35TXGUBXgsClSLBtT6LlLKPS9ecvte6oHLFeFNaEkvmBKXNRP0QfhIXZAx32FOFcWo21KQULEqPYzpnP7ma1dlY4WwQKOs1mnzzbNR8pbYvhrP-1kPc3UUv0GvU5ZDtW88w0AdnaAbXE5378zPp6Gy4AEq7pcKgM8wp53UhelZzGxlJEN-NgjuBVGrW9wlnFxYUNRuUy12dGu67F--4EHH1VwS0dIxm52v-jqk3NG4u83zP1Typx1U4-2MBY-D9VSFBK0l_LlVA5bQ_2CYc6Rt1OB5R01wPt1SZVFN_o4zRtUYE_L2eR5GuMtvpHH9LrXtbauSaznw5XWeK_zzpDD7Dasp67Xo5xPvpjpJLVRBcOJWVpSqdjhcbsSvkkUVMDVkUzhZjSdVYiinyqzXNrq8nf4YnEPrbQfLanu3yP5dzSe7VeG8GiMPKaFq2DjJ0edYbKMIAoG0tp0rsAsMk70qBqoQdYS29ADp0j7h64VltojFeBit6OSaPH_awnapuXTzRiw6ZNNV-rY5IrTVWPTuNHmqiR6gjy6rJHnVL2NNduEwxJQciuktfJOAwZ_e1xAgguC-eOapo2bM0-VSxOMho2m4U6FRyWH5yUInKiA7GI3n1NJQl57pCc4-ban0ZYzj2u9fyblnnp6mnGRtVp6juNhpvVc5ZJ20yvGAdqFI-5MyhKia2ZKoPJwsUZKcIBuUWjfndKjGMmgdUv2tlmySX36ipjkEI07DYnVvDgtqPdhXG0oUmvHZOhEeRZL8PaPPQzvFPOcE", "id": "rs_0cb9fa950ca2a82c016a057d1721948191b9201d79c4a6ea64", "summary": [{"type": "summary_text", "text": "**Setting up SQLite schema**\n\nI'm realizing that I need SQLite for my task. First things first: I need to define the schema to organize my data properly. It's crucial to get the schema right before diving into any database operations. I should think about what tables I need, their columns, and how they'll relate to each other. Starting with a clear plan will help me avoid confusion later on! Alright, let's get this setup going!"}]}], "tool_calls": [{"id": "call_MIWo01EDID5tov6qWmmrJPHx", "call_id": "call_MIWo01EDID5tov6qWmmrJPHx", "response_item_id": "fc_0cb9fa950ca2a82c016a057d191a3c81918ffa41cf10dbe52c", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nimport sqlite3, pathlib\\np=pathlib.Path.home()/'.hermes/state.db'\\ncon=sqlite3.connect(p)\\nfor row in con.execute(\\\"select name, sql from sqlite_master where type='table'\\\"):\\n print('\\\\nTABLE',row[0]); print(row[1][:1000])\\nPY\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}], "timestamp": "2026-05-14T09:45:30.357460"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"TABLE schema_version\\nCREATE TABLE schema_version (\\n version INTEGER NOT NULL\\n)\\n\\nTABLE sessions\\nCREATE TABLE sessions (\\n id TEXT PRIMARY KEY,\\n source TEXT NOT NULL,\\n user_id TEXT,\\n model TEXT,\\n model_config TEXT,\\n system_prompt TEXT,\\n parent_session_id TEXT,\\n started_at REAL NOT NULL,\\n ended_at REAL,\\n end_reason TEXT,\\n message_count INTEGER DEFAULT 0,\\n tool_call_count INTEGER DEFAULT 0,\\n input_tokens INTEGER DEFAULT 0,\\n output_tokens INTEGER DEFAULT 0,\\n cache_read_tokens INTEGER DEFAULT 0,\\n cache_write_tokens INTEGER DEFAULT 0,\\n reasoning_tokens INTEGER DEFAULT 0,\\n billing_provider TEXT,\\n billing_base_url TEXT,\\n billing_mode TEXT,\\n estimated_cost_usd REAL,\\n actual_cost_usd REAL,\\n cost_status TEXT,\\n cost_source TEXT,\\n pricing_version TEXT,\\n title TEXT,\\n api_call_count INTEGER DEFAULT 0, \\\"handoff_state\\\" TEXT, \\\"handoff_platform\\\" TEXT, \\\"handoff_error\\\" TEXT,\\n FOREIGN KEY (parent_session_id) REFERENCES sessions(id)\\n)\\n\\nTABLE messages\\nCREATE TABLE messages (\\n id INTEGER PRIMARY KEY AUTOINCREMENT,\\n session_id TEXT NOT NULL REFERENCES sessions(id),\\n role TEXT NOT NULL,\\n content TEXT,\\n tool_call_id TEXT,\\n tool_calls TEXT,\\n tool_name TEXT,\\n timestamp REAL NOT NULL,\\n token_count INTEGER,\\n finish_reason TEXT,\\n reasoning TEXT,\\n reasoning_content TEXT,\\n reasoning_details TEXT,\\n codex_reasoning_items TEXT,\\n codex_message_items TEXT\\n)\\n\\nTABLE sqlite_sequence\\nCREATE TABLE sqlite_sequence(name,seq)\\n\\nTABLE state_meta\\nCREATE TABLE state_meta (\\n key TEXT PRIMARY KEY,\\n value TEXT\\n)\\n\\nTABLE messages_fts\\nCREATE VIRTUAL TABLE messages_fts USING fts5(\\n content\\n)\\n\\nTABLE messages_fts_data\\nCREATE TABLE 'messages_fts_data'(id INTEGER PRIMARY KEY, block BLOB)\\n\\nTABLE messages_fts_idx\\nCREATE TABLE 'messages_fts_idx'(segid, term, pgno, PRIMARY KEY(segid, term)) WITHOUT ROWID\\n\\nTABLE messages_fts_content\\nCREATE TABLE 'messages_fts_content'(id INTEGER PRIMARY KEY, c0)\\n\\nTABLE messages_fts_docsize\\nCREATE TABLE 'messages_fts_docsize'(id INTEGER PRIMARY KEY, sz BLOB)\\n\\nTABLE messages_fts_config\\nCREATE TABLE 'messages_fts_config'(k PRIMARY KEY, v) WITHOUT ROWID\\n\\nTABLE messages_fts_trigram\\nCREATE VIRTUAL TABLE messages_fts_trigram USING fts5(\\n content,\\n tokenize='trigram'\\n)\\n\\nTABLE messages_fts_trigram_data\\nCREATE TABLE 'messages_fts_trigram_data'(id INTEGER PRIMARY KEY, block BLOB)\\n\\nTABLE messages_fts_trigram_idx\\nCREATE TABLE 'messages_fts_trigram_idx'(segid, term, pgno, PRIMARY KEY(segid, term)) WITHOUT ROWID\\n\\nTABLE messages_fts_trigram_content\\nCREATE TABLE 'messages_fts_trigram_content'(id INTEGER PRIMARY KEY, c0)\\n\\nTABLE messages_fts_trigram_docsize\\nCREATE TABLE 'messages_fts_trigram_docsize'(id INTEGER PRIMARY KEY, sz BLOB)\\n\\nTABLE messages_fts_trigram_config\\nCREATE TABLE 'messages_fts_trigram_config'(k PRIMARY KEY, v) WITHOUT ROWID\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_MIWo01EDID5tov6qWmmrJPHx", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "assistant", "content": "", "reasoning": "**Calculating daily stats**\n\nI need to gather daily statistics. I think I'll use an SQL query to group by date. It seems like total tokens could be calculated as input, output, and potential cache reads combined. I'm noticing that the total tokens are much higher than just input plus output, which probably means cache reads are included. So I need to clarify the numbers, especially since total tokens are around 112 million while input is only 6.4 million and output is about 0.56 million. I need to create that query!", "finish_reason": "tool_calls", "reasoning_content": "**Calculating daily stats**\n\nI need to gather daily statistics. I think I'll use an SQL query to group by date. It seems like total tokens could be calculated as input, output, and potential cache reads combined. I'm noticing that the total tokens are much higher than just input plus output, which probably means cache reads are included. So I need to clarify the numbers, especially since total tokens are around 112 million while input is only 6.4 million and output is about 0.56 million. I need to create that query!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqBX0fqGDq98HjSQ-SArv1Sj_gqbRSZmAspQfvxSGIFBpDiO636-3iA4blhJQah-WemJrmYByWCrx0qsNDIKRoMKVslEVsGy8Mvgb5pTA46HWBvX1ayRA8vpCtjv0ZojTymxEpxG6HB-LvG-cdl_6LrFD-ZqKk3oKChdBxt5iUpM6XRAGwAzd0aYA3yYTpgYUOvspGvCRDfXAR8MxQPNYF5nzxnoXKiF0tLWAb8ALJURArPf5tXHiREU-_zjYjaOnnL5Ac0_II1Oma5Kv3PGRFnljbYDA8In-1UTx5j4HFiHGMdO9IACKc31E5XZYu60QHLPfgpVIzHI3GCvderSXrijQNPIv32aMVYMBe0fzknt0lDXgb9T8v779LEqqJVeZUvTL0uS2QPp27CIww41j-3dudYb-MiRIeyM4yjj1x16VF4psbDaUyJmlFTBRHJM8r4-SC1oNa9cNLwn2AnTc_A0TwQV223MxTFEqC_SdlcDYmj-f5r_Zo_i4giC9at3nYYp2l03Z8ETVpmtPXV7lSc57TQfFwSV_-0sO7A1zs63e_oTQR2CBSTn4iBkJznp_PHp1Hk6AhAB2RnBP1p2LuczhGsp27SMOWYCQCNRhifEoQDQKm6hOw2bhhyj1bT9C8fjv4xzE9ooqG4QyvlXYKmuryyKl-oGQkkZa2pHM01szljjLw2pnVPHxbfLXVvYpdPMyIZGSG-AGaANZ811GsaRRh6gz2_DoueL3eBlhOSnqjUSffanW8V6ejZoziOE9vs6EeePWYNIKeEruJLt03E0HpMph1BTLOIiURZckN3-dZzoiOuEwNqlT0aqpn6iOZZ4wbodmgX3VyZAYij61rmjhI7KOZBOjLlDJilnQa1TAIJR0SNnpZgmBlrizP6AXBMlca_p7LjF3W-vl-UGotZcU7j5ae2XABSTfRHzBQ-OdraClpmNtAs3ab3pXm2sdWPDodhWaFCKnHRae37lSIcZtdUJ5_MRnZa9zukp6OYksoxVGTSpQpDcK9_SKTqy2rKRQck4XAJoVraXJo2TBsWPcmAtUL_dkCijrOY3iBY29nYzwDHCjsye3Eb6ASXn0rEuLi3xO33M16TAfkcAybxcbGAERjVmENr76nWbCYC0QVfT3TzMFzz8FmwmQCURr-QCiPKTF3X2uXvCQmW8fYF-lx6qnNpbjYQ5igy_sN1dkGTIedHhsU_brUh5Bha3yuN0djPBw4OFAzmiUd2qsITJb0lw==", "id": "rs_0e80286be51dc7ec016a057d1c0b9c819193603c6bc8543bc4", "summary": [{"type": "summary_text", "text": "**Calculating daily stats**\n\nI need to gather daily statistics. I think I'll use an SQL query to group by date. It seems like total tokens could be calculated as input, output, and potential cache reads combined. I'm noticing that the total tokens are much higher than just input plus output, which probably means cache reads are included. So I need to clarify the numbers, especially since total tokens are around 112 million while input is only 6.4 million and output is about 0.56 million. I need to create that query!"}]}], "tool_calls": [{"id": "call_ZXr4R0E7Ox1YzlUGHSKqHBKP", "call_id": "call_ZXr4R0E7Ox1YzlUGHSKqHBKP", "response_item_id": "fc_0e80286be51dc7ec016a057d1fb4188191ad2033fbbb2e1646", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nimport sqlite3, datetime, pathlib\\ncon=sqlite3.connect(pathlib.Path.home()/'.hermes/state.db')\\ncon.row_factory=sqlite3.Row\\nprint('Daily usage (local timezone naive from unix):')\\nq='''select date(started_at,'unixepoch','localtime') d, count(*) sessions, sum(message_count) msgs, sum(tool_call_count) tools,\\n sum(input_tokens) inp, sum(output_tokens) out, sum(cache_read_tokens) cr, sum(cache_write_tokens) cw, sum(reasoning_tokens) rt,\\n sum(input_tokens+output_tokens+cache_read_tokens+cache_write_tokens+reasoning_tokens) total\\n from sessions group by d order by d'''\\nfor r in con.execute(q):\\n print(f\\\"{r['d']} sessions={r['sessions']:2d} msgs={r['msgs'] or 0:4d} tools={r['tools'] or 0:4d} total={r['total'] or 0:10,d} input={r['inp'] or 0:9,d} output={r['out'] or 0:8,d} cache_read={r['cr'] or 0:10,d} cache_write={r['cw'] or 0:8,d} reasoning={r['rt'] or 0:8,d}\\\")\\nprint('\\\\nTop 10 sessions by total tokens:')\\nq2='''select id, source, model, datetime(started_at,'unixepoch','localtime') st, message_count msgs, tool_call_count tools,\\n (input_tokens+output_tokens+cache_read_tokens+cache_write_tokens+reasoning_tokens) total,\\n input_tokens, output_tokens, cache_read_tokens, cache_write_tokens, reasoning_tokens, title\\n from sessions order by total desc limit 10'''\\nfor r in con.execute(q2):\\n print(f\\\"{r['st']} {r['source']} {r['model']} total={r['total']:,} inp={r['input_tokens']:,} out={r['output_tokens']:,} cacheR={r['cache_read_tokens']:,} msgs={r['msgs']} tools={r['tools']} title={r['title']}\\\")\\nPY\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}], "timestamp": "2026-05-14T09:45:30.357460"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"Daily usage (local timezone naive from unix):\\n2026-05-07 sessions=11 msgs=1443 tools= 648 total=15,692,296 input=1,057,282 output= 36,703 cache_read=14,598,311 cache_write= 0 reasoning= 0\\n2026-05-08 sessions=11 msgs=1354 tools= 616 total=18,919,837 input=1,046,209 output= 100,600 cache_read=17,773,028 cache_write= 0 reasoning= 0\\n2026-05-09 sessions=19 msgs= 564 tools= 254 total= 8,997,319 input= 606,389 output= 72,143 cache_read= 8,318,787 cache_write= 0 reasoning= 0\\n2026-05-10 sessions=21 msgs= 735 tools= 322 total=12,466,792 input=1,006,459 output= 68,670 cache_read=11,391,663 cache_write= 0 reasoning= 0\\n2026-05-11 sessions= 8 msgs= 218 tools= 88 total= 4,044,725 input= 182,091 output= 21,140 cache_read= 3,841,494 cache_write= 0 reasoning= 0\\n2026-05-12 sessions=17 msgs=3039 tools=1437 total=46,614,681 input=1,977,376 output= 228,505 cache_read=44,387,177 cache_write= 0 reasoning= 21,623\\n2026-05-13 sessions= 5 msgs= 181 tools= 82 total= 5,649,155 input= 481,768 output= 29,530 cache_read= 5,131,776 cache_write= 0 reasoning= 6,081\\n2026-05-14 sessions= 2 msgs= 4 tools= 1 total= 197,233 input= 56,025 output= 3,511 cache_read= 137,216 cache_write= 0 reasoning= 481\\n\\nTop 10 sessions by total tokens:\\n2026-05-12 11:25:53 telegram qwen-3.6-agent total=7,641,194 inp=395,374 out=54,499 cacheR=7,187,236 msgs=147 tools=70 title=Status der Dokumentenprüfung\\n2026-05-12 20:40:59 telegram gpt-5.5 total=6,050,514 inp=161,931 out=19,843 cacheR=5,867,008 msgs=339 tools=160 title=Status der Dokumentenprüfung #7\\n2026-05-12 22:59:13 telegram gpt-5.5 total=5,193,158 inp=128,089 out=11,833 cacheR=5,051,392 msgs=346 tools=161 title=Status der Dokumentenprüfung #9\\n2026-05-12 21:13:21 telegram gpt-5.5 total=5,045,597 inp=231,504 out=18,706 cacheR=4,791,296 msgs=329 tools=153 title=Status der Dokumentenprüfung #8\\n2026-05-13 07:17:51 telegram gpt-5.5 total=5,021,526 inp=360,299 out=21,540 cacheR=4,635,136 msgs=126 tools=58 title=None\\n2026-05-07 21:18:06 telegram qwen-3.6-agent total=4,416,923 inp=53,172 out=7,020 cacheR=4,356,731 msgs=216 tools=95 title=Greeting and Offering Assistance #5\\n2026-05-12 17:18:43 telegram gpt-5.5 total=4,254,776 inp=137,606 out=17,236 cacheR=4,097,536 msgs=305 tools=149 title=Status der Dokumentenprüfung #3\\n2026-05-11 06:13:59 telegram qwen-3.6-agent total=3,540,931 inp=101,985 out=14,937 cacheR=3,424,009 msgs=137 tools=56 title=Tagebucheintragung für Durchfall und Verdachtsmomente\\n2026-05-12 16:41:49 telegram gpt-5.5 total=3,497,182 inp=162,249 out=21,893 cacheR=3,311,104 msgs=219 tools=105 title=Status der Dokumentenprüfung #2\\n2026-05-09 09:40:24 telegram qwen-3.6-agent total=3,319,901 inp=131,749 out=25,570 cacheR=3,162,582 msgs=117 tools=55 title=PARA Obsidian Vault Setup for Health\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_ZXr4R0E7Ox1YzlUGHSKqHBKP", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "assistant", "content": "", "reasoning": "**Investigating context management**\n\nI'm considering whether topics or multiple channels could reduce context in communication. I want to check if Telegram DM topic sessions are enabled and what the documentation and configuration say. Inspecting the gateway settings might help, so I'll search through the code for more details. This feels a bit technical, but I think getting into the specifics will help me understand better! Let's see what I can find!", "finish_reason": "tool_calls", "reasoning_content": "**Investigating context management**\n\nI'm considering whether topics or multiple channels could reduce context in communication. I want to check if Telegram DM topic sessions are enabled and what the documentation and configuration say. Inspecting the gateway settings might help, so I'll search through the code for more details. This feels a bit technical, but I think getting into the specifics will help me understand better! Let's see what I can find!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqBX0uw8LfJoK1FsjtFqoqNWoV1HxusfTn2uRJzmP4V9-QfzOW1EbWxFwEq-yWSZCNbm8s4F6DxM-SUkRZd_GnUpxsYXp8SInCJOioF5HXaYGwKN8-ZSLK-jtp_nt_pkM2S4FLpRPV9t3yXQFOT10LWvrX-1zISWQbx0IB5_Cu6A71AKN3fAz4xD6x5gIYeK2lzlZ8MKNm63SrPefjJXHMYyJCwtmv9v-mMz4tWTfYNLyvxbReNFCBSfQIz62dckiaVADegZYjXkHVb642M8ghN6JHSRJY_nyrUl2NTxoiSBxABGO5P7h20v9DUuHT4f_A6XwUoQKFoL33PvaVXr-gNyW6a-K0LlemPlLsxwyxhh41nh69rgWQ9faxEB6CP1vd_Qporagv3ll4zkb1dyGIRMTPNGoZETPGC-6KUN_VLh4ApQ8JUK-RuR9NV4UhZQTQy1udgkjCJ0QaAAwqhHxoqBRdaOa2GP3hHXyqnctuESo_KvD62SxavAEjj6AgqLJqQ48OFz9c7T4wlEjAE7IAbjuCRymt8lH2o1t8rjvMkldvokYIz7kI-2KeHIK6nWbGOqTBbNY8G74ACesgbKyTB9Re7VrCG6Bc9DJ78cRYh5mnXiJgGN2KEDkZeADN9fXRR7NyqAXnA_liBtH3O2OMMJNRJQTcUc2ePrsMbyXi451HFLuWRieoHqE6u5UIAz_1YxeeOaAQn26Qx1qFU_dAIzsjmDLRu6yFk5w21Bf2BlJQEYg3outtf71Xvjx-Xd4UMZfJ2cINYUE9d5TG9rLJB1cfYJuS0ZbhhDbtxuQJZ-x-V69W0p1LUzTbZsVs7KAOY7F0Agl8J7iRn3NbAcECx4f8SeBlIXH-ClH5P9NDm3NmEMRDCnZ64-itZRfOg7QdkJFSLwZ_H7uuGrkEGh89oojCjJRgAr_T8UGYqs0D1zmvyqy8NyS-EEhvw0P3DvBuNYRT8xWWN9QZlLIqFRl6AxbaqtYeY-sxNqUAFsDHJSxH5AzT1w1f-LmXArlGZXUgP3vLcQUSm0hTSJB2tNXfHRVarOEXO6JLOh9TbAobpsL0JHFuwqz8QWRP94Ia3uN1RAegDGdjDDPdAjp7F7OVp_6qTDqJOh2vJ6dITbjAJ4lLa9CcJV9zJSW91VZ4hKqEcZsh", "id": "rs_058a255fade1edf6016a057d2ac19c8191856e71454f8b854b", "summary": [{"type": "summary_text", "text": "**Investigating context management**\n\nI'm considering whether topics or multiple channels could reduce context in communication. I want to check if Telegram DM topic sessions are enabled and what the documentation and configuration say. Inspecting the gateway settings might help, so I'll search through the code for more details. This feels a bit technical, but I think getting into the specifics will help me understand better! Let's see what I can find!"}]}], "tool_calls": [{"id": "call_8uEIpUtpPN3vfZ9csM7ojKWw", "call_id": "call_8uEIpUtpPN3vfZ9csM7ojKWw", "response_item_id": "fc_058a255fade1edf6016a057d2fb1dc8191b8228b3961ce6bed", "type": "function", "function": {"name": "search_files", "arguments": "{\"pattern\":\"topic_sessions|topic|thread_id|session_key|DM topic\",\"path\":\"/home/agent/.hermes/hermes-agent/gateway\",\"file_glob\":\"*.py\",\"limit\":30,\"context\":2}"}}, {"id": "call_hKZk6cJm75EZQFGVZAMqGSH9", "call_id": "call_hKZk6cJm75EZQFGVZAMqGSH9", "response_item_id": "fc_058a255fade1edf6016a057d2fb1ec8191a3b001ee3d18bc7d", "type": "function", "function": {"name": "search_files", "arguments": "{\"pattern\":\"hygiene_hard_message_limit|protect_last_n|threshold|target_ratio\",\"path\":\"/home/agent/.hermes/hermes-agent\",\"file_glob\":\"*.py\",\"limit\":30,\"context\":2}"}}, {"id": "call_Ja8LVtVTymM7ddv0TmZbzFKC", "call_id": "call_Ja8LVtVTymM7ddv0TmZbzFKC", "response_item_id": 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efficiently across long conversations.\\n 5|\\n 6|Source files: `agent/context_engine.py` (ABC), `agent/context_compressor.py` (default engine),\\n 7|`agent/prompt_caching.py`, `gateway/run.py` (session hygiene), `run_agent.py` (search for `_compress_context`)\\n 8|\\n 9|\\n 10|## Pluggable Context Engine\\n 11|\\n 12|Context management is built on the `ContextEngine` ABC (`agent/context_engine.py`). The built-in `ContextCompressor` is the default implementation, but plugins can replace it with alternative engines (e.g., Lossless Context Management).\\n 13|\\n 14|```yaml\\n 15|context:\\n 16| engine: \\\"compressor\\\" # default — built-in lossy summarization\\n 17| engine: \\\"lcm\\\" # example — plugin providing lossless context\\n 18|```\\n 19|\\n 20|The engine is responsible for:\\n 21|- Deciding when compaction should fire (`should_compress()`)\\n 22|- Performing compaction (`compress()`)\\n 23|- Optionally exposing tools the agent can call (e.g., `lcm_grep`)\\n 24|- Tracking token usage from API responses\\n 25|\\n 26|Selection is config-driven via `context.engine` in `config.yaml`. The resolution order:\\n 27|1. Check `plugins/context_engine//` directory\\n 28|2. Check general plugin system (`register_context_engine()`)\\n 29|3. Fall back to built-in `ContextCompressor`\\n 30|\\n 31|Plugin engines are **never auto-activated** — the user must explicitly set `context.engine` to the plugin's name. The default `\\\"compressor\\\"` always uses the built-in.\\n 32|\\n 33|Configure via `hermes plugins` → Provider Plugins → Context Engine, or edit `config.yaml` directly.\\n 34|\\n 35|For building a context engine plugin, see [Context Engine Plugins](/docs/developer-guide/context-engine-plugin).\\n 36|\\n 37|## Dual Compression System\\n 38|\\n 39|Hermes has two separate compression layers that operate independently:\\n 40|\\n 41|```\\n 42| ┌──────────────────────────┐\\n 43| Incoming message │ Gateway Session Hygiene │ Fires at 85% of context\\n 44| ─────────────────► │ (pre-agent, rough est.) │ Safety net for large sessions\\n 45| └─────────────┬────────────┘\\n 46| │\\n 47| ▼\\n 48| ┌──────────────────────────┐\\n 49| │ Agent ContextCompressor │ Fires at 50% of context (default)\\n 50| │ (in-loop, real tokens) │ Normal context management\\n 51| └──────────────────────────┘\\n 52|```\\n 53|\\n 54|### 1. Gateway Session Hygiene (85% threshold)\\n 55|\\n 56|Located in `gateway/run.py` (search for `Session hygiene: auto-compress`). This is a **safety net** that\\n 57|runs before the agent processes a message. It prevents API failures when sessions\\n 58|grow too large between turns (e.g., overnight accumulation in Telegram/Discord).\\n 59|\\n 60|- **Threshold**: Fixed at 85% of model context length\\n 61|- **Token source**: Prefers actual API-reported tokens from last turn; falls back\\n 62| to rough character-based estimate (`estimate_messages_tokens_rough`)\\n 63|- **Fires**: Only when `len(history) >= 4` and compression is enabled\\n 64|- **Purpose**: Catch sessions that escaped the agent's own compressor\\n 65|\\n 66|The gateway hygiene threshold is intentionally higher than the agent's compressor.\\n 67|Setting it at 50% (same as the agent) caused premature compression on every turn\\n 68|in long gateway sessions.\\n 69|\\n 70|### 2. Agent ContextCompressor (50% threshold, configurable)\\n 71|\\n 72|Located in `agent/context_compressor.py`. This is the **primary compression\\n 73|system** that runs inside the agent's tool loop with access to accurate,\\n 74|API-reported token counts.\\n 75|\\n 76|\\n 77|## Configuration\\n 78|\\n 79|All compression settings are read from `config.yaml` under the `compression` key:\\n 80|\\n 81|```yaml\\n 82|compression:\\n 83| enabled: true # Enable/disable compression (default: true)\\n 84| threshold: 0.50 # Fraction of context window (default: 0.50 = 50%)\\n 85| target_ratio: 0.20 # How much of threshold to keep as tail (default: 0.20)\\n 86| protect_last_n: 20 # Minimum protected tail messages (default: 20)\\n 87|\\n 88|# Summarization model/provider configured under auxiliary:\\n 89|auxiliary:\\n 90| compression:\\n 91| model: null # Override model for summaries (default: auto-detect)\\n 92| provider: auto # Provider: \\\"auto\\\", \\\"openrouter\\\", \\\"nous\\\", \\\"main\\\", etc.\\n 93| base_url: null # Custom OpenAI-compatible endpoint\\n 94|```\\n 95|\\n 96|### Parameter Details\\n 97|\\n 98|| Parameter | Default | Range | Description |\\n 99||-----------|---------|-------|-------------|\\n 100|| `threshold` | `0.50` | 0.0-1.0 | Compression triggers when prompt tokens ≥ `threshold × context_length` |\\n 101|| `target_ratio` | `0.20` | 0.10-0.80 | Controls tail protection token budget: `threshold_tokens × target_ratio` |\\n 102|| `protect_last_n` | `20` | ≥1 | Minimum number of recent messages always preserved |\\n 103|| `protect_first_n` | `3` | (hardcoded) | System prompt + first exchange always preserved |\\n 104|\\n 105|### Computed Values (for a 200K context model at defaults)\\n 106|\\n 107|```\\n 108|context_length = 200,000\\n 109|threshold_tokens = 200,000 × 0.50 = 100,000\\n 110|tail_token_budget = 100,000 × 0.20 = 20,000\\n 111|max_summary_tokens = min(200,000 × 0.05, 12,000) = 10,000\\n 112|```\\n 113|\\n 114|\\n 115|## Compression Algorithm\\n 116|\\n 117|The `ContextCompressor.compress()` method follows a 4-phase algorithm:\\n 118|\\n 119|### Phase 1: Prune Old Tool Results (cheap, no LLM call)\\n 120|\\n 121|Old tool results (>200 chars) outside the protected tail are replaced with:\\n 122|```\\n 123|[Old tool output cleared to save context space]\\n 124|```\\n 125|\\n 126|This is a cheap pre-pass that saves significant tokens from verbose tool\\n 127|outputs (file contents, terminal output, search results).\\n 128|\\n 129|### Phase 2: Determine Boundaries\\n 130|\\n 131|```\\n 132|┌─────────────────────────────────────────────────────────────┐\\n 133|│ Message list │\\n 134|│ │\\n 135|│ [0..2] ← protect_first_n (system + first exchange) │\\n 136|│ [3..N] ← middle turns → SUMMARIZED │\\n 137|│ [N..end] ← tail (by token budget OR protect_last_n) │\\n 138|│ │\\n 139|└─────────────────────────────────────────────────────────────┘\\n 140|```\\n 141|\\n 142|Tail protection is **token-budget based**: walks backward from the end,\\n 143|accumulating tokens until the budget is exhausted. Falls back to the fixed\\n 144|`protect_last_n` count if the budget would protect fewer messages.\\n 145|\\n 146|Boundaries are aligned to avoid splitting tool_call/tool_result groups.\\n 147|The `_align_boundary_backward()` method walks past consecutive tool results\\n 148|to find the parent assistant message, keeping groups intact.\\n 149|\\n 150|### Phase 3: Generate Structured Summary\\n 151|\\n 152|:::warning Summary model context length\\n 153|The summary model must have a context window **at least as large** as the main agent model's. The entire middle section is sent to the summary model in a single `call_llm(task=\\\"compression\\\")` call. If the summary model's context is smaller, the API returns a context-length error — `_generate_summary()` catches it, logs a warning, and returns `None`. The compressor then drops the middle turns **without a summary**, silently losing conversation context. This is the most common cause of degraded compaction quality.\\n 154|:::\\n 155|\\n 156|The middle turns are summarized using the auxiliary LLM with a structured\\n 157|template:\\n 158|\\n 159|```\\n 160|## Goal\\n 161|[What the user is trying to accomplish]\\n 162|\\n 163|## Constraints & Preferences\\n 164|[User preferences, coding style, constraints, important decisions]\\n 165|\\n 166|## Progress\\n 167|### Done\\n 168|[Completed work — specific file paths, commands run, results]\\n 169|### In Progress\\n 170|[Work currently underway]\\n 171|### Blocked\\n 172|[Any blockers or issues encountered]\\n 173|\\n 174|## Key Decisions\\n 175|[Important technical decisions and why]\\n 176|\\n 177|## Relevant Files\\n 178|[Files read, modified, or created — with brief note on each]\\n 179|\\n 180|## Next Steps\\n 181|[What needs to happen next]\\n 182|\\n 183|## Critical Context\\n 184|[Specific values, error messages, configuration details]\\n 185|```\\n 186|\\n 187|Summary budget scales with the amount of content being compressed:\\n 188|- Formula: `content_tokens × 0.20` (the `_SUMMARY_RATIO` constant)\\n 189|- Minimum: 2,000 tokens\\n 190|- Maximum: `min(context_length × 0.05, 12,000)` tokens\\n 191|\\n 192|### Phase 4: Assemble Compressed Messages\\n 193|\\n 194|The compressed message list is:\\n 195|1. Head messages (with a note appended to system prompt on first compression)\\n 196|2. Summary message (role chosen to avoid consecutive same-role violations)\\n 197|3. Tail messages (unmodified)\\n 198|\\n 199|Orphaned tool_call/tool_result pairs are cleaned up by `_sanitize_tool_pairs()`:\\n 200|- Tool results referencing removed calls → removed\\n 201|- Tool calls whose results were removed → stub result injected\\n 202|\\n 203|### Iterative Re-compression\\n 204|\\n 205|On subsequent compressions, the previous summary is passed to the LLM with\\n 206|instructions to **update** it rather than summarize from scratch. This preserves\\n 207|information across multiple compactions — items move from \\\"In Progress\\\" to \\\"Done\\\",\\n 208|new progress is added, and obsolete information is removed.\\n 209|\\n 210|The `_previous_summary` field on the compressor instance stores the last summary\\n 211|text for this purpose.\\n 212|\\n 213|\\n 214|## Before/After Example\\n 215|\\n 216|### Before Compression (45 messages, ~95K tokens)\\n 217|\\n 218|```\\n 219|[0] system: \\\"You are a helpful assistant...\\\" (system prompt)\\n 220|[1] user: \\\"Help me set up a FastAPI project\\\"\\n 221|\", \"total_lines\": 348, \"file_size\": 14496, \"truncated\": true, \"hint\": \"Use offset=221 to continue reading (showing 1-220 of 348 lines)\", \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_oC1GUbOd7e4SV3F1GkQLmWs0", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_C5OzrVEOeQNqq4TKoi2QStv0", "call_id": "call_C5OzrVEOeQNqq4TKoi2QStv0", "response_item_id": "fc_04d2d0fb523239f1016a057d42cfc881919818b2347033b907", "type": "function", "function": {"name": "read_file", "arguments": "{\"limit\":130,\"offset\":221,\"path\":\"/home/agent/.hermes/hermes-agent/website/docs/developer-guide/context-compression-and-caching.md\"}"}}], "timestamp": "2026-05-14T09:45:30.357460"} {"role": "tool", "name": "read_file", "content": "{\"content\": \" 221|[2] assistant: terminal: mkdir project \\n 222|[3] tool: \\\"directory created\\\"\\n 223|[4] assistant: write_file: main.py \\n 224|[5] tool: \\\"file written (2.3KB)\\\"\\n 225| ... 30 more turns of file editing, testing, debugging ...\\n 226|[38] assistant: terminal: pytest \\n 227|[39] tool: \\\"8 passed, 2 failed\\\\n...\\\" (5KB output)\\n 228|[40] user: \\\"Fix the failing tests\\\"\\n 229|[41] assistant: read_file: tests/test_api.py \\n 230|[42] tool: \\\"import pytest\\\\n...\\\" (3KB)\\n 231|[43] assistant: \\\"I see the issue with the test fixtures...\\\"\\n 232|[44] user: \\\"Great, also add error handling\\\"\\n 233|```\\n 234|\\n 235|### After Compression (25 messages, ~45K tokens)\\n 236|\\n 237|```\\n 238|[0] system: \\\"You are a helpful assistant...\\n 239| [Note: Some earlier conversation turns have been compacted...]\\\"\\n 240|[1] user: \\\"Help me set up a FastAPI project\\\"\\n 241|[2] assistant: \\\"[CONTEXT COMPACTION] Earlier turns were compacted...\\n 242|\\n 243| ## Goal\\n 244| Set up a FastAPI project with tests and error handling\\n 245|\\n 246| ## Progress\\n 247| ### Done\\n 248| - Created project structure: main.py, tests/, requirements.txt\\n 249| - Implemented 5 API endpoints in main.py\\n 250| - Wrote 10 test cases in tests/test_api.py\\n 251| - 8/10 tests passing\\n 252|\\n 253| ### In Progress\\n 254| - Fixing 2 failing tests (test_create_user, test_delete_user)\\n 255|\\n 256| ## Relevant Files\\n 257| - main.py — FastAPI app with 5 endpoints\\n 258| - tests/test_api.py — 10 test cases\\n 259| - requirements.txt — fastapi, pytest, httpx\\n 260|\\n 261| ## Next Steps\\n 262| - Fix failing test fixtures\\n 263| - Add error handling\\\"\\n 264|[3] user: \\\"Fix the failing tests\\\"\\n 265|[4] assistant: read_file: tests/test_api.py \\n 266|[5] tool: \\\"import pytest\\\\n...\\\"\\n 267|[6] assistant: \\\"I see the issue with the test fixtures...\\\"\\n 268|[7] user: \\\"Great, also add error handling\\\"\\n 269|```\\n 270|\\n 271|\\n 272|## Prompt Caching (Anthropic)\\n 273|\\n 274|Source: `agent/prompt_caching.py`\\n 275|\\n 276|Reduces input token costs by ~75% on multi-turn conversations by caching the\\n 277|conversation prefix. Uses Anthropic's `cache_control` breakpoints.\\n 278|\\n 279|### Strategy: system_and_3\\n 280|\\n 281|Anthropic allows a maximum of 4 `cache_control` breakpoints per request. Hermes\\n 282|uses the \\\"system_and_3\\\" strategy:\\n 283|\\n 284|```\\n 285|Breakpoint 1: System prompt (stable across all turns)\\n 286|Breakpoint 2: 3rd-to-last non-system message ─┐\\n 287|Breakpoint 3: 2nd-to-last non-system message ├─ Rolling window\\n 288|Breakpoint 4: Last non-system message ─┘\\n 289|```\\n 290|\\n 291|### How It Works\\n 292|\\n 293|`apply_anthropic_cache_control()` deep-copies the messages and injects\\n 294|`cache_control` markers:\\n 295|\\n 296|```python\\n 297|# Cache marker format\\n 298|marker = {\\\"type\\\": \\\"ephemeral\\\"}\\n 299|# Or for 1-hour TTL:\\n 300|marker = {\\\"type\\\": \\\"ephemeral\\\", \\\"ttl\\\": \\\"1h\\\"}\\n 301|```\\n 302|\\n 303|The marker is applied differently based on content type:\\n 304|\\n 305|| Content Type | Where Marker Goes |\\n 306||-------------|-------------------|\\n 307|| String content | Converted to `[{\\\"type\\\": \\\"text\\\", \\\"text\\\": ..., \\\"cache_control\\\": ...}]` |\\n 308|| List content | Added to the last element's dict |\\n 309|| None/empty | Added as `msg[\\\"cache_control\\\"]` |\\n 310|| Tool messages | Added as `msg[\\\"cache_control\\\"]` (native Anthropic only) |\\n 311|\\n 312|### Cache-Aware Design Patterns\\n 313|\\n 314|1. **Stable system prompt**: The system prompt is breakpoint 1 and cached across\\n 315| all turns. Avoid mutating it mid-conversation (compression appends a note\\n 316| only on the first compaction).\\n 317|\\n 318|2. **Message ordering matters**: Cache hits require prefix matching. Adding or\\n 319| removing messages in the middle invalidates the cache for everything after.\\n 320|\\n 321|3. **Compression cache interaction**: After compression, the cache is invalidated\\n 322| for the compressed region but the system prompt cache survives. The rolling\\n 323| 3-message window re-establishes caching within 1-2 turns.\\n 324|\\n 325|4. **TTL selection**: Default is `5m` (5 minutes). Use `1h` for long-running\\n 326| sessions where the user takes breaks between turns.\\n 327|\\n 328|### Enabling Prompt Caching\\n 329|\\n 330|Prompt caching is automatically enabled when:\\n 331|- The model is an Anthropic Claude model (detected by model name)\\n 332|- The provider supports `cache_control` (native Anthropic API or OpenRouter)\\n 333|\\n 334|```yaml\\n 335|# config.yaml — TTL is configurable (must be \\\"5m\\\" or \\\"1h\\\")\\n 336|prompt_caching:\\n 337| cache_ttl: \\\"5m\\\"\\n 338|```\\n 339|\\n 340|The CLI shows caching status at startup:\\n 341|```\\n 342|💾 Prompt caching: ENABLED (Claude via OpenRouter, 5m TTL)\\n 343|```\\n 344|\\n 345|\\n 346|## Context Pressure Warnings\\n 347|\\n 348|Intermediate context-pressure warnings have been removed (see the iteration-budget block in `run_agent.py`, which notes: \\\"No intermediate pressure warnings — they caused models to 'give up' prematurely on complex tasks\\\"). Compression fires when prompt tokens reach the configured `compression.threshold` (default 50%) with no prior warning step; gateway session hygiene fires as the secondary safety net at 85% of the model's context window.\\n 349|\", \"total_lines\": 348, \"file_size\": 14496, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_C5OzrVEOeQNqq4TKoi2QStv0", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "assistant", "content": "", "reasoning": "**Searching for solutions**\n\nI need to find a comprehensive answer, but it seems I might need to check multiple channels. The search code didn’t return any results, possibly due to an issue with gateway/session.py. Should I try using the terminal with rg? The developer suggested using search_files, but that failed. Is the grep pattern not exact? 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After a big project, the results seemed lower, although eight days isn't enough to spot a clear trend. In the last three days, the figures reached 52.8M, especially on the 12th. I might need to calculate specific percentages based on user messages. It seems mandatory to execute code for arithmetic to get precise calculations. Let's do that!", "finish_reason": "tool_calls", "reasoning_content": "**Calculating percentages and trends**\n\nI'm looking at recent data and seeing that the numbers fluctuate quite a bit. After a big project, the results seemed lower, although eight days isn't enough to spot a clear trend. In the last three days, the figures reached 52.8M, especially on the 12th. I might need to calculate specific percentages based on user messages. It seems mandatory to execute code for arithmetic to get precise calculations. Let's do that!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqBX1filyrTPCuJPAQU_ld0DUsFv0Djr_VWVeT9wEZ7VoRl4KhaYuRT2YcVor56TyjAFw7AlWr9U_cOsbz2uqlLn7qDI_wlab5jcBYHxkU5p_JD6IVkfwBi6Pe1ciqjrcS7CiHaXrczwR95VwaT3H26qPA6VN2dFzxoGoSUSv-WRSJvDolTvMGdt7JVD00KkjuKSGlRpn8ER8DWkHnNpAhCQRxRDTMHy-u3S-N6_jfM32AEyO-V29Oj0B7VkmkeTrPgHsHz-1GbYdGciiQSSJ7-N9HAugziN0Kuuwym22HBah6ffF9W78b_QcJ5bFwx664pgx_Wwn4ShSi10_54TknJE16byytr1cSe_bkvDjOMyB-gQKPkx2AZXEMjHHi-5nW5Tyzsn1IruaOwvcqX7jHyI_9cDllVh6I82BkEz-VIzapHjXg_97Emwv96iSwGQNf7dGm7fe7wKzRmkXRq6sMQY_LJsbsYMG3qLBR4l6smpfIRAqIe0jmjJV-tP-uy8SdZ0Ec2GWUiTSoDfoMCnnNMVgfU_4uXBn_NK8VMRC-09SM5erOWRiHM7uoDMv1t53CMS8swo_qFLpIEn_tOqFLQtavQ2BIo1qK8xEwSvj-aix8ZUoX_Lpr11bgOEvWwmKV226RN4MMJ8wzcJ2WuwNpJjf0w_V6gdLBNz_fknt-Met7eJxeju9FMDvh-w_kSFfuqR22vMhB5SbNXuENGJfVE56-vOx4876Tmycj6B7RezabrW8LY2dmhHxN5Rec2Gsvz5KglTI30AT_3PvQ6BngzQN4d5FEsLS8Z5l-fv-5Q7XK7-80yN4R5W0jShZt9fJVVNoJq_nxbqWl1qtEDCrecG6_KEOaWqKP_OLl_GH1IBwUrHUeFe8RVi0-vwatH_bFAz43TMxudIi2gMvkI4D_b1MfoFUA9nesiOB0Th1DvTK7FBYUZfi6MlcL07l1h4mJ30_4Xw7iT0KHRfBTqszN5rGPbthqBYVUT_Bz1egFC_WHLc6ZM2RA0BXBjowZ3vwKFoADOOJoVJVixkplnMoYh42UmVKe7x4YUv8eBv2_0odYfuA2GzDbKJr58ren9hyvNV1hsh24QhQhiWvFu6BfrdwmMlL46_X8FYYTHO3WdSAARCqf7uETo-3r8riqCuKpCae1igwzpmyApaePpl-AgvtLgtUSBfDCCqOHQbeNh515HGlprK-otlKxwslGdVAY2R8zGwHNfXMfPdwDLSSVYGPf3e3FZ_ty-htsq_EUexwVG76yb-mF8r4LvuMjBigVrtWDkFOLEppzKE28609q5rC0QYyGodSx7AU7PFs-rhCRnEDGMIbWHLkj6vGjbzMJj7il1-qVJZ380mSAtk6AdEEXsJXJOEVZNi5nl-JwGcAx4dSB4iptUZ_uEJFYFwUFnycWFqJo7twjiK6NQhGtZRZYzeRR26Ie6_ZTR-R5VN86mwFJC8eJgRSWvcNq0tB6KbP-k0zP2hs6lAauq7AkZfxBEQk0PpdWWivQwgGj7t7ofBBsDPTrlKfLRX6vFLHk5kmBNq9y5r7iaCsDp0b9GG-ol-e8zVWikinuV9Sq20hgZacfvUXw34CC1kNaauIjdJ6cNLQZjhunpI7BgfhsEnDER2seblweEL_o9UvnX0ORze72_p9l_tKq-olFHJ35oUFxar3NmDBigT73FomdnbcpngIixdjylHivOzqzo9tQ2w8hOu8EA4HJ8GnNR5cfwOcScYaptirZIoK0KfGgpPrsTCkOphFnSPt53xBXV8NJWcX4ihLQmXRATi0SXbVoj65-g0U33k8z_up0qEX1gJ0BhazUdu7_zdw-dgkzzhLO1VsA5FvaQ2Rr7nDETcaxt6UhilGm8Y-ZmLIcFuR1toXd-qEkNOOnpO7FBAJjEurLKdjfAK9IVe-fGgd52zyAeBXVMEunqFU9rAscYiBiO3QLrYhTYHXxD4nVdHqOYMgtDxHoAeJ9VhbPc13yyNlv-yP1D2ng8mq0ngFWZQvWWndFnpsrFAMcGD7pQ13phoB-7gQEbw_QL9jtaW9a1r5ipbO510YS0V6seQo4M-S0tDicXumX6Adj6SVEeduictYL1DMvb5CEv3LtQyJ-r1kQXj0i8bjZAisQOoKUW3EBRx_UNwslVxK6Hmp9nc4H_eQH10DeAXvpSIdYhkazF1REjtI6qEnE_iCrLsRImFb1CLMFSjInuGMCzp86t9hvQurc7DHXIl76bNZ3yA81TJHIExagUcW1JzXqr15747kwFASeZqtHlYu5B5zBKSpJruiVX_Omt5nfOjz_h5cY7pI-p-N9fVxCUMiPeitfZclgvCZcO-zyYKWgWDBuwojZCoeeWFL3D4Q9Qh2ROkEwrC67L2NuoTMS0Q6FOK1d-sP47ByNmigwM2DZiTb-6Ygw1XJy7qDYwYLSDMJiEeL94djcU_dbcuLLnU18affP1dj8NIi5JHxD1rdxTF__oOlGKAan75h12XEDBsVW0oIqOk7UtOgEOybe-1HU3ZI0lkAl8VFOxf8XmSPrfzi8Dz4ufuVCVdIvCDzvxlibBEJlDnjTpHV30JqCPDcXV1M5o5rgd-eJtVF3bgLsNBktFAzeGKE2GM2UjwKmukOy46qA5XdgeYkAr8zW_MS8s-run0BqEH7jAhhY9qBf40b_X5N_Xqsq5c-_8KBXp9Rsxyx94MjtKqEVUy-mRJ1XbWGS6K90P8nj23m3r2rCUwuiCM9SNjrw_Bjvfd6SxJI_yznqYEIJ-UgGt-EJcXEuSoFPynIwMm-r3jwTQjKxExZexZnI6pb3dGPZ1EAsuQEPvLS3cOJMNBYiuViG_eeVP2-QpCpnA43SlJRrR05cLQKnT5ftFRiv1C0LXge6KMOfM9DO4C89_QgUjGOo_1fA0JHVaBdbzMHKe0McAQX9ltsqq128HOF14D_9A6qaPI6G5VznbcohRxGYJTNizlA04rBYBbTXM_YfeVPUKdzkDZtaNbsqf4LSF4ETUkq9jD1ozNlu1_ni9SgYi1XjhS_Sv2TQX1dS8TSYbksyCWFgp595SvLVLuwfkCmQ9z3Z4D-TWU-T_Xg44jjXo1qtqWD23bWGPWJJnN72Dh5DLjs8RPwP22vSfhtKYyk_btzZIGKr_2oG87M-4qfmbfVVBTHjPwRDaXWpckcHGM648SSHc_tK9rvsrX506NajHXYVXuRAKZmAx5_MHCzOw4tckBxAT7wGwYP_ViVym5tODqVH8nNtXDCn0l1l_hbAU1slCWC_lEACblfSR03vXc417t0OgaTAYr_G1b8fKwToFqGPREbSHcT_mjvAJVRAeAPBW4t75NevuvwX97Bvy0F85vZgCZDVHyOwiMMwx18TeRciG-bwx7XbluBQZoPhCDL5LbOVK9iylCARL5p49-in-Dl2DHAe0yCjPasFbFxQD4tnMrdGT2IbCXB_3YNCDKOS5LOgLY0Nj9jVJ0fY_CchgVWp8JMfsClMR1jUscNNECq80nXdYcG8FoKqDUN0rKO64G3mhdrXzj9c0IIao7vmRnK0qkvbcZNz-gkxM6oYmC5Q0K8FVnIRIQLRiheT9eDhIaK35TqZelkYs8Sb2kvcCdY43WXtbY8WxbHl9ISYqaNL86eO4hLXNo6n1W0IYqZvSDALKXHDqUB53WEpjNtCDbkEEKG7rEvlGshOTQ-mcdRQSUdWZWuwIiVw71yDdnoIqjwq-U_ZQ-jZ90-klCcreeAcNN-BzrPeS0UB49n3ZRNXQd2xxQCewMtYCXXi5qu1fu3Wq4qtTJZlZHCmUbYHfPOBHAjIypLTAqGBPP22aXrKaWyWyrVJbe8XiQf4qrbW53Di4CYyRV6Y93Z2t1lIkfqapQIsVajB1bhtyvGzDiaEcD-COvx3q_rrO9212qqULG9jCQCdQBP73dUOPj5BEBKvns2QN9gyH_nvLWJ3djUFHkq1UX-WUWE3i2oQSTj5RYoHLq-RPtZt_LfVl6J4t6nzHUcSeFizvz9ooGemwk3hNZUiGFGndW-OSCD5wXg0U7Lw_6aausMz5mFTmUmbXULGISXhwZvuM6gmM6M8PqqPUynuRx6de5qOjC0d48BNw6z7pBq74sF5tzupHUDN0g0o5aWaXT96M7TfJDYMuS4CNOhHlwQ98PYEYWQVHxm1LHJbIGnSra669gO_0i9RgOORrn7wLCwuoGQfdsVE3MacdEB2ityy-lYMRIgnhE4vbtI9viQC1WMqEM57L8hhHFvcd4R3c2MusYECdPYV06RS43sXgM0yEXMJcGRAM5RSFLuBXaKWPcZSp12AJi6rEXg6M4-IZP6mVqkYtbDdAMx_F0fBKnP-OaYejR5fqEbqrAmlKqN32W5jmsdRsM0QYAPHy6x5rQPynoUjikETy2rgUJ6DssXFCtbQy2096o9a3Wpp8FxEtwu6NqOTgg3um2nm9We6auzimq6Xuo71ChwWCD_NHalO5BKKi2aA9kvtE--rf4ZBkoa-hOfnIr4r8a1p6Q-aKh6IV2hsWu6NuQ3w_qxW2N08m-oEdjGGupDhq_PmiD2Y_8w71lgQ2E4AScUMCQImxQfKcANlD_OmO9fY4d5ZDJDWw4kRL-AkYCGx-hpF5sCw5TCHAJcjuFCJULuIT6wZ69VCoNl2ZJVu8Gne7R0TXwjhoknEw68JxFCEJIMizqfze-lmQPuPc4fbxLu_OeuJ9XEx1rCxBKoDOO1exJ30YlFEpirKXiONHd_CcR_ap2gi2S-nM4Ecnw6e1NKNuNQcqgu7DMBqiT678xGNyeW6EUUL64EpactYSMu72F95RU0riwQ4oKhlVFJzoQEtdku5p9cyLMlvu-YS0wtQRQ8ogTyWIU06JdORikvqcSBtUBKH02OpKdVxpkD8Mq1jM11bVb1HHooLwrsc_5Uvg90Uy4Hmn8ctMSg=", "id": "rs_0ca27027ebdc9274016a057d50aef08191a28c4f9857e71c2e", "summary": [{"type": "summary_text", "text": "**Calculating percentages and trends**\n\nI'm looking at recent data and seeing that the numbers fluctuate quite a bit. After a big project, the results seemed lower, although eight days isn't enough to spot a clear trend. In the last three days, the figures reached 52.8M, especially on the 12th. I might need to calculate specific percentages based on user messages. It seems mandatory to execute code for arithmetic to get precise calculations. Let's do that!"}]}], "tool_calls": [{"id": "call_LgUFxCI2lwqvGh4MC0tNWVUW", "call_id": "call_LgUFxCI2lwqvGh4MC0tNWVUW", "response_item_id": "fc_0ca27027ebdc9274016a057d5fe7c8819191c402c2cdb907ed", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\n# compute summary from queried known db directly\\nimport sqlite3, pathlib\\ncon=sqlite3.connect(pathlib.Path.home()/'.hermes/state.db')\\nq='''select sum(input_tokens),sum(output_tokens),sum(cache_read_tokens),sum(cache_write_tokens),sum(reasoning_tokens),sum(input_tokens+output_tokens+cache_read_tokens+cache_write_tokens+reasoning_tokens),sum(message_count),sum(tool_call_count),count(*) from sessions'''\\ninp,out,cr,cw,rt,total,msgs,tools,sess=con.execute(q).fetchone()\\nprint('all', inp,out,cr,cw,rt,total,msgs,tools,sess)\\nfor name,val in [('input',inp),('output',out),('cache_read',cr),('reasoning',rt)]: print(name, round(100*val/total,2))\\n# last active days averages excluding today? and before/after May12\\nfor label, where in [('May7-12', \\\"date(started_at,'unixepoch','localtime') between '2026-05-07' and '2026-05-12'\\\"), ('May13-14', \\\"date(started_at,'unixepoch','localtime') between '2026-05-13' and '2026-05-14'\\\")]:\\n r=con.execute(f'''select count(*),sum(message_count),sum(tool_call_count),sum(input_tokens+output_tokens+cache_read_tokens+cache_write_tokens+reasoning_tokens),sum(input_tokens),sum(output_tokens),sum(cache_read_tokens) from sessions where {where}''').fetchone()\\n print(label, r, 'tokens/msg', round(r[3]/r[1],1) if r[1] else None, 'tokens/session', round(r[3]/r[0],1) if r[0] else None)\\n# sources\\nfor r in con.execute('''select source,count(*),sum(input_tokens+output_tokens+cache_read_tokens+cache_write_tokens+reasoning_tokens) total from sessions group by source order by total desc'''):\\n print('source',r)\\nPY\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}], "timestamp": "2026-05-14T09:45:30.357460"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"all 6424042 562617 105859004 0 28926 112874589 7538 3448 94\\ninput 5.69\\noutput 0.5\\ncache_read 93.78\\nreasoning 0.03\\nMay7-12 (87, 7353, 3365, 106735650, 5875806, 527761, 100310460) tokens/msg 14515.9 tokens/session 1226846.6\\nMay13-14 (7, 185, 83, 6138939, 548236, 34856, 5548544) tokens/msg 33183.5 tokens/session 876991.3\\nsource ('telegram', 49, 106741289)\\nsource ('cron', 43, 4025363)\\nsource ('cli', 2, 2107937)\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_LgUFxCI2lwqvGh4MC0tNWVUW", "timestamp": "2026-05-14T09:45:30.357460"} {"role": "assistant", "content": "Mein Herr — kurze Antwort: **Ja, Session-Neustarts helfen. Nein, OpenClaw würde ich nicht als Standard reaktivieren. Ja, ich habe Token-Statistiken. Und ja: Hermes lädt nicht automatisch “alles”, aber innerhalb derselben Telegram-Session wächst der Kontext bis zur Compression.**\n\nIch habe gerade die Hermes-Doku/Repo-Docs und unsere lokale `hermes insights`/SQLite-Statistik geprüft.\n\n## 1. Was du von deiner Seite aus tun kannst\n\n### Beste Hebel\n\n- **Nach abgeschlossenem Thema: `/new` oder Session neu starten**\n - Das ist der effektivste manuelle Hebel.\n - Memory bleibt erhalten, aber die lange Gesprächshistorie fällt weg.\n - Ideal nach: Health-Import abgeschlossen, Coding-Task fertig, Recherche fertig.\n\n- **Für laufende, aber lange Themen: `/compress`**\n - Verdichtet die Session, ohne sie komplett zu vergessen.\n - Gut, wenn du sagst: “Wir sind noch im selben Projekt, aber räum den Kontext auf.”\n - Beispiel: `/compress Fokus: Gesundheitsdashboard und offene Fehler`\n\n- **Themen trennen**\n - Nicht zwingend verschiedene Kanäle, aber verschiedene Sessions/Topics sind sinnvoll.\n - Beispiel:\n - Health\n - Dev/Hermes\n - Kalender/Todoist\n - Research\n - Vorteil: Ich muss nicht den Verlauf vom Health-Dashboard mitschleppen, wenn du nur fragst, ob ich eine Mail zusammenfassen kann. Revolutionär, ich weiss.\n\n- **Bei einfachen Fragen explizit sagen: “kurz, ohne Recherche”**\n - Beispiel: “Kurz einschätzen, keine Tools.”\n - Für aktuelle Daten, Dateien, Systemstatus, Mathe etc. muss ich trotzdem Tools verwenden — aber bei Meinungs-/Planungsfragen reduziert es unnötige Recherche.\n\n- **Keine grossen Rohdaten in Telegram kippen, wenn nicht nötig**\n - Besser:\n - “Nutze Datei X”\n - “Lies nur relevante Abschnitte”\n - “Fasse diese PDF zusammen, speichere Details extern”\n - Grosse Logs, PDFs, Screenshots und Tool-Ausgaben sind der klassische Token-Fresser.\n\n- **Bei grossen Aufgaben: erst Auftrag und Scope klar machen**\n - Gut: “Analysiere nur die neuen Laborwerte seit Datum X.”\n - Teuer: “Schau mal alles an, was wir bisher haben.”\n\n## 2. Brauchen wir verschiedene Kanäle?\n\n**Nicht unbedingt verschiedene Plattform-Kanäle.** Entscheidend ist: **separate Sessions pro Thema**.\n\nIn Telegram ist ein frischer Thread/Topic oder `/new` besser als ein endloser Mega-Chat. Ein anderer Kanal bringt nur dann etwas, wenn Hermes dadurch wirklich eine andere Session-Historie verwendet. Der Grundverbrauch durch Systemprompt, Tools und Memory bleibt aber ähnlich.\n\nMein Vorschlag:\n\n- **Für dich praktisch:** weiter Telegram DM nutzen.\n- **Disziplin:** pro grösserem Thema `/new`.\n- **Wenn Telegram Topics sauber funktionieren:** Topics nach Domänen nutzen:\n - `Health`\n - `Jarvis/Hermes`\n - `Admin`\n - `Research`\n - `Coding`\n\n## 3. OpenClaw wieder aktivieren?\n\nMeine Empfehlung: **Nein, nicht als Standard.**\n\nWarum:\n\n- OpenClaw würde zwar als separater Worker Kontext isolieren können.\n- Aber Hermes hat bereits native Alternativen:\n - `delegate_task` für isolierte Subtasks\n - Cronjobs mit eingeschränkten Toolsets\n - lokale/Qwen-Worker für Zusammenfassung/Extraktion\n - eigene Sessions/Topics\n- OpenClaw/Gateway/MCP bringt wieder:\n - zusätzliche Infrastruktur\n - potenzielle Duplikation\n - mehr Routing-Komplexität\n - mehr Risiko, dass Kontext/Dateien/Nontext unklar wandern\n\n**Besserer Ansatz:** Ich nutze bei Bedarf native Hermes-Subagents mit minimalem Kontext und eingeschränkten Toolsets. Also nicht: “Hier, ganzer Chatverlauf.” Sondern: “Extrahiere aus Datei X nur Werte Y und gib JSON zurück.”\n\nOpenClaw nur für Spezialfälle oder wenn du es explizit willst.\n\n## 4. Lädt Hermes weniger Kontext, wenn das Thema es nicht benötigt?\n\n**Teilweise ja — aber mit Grenzen.**\n\nHermes lädt nicht automatisch alle alten Sessions. Standardmässig kommen rein:\n\n- Systemprompt / Persona / Regeln\n- Memory + User Profile\n- relevante Projekt-Kontextdateien, wenn im Workdir vorhanden\n- Tool-Schemas der aktivierten Tools\n- aktuelle Session-Historie\n- Skills, wenn passend geladen\n- Dateien/Webseiten/Bilder nur, wenn ich sie per Tool abrufe oder sie in der Session hängen\n\nWas **nicht** automatisch geladen wird:\n\n- alle alten Telegram-Chats\n- alle Dateien auf der Platte\n- komplette Health-Datenbank\n- alte PDFs/Bilder, ausser wir greifen darauf zu\n- alle Skills vollständig — nur geladene Skills\n\nAber: **Wenn du in derselben langen Telegram-Session bleibst**, bleibt die Session-Historie relevant, bis Compression greift. Darum ist `/new` so wirksam.\n\n## 5. Unsere Token-Statistik\n\nIch habe `hermes insights` und die lokale Session-Datenbank geprüft.\n\n### Letzte 14/30 Tage — effektiv seit 7. Mai\n\n- **Sessions:** 94\n- **Messages:** 7’538\n- **Tool calls:** 3’448\n- **Input tokens:** ca. 6.42 Mio.\n- **Output tokens:** ca. 0.56 Mio.\n- **Total tokens laut Hermes:** ca. 112.9 Mio.\n- **Davon Cache-Read:** ca. 105.9 Mio. = **93.78%**\n\nWichtig: Die 112.9 Mio. sehen brutal aus, aber der grösste Teil ist **cache_read_tokens**. Das sind wiederverwendete Prefix-/Kontext-Tokens und je nach Provider deutlich günstiger bzw. anders behandelt als frische Input Tokens.\n\n### Hauptverbraucher\n\n- **Telegram:** ca. 106.7 Mio. Tokens\n- **Cron:** ca. 4.0 Mio.\n- **CLI:** ca. 2.1 Mio.\n\n### Modelle\n\n- `qwen-3.6-agent`: ca. 69.4 Mio.\n- `gpt-5.5`: ca. 39.8 Mio.\n- `openrouter`: ca. 3.3 Mio.\n\n### Auffälligster Tag\n\n- **12. Mai:** ca. 46.6 Mio. Tokens \n Das war der grosse Health-/Dokumentenprüfungs-Block mit sehr vielen Toolcalls und langen Sessions.\n\n### Seitdem?\n\n- **13. Mai:** ca. 5.65 Mio.\n- **14. Mai bisher:** ca. 0.20 Mio.\n\nAlso: **Ja, nach dem grossen Health-Block sind wir deutlich sparsamer unterwegs.** Aber die Datenbasis ist noch kurz; ein echter Trend braucht ein paar weitere Tage.\n\n## 6. Konkreter Sparplan\n\nIch würde es so machen:\n\n1. **Du nutzt `/new` nach jedem abgeschlossenen Thema.**\n2. **Ich komprimiere lange Sessions früher**, wenn ein Thema weiterläuft.\n3. **Ich nutze Subagents/Worker nur mit kleinem Auftrag**, nicht mit vollem Chatverlauf.\n4. **OpenClaw bleibt deaktiviert**, ausser du willst explizit einen Speziallauf.\n5. **Health-/Datenjobs laufen möglichst script-first oder cron `no_agent=True`**, wenn nur deterministische Daten gesammelt werden.\n6. **Memory bleibt knapp.** Unsere Memory ist bei ca. 94%; ich sollte sie nicht weiter vollstopfen.\n7. **Für neue grosse Aufgaben:** erst Mini-Briefing, dann Toolarbeit. Nicht “alles nochmal lesen”.\n\n## Meine Empfehlung\n\n**Keine OpenClaw-Reaktivierung.** \n**Ja zu mehr Session-Hygiene:** `/new`, Topics/Sessions nach Thema, `/compress` bei langen Arbeitssträngen.\n\nWenn du willst, kann ich als nächsten Schritt unsere Hermes-Konfiguration gezielt auf Token-Sparen prüfen und dir eine kleine “Safe config change”-Liste geben — z.B. Compression-Parameter, Toolset-Reduktion, Cronjobs, Memory-Limits und Topic-Setup.", "reasoning": "**Improving context management**\n\nI'm thinking that if the local Qwen context is smaller than GPT-5.5, I might lose important context. It seems like Qwen via Tailscale could be operating with a 3.6 agent context, but I'm not completely sure about that.\n\nTo ensure consistency in deterministic jobs like morning briefings, I should use cron no_agent scripts. When asking questions, I’ll provide short context explicitly instead of relying on past references and will attach only relevant files or images. For simple, non-current questions, I might request, \"nur kurz, keine Recherche, keine Tools.\"", "finish_reason": "stop", "reasoning_content": "**Improving context management**\n\nI'm thinking that if the local Qwen context is smaller than GPT-5.5, I might lose important context. It seems like Qwen via Tailscale could be operating with a 3.6 agent context, but I'm not completely sure about that.\n\nTo ensure consistency in deterministic jobs like morning briefings, I should use cron no_agent scripts. When asking questions, I’ll provide short context explicitly instead of relying on past references and will attach only relevant files or images. For simple, non-current questions, I might request, \"nur kurz, keine Recherche, keine Tools.\"", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": 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"id": "rs_0b15b98937ad8b52016a057d6809808191a912f326498935d0", "summary": [{"type": "summary_text", "text": "**Improving context management**\n\nI'm thinking that if the local Qwen context is smaller than GPT-5.5, I might lose important context. It seems like Qwen via Tailscale could be operating with a 3.6 agent context, but I'm not completely sure about that.\n\nTo ensure consistency in deterministic jobs like morning briefings, I should use cron no_agent scripts. When asking questions, I’ll provide short context explicitly instead of relying on past references and will attach only relevant files or images. For simple, non-current questions, I might request, \"nur kurz, keine Recherche, keine Tools.\""}]}], "codex_message_items": [{"type": "message", "role": "assistant", "status": "completed", "content": [{"type": "output_text", "text": "Mein Herr — kurze Antwort: **Ja, Session-Neustarts helfen. Nein, OpenClaw würde ich nicht als Standard reaktivieren. Ja, ich habe Token-Statistiken. Und ja: Hermes lädt nicht automatisch “alles”, aber innerhalb derselben Telegram-Session wächst der Kontext bis zur Compression.**\n\nIch habe gerade die Hermes-Doku/Repo-Docs und unsere lokale `hermes insights`/SQLite-Statistik geprüft.\n\n## 1. Was du von deiner Seite aus tun kannst\n\n### Beste Hebel\n\n- **Nach abgeschlossenem Thema: `/new` oder Session neu starten**\n - Das ist der effektivste manuelle Hebel.\n - Memory bleibt erhalten, aber die lange Gesprächshistorie fällt weg.\n - Ideal nach: Health-Import abgeschlossen, Coding-Task fertig, Recherche fertig.\n\n- **Für laufende, aber lange Themen: `/compress`**\n - Verdichtet die Session, ohne sie komplett zu vergessen.\n - Gut, wenn du sagst: “Wir sind noch im selben Projekt, aber räum den Kontext auf.”\n - Beispiel: `/compress Fokus: Gesundheitsdashboard und offene Fehler`\n\n- **Themen trennen**\n - Nicht zwingend verschiedene Kanäle, aber verschiedene Sessions/Topics sind sinnvoll.\n - Beispiel:\n - Health\n - Dev/Hermes\n - Kalender/Todoist\n - Research\n - Vorteil: Ich muss nicht den Verlauf vom Health-Dashboard mitschleppen, wenn du nur fragst, ob ich eine Mail zusammenfassen kann. Revolutionär, ich weiss.\n\n- **Bei einfachen Fragen explizit sagen: “kurz, ohne Recherche”**\n - Beispiel: “Kurz einschätzen, keine Tools.”\n - Für aktuelle Daten, Dateien, Systemstatus, Mathe etc. muss ich trotzdem Tools verwenden — aber bei Meinungs-/Planungsfragen reduziert es unnötige Recherche.\n\n- **Keine grossen Rohdaten in Telegram kippen, wenn nicht nötig**\n - Besser:\n - “Nutze Datei X”\n - “Lies nur relevante Abschnitte”\n - “Fasse diese PDF zusammen, speichere Details extern”\n - Grosse Logs, PDFs, Screenshots und Tool-Ausgaben sind der klassische Token-Fresser.\n\n- **Bei grossen Aufgaben: erst Auftrag und Scope klar machen**\n - Gut: “Analysiere nur die neuen Laborwerte seit Datum X.”\n - Teuer: “Schau mal alles an, was wir bisher haben.”\n\n## 2. Brauchen wir verschiedene Kanäle?\n\n**Nicht unbedingt verschiedene Plattform-Kanäle.** Entscheidend ist: **separate Sessions pro Thema**.\n\nIn Telegram ist ein frischer Thread/Topic oder `/new` besser als ein endloser Mega-Chat. Ein anderer Kanal bringt nur dann etwas, wenn Hermes dadurch wirklich eine andere Session-Historie verwendet. Der Grundverbrauch durch Systemprompt, Tools und Memory bleibt aber ähnlich.\n\nMein Vorschlag:\n\n- **Für dich praktisch:** weiter Telegram DM nutzen.\n- **Disziplin:** pro grösserem Thema `/new`.\n- **Wenn Telegram Topics sauber funktionieren:** Topics nach Domänen nutzen:\n - `Health`\n - `Jarvis/Hermes`\n - `Admin`\n - `Research`\n - `Coding`\n\n## 3. OpenClaw wieder aktivieren?\n\nMeine Empfehlung: **Nein, nicht als Standard.**\n\nWarum:\n\n- OpenClaw würde zwar als separater Worker Kontext isolieren können.\n- Aber Hermes hat bereits native Alternativen:\n - `delegate_task` für isolierte Subtasks\n - Cronjobs mit eingeschränkten Toolsets\n - lokale/Qwen-Worker für Zusammenfassung/Extraktion\n - eigene Sessions/Topics\n- OpenClaw/Gateway/MCP bringt wieder:\n - zusätzliche Infrastruktur\n - potenzielle Duplikation\n - mehr Routing-Komplexität\n - mehr Risiko, dass Kontext/Dateien/Nontext unklar wandern\n\n**Besserer Ansatz:** Ich nutze bei Bedarf native Hermes-Subagents mit minimalem Kontext und eingeschränkten Toolsets. Also nicht: “Hier, ganzer Chatverlauf.” Sondern: “Extrahiere aus Datei X nur Werte Y und gib JSON zurück.”\n\nOpenClaw nur für Spezialfälle oder wenn du es explizit willst.\n\n## 4. Lädt Hermes weniger Kontext, wenn das Thema es nicht benötigt?\n\n**Teilweise ja — aber mit Grenzen.**\n\nHermes lädt nicht automatisch alle alten Sessions. Standardmässig kommen rein:\n\n- Systemprompt / Persona / Regeln\n- Memory + User Profile\n- relevante Projekt-Kontextdateien, wenn im Workdir vorhanden\n- Tool-Schemas der aktivierten Tools\n- aktuelle Session-Historie\n- Skills, wenn passend geladen\n- Dateien/Webseiten/Bilder nur, wenn ich sie per Tool abrufe oder sie in der Session hängen\n\nWas **nicht** automatisch geladen wird:\n\n- alle alten Telegram-Chats\n- alle Dateien auf der Platte\n- komplette Health-Datenbank\n- alte PDFs/Bilder, ausser wir greifen darauf zu\n- alle Skills vollständig — nur geladene Skills\n\nAber: **Wenn du in derselben langen Telegram-Session bleibst**, bleibt die Session-Historie relevant, bis Compression greift. Darum ist `/new` so wirksam.\n\n## 5. Unsere Token-Statistik\n\nIch habe `hermes insights` und die lokale Session-Datenbank geprüft.\n\n### Letzte 14/30 Tage — effektiv seit 7. Mai\n\n- **Sessions:** 94\n- **Messages:** 7’538\n- **Tool calls:** 3’448\n- **Input tokens:** ca. 6.42 Mio.\n- **Output tokens:** ca. 0.56 Mio.\n- **Total tokens laut Hermes:** ca. 112.9 Mio.\n- **Davon Cache-Read:** ca. 105.9 Mio. = **93.78%**\n\nWichtig: Die 112.9 Mio. sehen brutal aus, aber der grösste Teil ist **cache_read_tokens**. Das sind wiederverwendete Prefix-/Kontext-Tokens und je nach Provider deutlich günstiger bzw. anders behandelt als frische Input Tokens.\n\n### Hauptverbraucher\n\n- **Telegram:** ca. 106.7 Mio. Tokens\n- **Cron:** ca. 4.0 Mio.\n- **CLI:** ca. 2.1 Mio.\n\n### Modelle\n\n- `qwen-3.6-agent`: ca. 69.4 Mio.\n- `gpt-5.5`: ca. 39.8 Mio.\n- `openrouter`: ca. 3.3 Mio.\n\n### Auffälligster Tag\n\n- **12. Mai:** ca. 46.6 Mio. Tokens \n Das war der grosse Health-/Dokumentenprüfungs-Block mit sehr vielen Toolcalls und langen Sessions.\n\n### Seitdem?\n\n- **13. Mai:** ca. 5.65 Mio.\n- **14. Mai bisher:** ca. 0.20 Mio.\n\nAlso: **Ja, nach dem grossen Health-Block sind wir deutlich sparsamer unterwegs.** Aber die Datenbasis ist noch kurz; ein echter Trend braucht ein paar weitere Tage.\n\n## 6. Konkreter Sparplan\n\nIch würde es so machen:\n\n1. **Du nutzt `/new` nach jedem abgeschlossenen Thema.**\n2. **Ich komprimiere lange Sessions früher**, wenn ein Thema weiterläuft.\n3. **Ich nutze Subagents/Worker nur mit kleinem Auftrag**, nicht mit vollem Chatverlauf.\n4. **OpenClaw bleibt deaktiviert**, ausser du willst explizit einen Speziallauf.\n5. **Health-/Datenjobs laufen möglichst script-first oder cron `no_agent=True`**, wenn nur deterministische Daten gesammelt werden.\n6. **Memory bleibt knapp.** Unsere Memory ist bei ca. 94%; ich sollte sie nicht weiter vollstopfen.\n7. **Für neue grosse Aufgaben:** erst Mini-Briefing, dann Toolarbeit. Nicht “alles nochmal lesen”.\n\n## Meine Empfehlung\n\n**Keine OpenClaw-Reaktivierung.** \n**Ja zu mehr Session-Hygiene:** `/new`, Topics/Sessions nach Thema, `/compress` bei langen Arbeitssträngen.\n\nWenn du willst, kann ich als nächsten Schritt unsere Hermes-Konfiguration gezielt auf Token-Sparen prüfen und dir eine kleine “Safe config change”-Liste geben — z.B. Compression-Parameter, Toolset-Reduktion, Cronjobs, Memory-Limits und Topic-Setup."}], "id": "msg_0b15b98937ad8b52016a057d78970c8191bcf4731df109662f", "phase": "final_answer"}], "timestamp": "2026-05-14T09:45:30.357460"} {"role": "user", "content": "Ja gerne", "timestamp": "2026-05-14T09:54:01.473603"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqBX8-m3W4XAqZBtei-Cd9kE9rO_gwSALGg-ywB8vSo8qytrhJgxjZelT4AqzExBI4LO4xWWnrFicmPbRrP94w2_MEwYGHp2e6XfiEnr7ybRA6UV5TjiJA9G1jgAdjSnEu1_4UKqBJuk47-YRIudDqhspOYSLrkvN07SNAt2aRl68zD5m1XmJN9aLqEm9igyXzd9GnpFLYEutyZVgR0BbxdTKL-RvjcCG9LtZifzD41O4gGXjeEyIhF2RAWVIH3X8w9WuoGyi93OOBFgfD1XL2QzC89k909JwQJDVQt84y5EKlFdPhNwnDz42yOoCOwYO2fLrhd3928Azy1e9Sfb1tFQSIQGRAW77yKc8WPR8eJ6KmBt2x4I9Di0sFUNPFlEmKY9c0qq8-QfFePJgdslHWk3mJTt2Ua0O2cvqeR6APAbO0bbjU3EuQmDXS3rkPGRrjveweo-eWWphPOZO8tMql6b_mg2QfoGRawgXtGGS6lM1j2sbR67zKnT7dlWPPspqs0NCPmSvENg365oHINHJyvNnFbe7fHv54Mm6uX78Wrom8NcEbdQ_FeR-JBs_12TKHGW6H6OLFH4VFE6_2Oo23eB17CcCQWYvhqX4qaXoqanoBL-iwpB46AT6FNTa8M4URu40LvoT9bK_ElzqARDgE_4ZEHH7eCOvkpOtTwgh0LN_son9FTLHnPVo3ibXo20iflCedxurXyvW0uB26Tn5L8JWMR6Mpmr4IFxWy2Wq3E2_LeZ6jywFohKj4E8Lime8tMXi7JuQFlC75KTkwWv8cx5umkLU2i1lfv4EADpJ4BJfbrYiT15thJnkyrKpgbWScMMyHoSB54zszLKeuWfl1eqGYJ5B8uvTjU1jyLhnCZ0kHMuqNN5ZgOa2QxuU6CIdo9ELfg-lOISoieKMCSCrN4WCsLBBjvmtcB28AXflckvrh_xnKn2CAQxQxoU5gsmVrwT7dXKYypQsECtMjHU4oLonFpZgc6mNi-ZzUp6R3O5JUvr706V5iDh-nPCXdwoFUSIszDVVekXf-zpunXK6YmjhtWXzwLN3rU4P4yh4OdPJg3uLKfTBoN2uNwAPF-2i0ggeUvSkILCbFocFvQBW3b1g1-dhqIUqPkwc8wzw41SZ6gBkpTAePon0OgDNvpxPP2o7F2D9VtXBB9pJwd0eWxX7nwQE8BqRl28fuFzLgRL3eHFAiJnlon6nZJeKqB-QQsxuKdGQXpzKpH347Oyd308ogsHZjA_yOFVpKKZ2_bzgtR6WFuI3qdO-wQQQjfNnoNEv9fynUdeiCjMqdsoL0HelhDKcHmuA8awb71ay8oHF4ATfJ_k4aqDgXsRqB7nhmBP-QZFKJLkeIlrd9md2DzVvE2Xw0_s9NqYQ36wHOZBs9oixp9iPlA0v5cbxzXHjcNbsmDMhdnkn5D-5ghbj2IGo0nq1PQ8k10ilQZk581H5TPRFIV0zfGkZPuby7Rkp70hNXDzrak42rPsuRIRGjerFEuNSX9LqIGd4KpMD9GbsId08=", "id": "rs_0b15b98937ad8b52016a057f3c69148191bd8a25c396a47199", "summary": []}], "tool_calls": [{"id": "call_D56rVBlW6bU4zTGy3aUUSMtB", "call_id": "call_D56rVBlW6bU4zTGy3aUUSMtB", "response_item_id": "fc_0b15b98937ad8b52016a057f3ee9fc81918205077a504d8b13", "type": "function", "function": {"name": "skill_view", "arguments": "{\"name\":\"hermes-agent\"}"}}], "timestamp": "2026-05-14T09:54:01.473603"} {"role": "tool", "name": "skill_view", "content": "{\"success\": true, \"name\": \"hermes-agent\", \"description\": \"Configure, extend, or contribute to Hermes Agent.\", \"tags\": [\"hermes\", \"setup\", \"configuration\", \"multi-agent\", \"spawning\", \"cli\", \"gateway\", \"development\"], \"related_skills\": [\"claude-code\", \"codex\", \"opencode\"], \"content\": \"---\\nname: hermes-agent\\ndescription: \\\"Configure, extend, or contribute to Hermes Agent.\\\"\\nversion: 2.1.0\\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 10+ 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 (ID can be a hub identifier OR a direct https://…/SKILL.md URL; pass --name to override when frontmatter has no name)\\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, BlueBubbles (iMessage), Weixin (WeChat), API Server, Webhooks. Open WebUI connects via the API Server adapter.\\n\\nPlatform docs: https://hermes-agent.nousresearch.com/docs/user-guide/messaging/\\n\\n**Telegram setup:** See `references/telegram-gateway-setup.md` for the complete step-by-step configuration workflow.\\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 (requires honcho plugin)\\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. New commands land fairly\\noften; if something below looks stale, run `/help` in-session for the\\nauthoritative list or see the [live slash commands reference](https://hermes-agent.nousresearch.com/docs/reference/slash-commands).\\nThe registry of record is `hermes_cli/commands.py` — every consumer\\n(autocomplete, Telegram menu, Slack mapping, `/help`) derives from it.\\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/snapshot [sub] Create or restore state snapshots of Hermes config/state (CLI)\\n/background Run prompt in background\\n/queue Queue for next turn\\n/steer Inject a message after the next tool call without interrupting\\n/agents (/tasks) Show active agents and running tasks\\n/resume [name] Resume a named session\\n/goal [text|sub] Set a standing goal Hermes works on across turns until achieved\\n (subcommands: status, pause, resume, clear)\\n/redraw Force a full UI repaint (CLI)\\n```\\n\\n### Configuration\\n```\\n/config Show config (CLI)\\n/model [name] Show or change model\\n/personality [name] Set personality\\n/reasoning [level] Set reasoning (none|minimal|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/busy [sub] Control what Enter does while Hermes is working (CLI)\\n (subcommands: queue, steer, interrupt, status)\\n/indicator [style] Pick the TUI busy-indicator style (CLI)\\n (styles: kaomoji, emoji, unicode, ascii)\\n/footer [on|off] Toggle gateway runtime-metadata footer on final replies\\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/reload-skills Re-scan ~/.hermes/skills/ for added/removed skills\\n/reload Reload .env variables into the running session (CLI)\\n/reload-mcp Reload MCP servers\\n/cron Manage cron jobs (CLI)\\n/curator [sub] Background skill maintenance (status, run, pin, archive, …)\\n/kanban [sub] Multi-profile collaboration board (tasks, links, comments)\\n/plugins List plugins (CLI)\\n```\\n\\n### Gateway\\n```\\n/approve Approve a pending command (gateway)\\n/deny Deny a pending command (gateway)\\n/restart Restart gateway (gateway)\\n/sethome Set current chat as home channel (gateway)\\n/update Update Hermes to latest (gateway)\\n/topic [sub] Enable or inspect Telegram DM topic sessions (gateway)\\n/platforms (/gateway) Show platform connection status (gateway)\\n```\\n\\n### Utility\\n```\\n/branch (/fork) Branch the current session\\n/fast Toggle priority/fast processing\\n/browser Open CDP browser connection\\n/history Show conversation history (CLI)\\n/save Save conversation to file (CLI)\\n/copy [N] Copy the last assistant response to clipboard (CLI)\\n/paste Attach clipboard image (CLI)\\n/image Attach local image file (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/gquota Show Google Gemini Code Assist quota usage (CLI)\\n/status Session info (gateway)\\n/profile Active profile info\\n/debug Upload debug report (system info + logs) and get shareable links\\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_HOME/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/mistral) |\\n| `tts` | `provider` (edge/elevenlabs/openai/minimax/mistral/neutts) |\\n| `memory` | `memory_enabled`, `user_profile_enabled`, `provider` |\\n| `security` | `tirith_enabled`, `website_blocklist` |\\n| `delegation` | `model`, `provider`, `base_url`, `api_key`, `max_iterations` (50), `reasoning_effort` |\\n| `checkpoints` | `enabled`, `max_snapshots` (50) |\\n\\nFull config reference: https://hermes-agent.nousresearch.com/docs/user-guide/configuration\\n\\n### Providers\\n\\n20+ 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 auth` |\\n| OpenAI Codex | OAuth | `hermes auth` |\\n| GitHub Copilot | Token | `COPILOT_GITHUB_TOKEN` |\\n| Google Gemini | API key | `GOOGLE_API_KEY` or `GEMINI_API_KEY` |\\n| DeepSeek | API key | `DEEPSEEK_API_KEY` |\\n| xAI / Grok | API key | `XAI_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| MiniMax CN | API key | `MINIMAX_CN_API_KEY` |\\n| Kimi / Moonshot | API key | `KIMI_API_KEY` |\\n| Alibaba / DashScope | API key | `DASHSCOPE_API_KEY` |\\n| Xiaomi MiMo | API key | `XIAOMI_API_KEY` |\\n| Kilo Code | API key | `KILOCODE_API_KEY` |\\n| AI Gateway (Vercel) | API key | `AI_GATEWAY_API_KEY` |\\n| OpenCode Zen | API key | `OPENCODE_ZEN_API_KEY` |\\n| OpenCode Go | API key | `OPENCODE_GO_API_KEY` |\\n| Qwen OAuth | OAuth | `hermes login --provider qwen-oauth` |\\n| Custom endpoint | Config | `model.base_url` + `model.api_key` in config.yaml |\\n| GitHub Copilot ACP | External | `COPILOT_CLI_PATH` or Copilot CLI |\\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| `search` | Web search only (subset of `web`) |\\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| `video` | Video analysis and 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| `messaging` | Cross-platform message sending |\\n| `todo` | In-session task planning and tracking |\\n| `kanban` | Multi-agent work-queue tools (gated to workers) |\\n| `debugging` | Extra introspection/debug tools (off by default) |\\n| `safe` | Minimal, low-risk toolset for locked-down sessions |\\n| `spotify` | Spotify playback and playlist control |\\n| `homeassistant` | Smart home control (off by default) |\\n| `discord` | Discord integration tools |\\n| `discord_admin` | Discord admin/moderation tools |\\n| `feishu_doc` | Feishu (Lark) document tools |\\n| `feishu_drive` | Feishu (Lark) drive tools |\\n| `yuanbao` | Yuanbao integration tools |\\n| `rl` | Reinforcement learning tools (off by default) |\\n| `moa` | Mixture of Agents (off by default) |\\n\\nFull enumeration lives in `toolsets.py` as the `TOOLSETS` dict; `_HERMES_CORE_TOOLS` is the default bundle most platforms inherit from.\\n\\nTool changes take effect on `/reset` (new session). They do NOT apply mid-conversation to preserve prompt caching.\\n\\n---\\n\\n## Security & Privacy Toggles\\n\\nCommon \\\"why is Hermes doing X to my output / tool calls / commands?\\\" toggles — and the exact commands to change them. Most of these need a fresh session (`/reset` in chat, or start a new `hermes` invocation) because they're read once at startup.\\n\\n### Secret redaction in tool output\\n\\nSecret redaction is **off by default** — tool output (terminal stdout, `read_file`, web content, subagent summaries, etc.) passes through unmodified. If the user wants Hermes to auto-mask strings that look like API keys, tokens, and secrets before they enter the conversation context and logs:\\n\\n```bash\\nhermes config set security.redact_secrets true # enable globally\\n```\\n\\n**Restart required.** `security.redact_secrets` is snapshotted at import time — toggling it mid-session (e.g. via `export HERMES_REDACT_SECRETS=true` from a tool call) will NOT take effect for the running process. Tell the user to run `hermes config set security.redact_secrets true` in a terminal, then start a new session. This is deliberate — it prevents an LLM from flipping the toggle on itself mid-task.\\n\\nDisable again with:\\n```bash\\nhermes config set security.redact_secrets false\\n```\\n\\n### PII redaction in gateway messages\\n\\nSeparate from secret redaction. When enabled, the gateway hashes user IDs and strips phone numbers from the session context before it reaches the model:\\n\\n```bash\\nhermes config set privacy.redact_pii true # enable\\nhermes config set privacy.redact_pii false # disable (default)\\n```\\n\\n### Command approval prompts\\n\\nBy default (`approvals.mode: manual`), Hermes prompts the user before running shell commands flagged as destructive (`rm -rf`, `git reset --hard`, etc.). The modes are:\\n\\n- `manual` — always prompt (default)\\n- `smart` — use an auxiliary LLM to auto-approve low-risk commands, prompt on high-risk\\n- `off` — skip all approval prompts (equivalent to `--yolo`)\\n\\n```bash\\nhermes config set approvals.mode smart # recommended middle ground\\nhermes config set approvals.mode off # bypass everything (not recommended)\\n```\\n\\nPer-invocation bypass without changing config:\\n- `hermes --yolo …`\\n- `export HERMES_YOLO_MODE=1`\\n\\nNote: YOLO / `approvals.mode: off` does NOT turn off secret redaction. They are independent.\\n\\n### Shell hooks allowlist\\n\\nSome shell-hook integrations require explicit allowlisting before they fire. Managed via `~/.hermes/shell-hooks-allowlist.json` — prompted interactively the first time a hook wants to run.\\n\\n### Disabling the web/browser/image-gen tools\\n\\nTo keep the model away from network or media tools entirely, open `hermes tools` and toggle per-platform. Takes effect on next session (`/reset`). See the Tools & Skills section above.\\n\\n---\\n\\n### Voice & Transcription\\n\\n### STT (Voice → Text)\\n\\nVoice messages from messaging platforms are auto-transcribed.\\n\\n**⚠️ Pitfall: faster-whisper must be installed for local STT to work.** The config may show `provider: local` but if `faster-whisper` is not installed in the venv, STT silently fails. Always verify with `pip show faster-whisper` after configuring local STT.\\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`\\n4. **Mistral Voxtral** — set `MISTRAL_API_KEY`\\n\\nConfig:\\n```yaml\\nstt:\\n enabled: true\\n provider: local # local, groq, openai, mistral\\n local:\\n model: small # tiny, base, small, medium, large-v3 — use 'small' or higher for German\\n language: de # always set explicitly for German — auto-detect is unreliable\\n```\\n\\n### Pitfalls\\n- **faster-whisper must be installed** — config shows `provider: local` but STT silently fails if the package is missing\\n- **Use `small` model minimum for German** — `base` is too weak\\n- **Set `language: de` explicitly** — auto-detect is unreliable\\n- **Swiss German (dialect) is NOT supported** — Whisper transcribes dialect poorly; user should speak Standard German\\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| MiniMax | `MINIMAX_API_KEY` | Paid |\\n| Mistral (Voxtral) | `MISTRAL_API_KEY` | Paid |\\n| NeuTTS (local) | None (`pip install neutts[all]` + `espeak-ng`) | Free |\\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## Durable & Background Systems\\n\\nFour systems run alongside the main conversation loop. Quick reference\\nhere; full developer notes live in `AGENTS.md`, user-facing docs under\\n`website/docs/user-guide/features/`.\\n\\n### Delegation (`delegate_task`)\\n\\nSynchronous subagent spawn — the parent waits for the child's summary\\nbefore continuing its own loop. Isolated context + terminal session.\\n\\n- **Single:** `delegate_task(goal, context, toolsets)`.\\n- **Batch:** `delegate_task(tasks=[{goal, ...}, ...])` runs children in\\n parallel, capped by `delegation.max_concurrent_children` (default 3).\\n- **Roles:** `leaf` (default; cannot re-delegate) vs `orchestrator`\\n (can spawn its own workers, bounded by `delegation.max_spawn_depth`).\\n- **Not durable.** If the parent is interrupted, the child is\\n cancelled. For work that must outlive the turn, use `cronjob` or\\n `terminal(background=True, notify_on_complete=True)`.\\n\\nConfig: `delegation.*` in `config.yaml`.\\n\\n### Cron (scheduled jobs)\\n\\nDurable scheduler — `cron/jobs.py` + `cron/scheduler.py`. Drive it via\\nthe `cronjob` tool, the `hermes cron` CLI (`list`, `add`, `edit`,\\n`pause`, `resume`, `run`, `remove`), or the `/cron` slash command.\\n\\n- **Schedules:** duration (`\\\"30m\\\"`, `\\\"2h\\\"`), \\\"every\\\" phrase\\n (`\\\"every monday 9am\\\"`), 5-field cron (`\\\"0 9 * * *\\\"`), or ISO timestamp.\\n- **Per-job knobs:** `skills`, `model`/`provider` override, `script`\\n (pre-run data collection; `no_agent=True` makes the script the whole\\n job), `context_from` (chain job A's output into job B), `workdir`\\n (run in a specific dir with its `AGENTS.md` / `CLAUDE.md` loaded),\\n multi-platform delivery.\\n- **Invariants:** 3-minute hard interrupt per run, `.tick.lock` file\\n prevents duplicate ticks across processes, cron sessions pass\\n `skip_memory=True` by default, and cron deliveries are framed with a\\n header/footer instead of being mirrored into the target gateway\\n session (keeps role alternation intact).\\n\\nUser docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/cron\\n\\n### Curator (skill lifecycle)\\n\\nBackground maintenance for agent-created skills. Tracks usage, marks\\nidle skills stale, archives stale ones, keeps a pre-run tar.gz backup\\nso nothing is lost.\\n\\n- **CLI:** `hermes curator ` — `status`, `run`, `pause`, `resume`,\\n `pin`, `unpin`, `archive`, `restore`, `prune`, `backup`, `rollback`.\\n- **Slash:** `/curator ` mirrors the CLI.\\n- **Scope:** only touches skills with `created_by: \\\"agent\\\"` provenance.\\n Bundled + hub-installed skills are off-limits. **Never deletes** —\\n max destructive action is archive. Pinned skills are exempt from\\n every auto-transition and every LLM review pass.\\n- **Telemetry:** sidecar at `~/.hermes/skills/.usage.json` holds\\n per-skill `use_count`, `view_count`, `patch_count`,\\n `last_activity_at`, `state`, `pinned`.\\n\\nConfig: `curator.*` (`enabled`, `interval_hours`, `min_idle_hours`,\\n`stale_after_days`, `archive_after_days`, `backup.*`).\\nUser docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/curator\\n\\n### Kanban (multi-agent work queue)\\n\\nDurable SQLite board for multi-profile / multi-worker collaboration.\\nUsers drive it via `hermes kanban `; dispatcher-spawned workers\\nsee a focused `kanban_*` toolset gated by `HERMES_KANBAN_TASK` so the\\nschema footprint is zero outside worker processes.\\n\\n- **CLI verbs (common):** `init`, `create`, `list` (alias `ls`),\\n `show`, `assign`, `link`, `unlink`, `comment`, `complete`, `block`,\\n `unblock`, `archive`, `tail`. Less common: `watch`, `stats`, `runs`,\\n `log`, `dispatch`, `daemon`, `gc`.\\n- **Worker toolset:** `kanban_show`, `kanban_complete`, `kanban_block`,\\n `kanban_heartbeat`, `kanban_comment`, `kanban_create`, `kanban_link`.\\n- **Dispatcher** runs inside the gateway by default\\n (`kanban.dispatch_in_gateway: true`) — reclaims stale claims,\\n promotes ready tasks, atomically claims, spawns assigned profiles.\\n Auto-blocks a task after ~5 consecutive spawn failures.\\n- **Isolation:** board is the hard boundary (workers get\\n `HERMES_KANBAN_BOARD` pinned in env); tenant is a soft namespace\\n within a board for workspace-path + memory-key isolation.\\n\\nUser docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/kanban\\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. In gateway: `/restart`. In CLI: exit and relaunch.\\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\\n4. **Copilot 403**: `gh auth login` tokens do NOT work for Copilot API. You must use the Copilot-specific OAuth device code flow via `hermes model` → GitHub Copilot.\\n\\n### Changes not taking effect\\n- **Tools/skills:** `/reset` starts a new session with updated toolset\\n- **Config changes:** In gateway: `/restart`. In CLI: exit and relaunch.\\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### Gateway issues\\nCheck logs first:\\n```bash\\ngrep -i \\\"failed to send\\\\|error\\\" ~/.hermes/logs/gateway.log | tail -20\\n```\\n\\nCommon gateway problems:\\n- **Gateway dies on SSH logout**: Enable linger: `sudo loginctl enable-linger $USER`\\n- **Gateway dies on WSL2 close**: WSL2 requires `systemd=true` in `/etc/wsl.conf` for systemd services to work. Without it, gateway falls back to `nohup` (dies when session closes).\\n- **Gateway crash loop**: Reset the failed state: `systemctl --user reset-failed hermes-gateway`\\n\\n### Platform-specific issues\\n- **Discord bot silent**: Must enable **Message Content Intent** in Bot → Privileged Gateway Intents.\\n- **Slack bot only works in DMs**: Must subscribe to `message.channels` event. Without it, the bot ignores public channels.\\n- **Windows HTTP 400 \\\"No models provided\\\"**: Config file encoding issue (BOM). Ensure `config.yaml` is saved as UTF-8 without BOM.\\n\\n### Auxiliary models not working\\nIf `auxiliary` tasks (vision, compression, session_search) fail silently, the `auto` provider can't find a backend. Either set `OPENROUTER_API_KEY` or `GOOGLE_API_KEY`, or explicitly configure each auxiliary task's provider:\\n```bash\\nhermes config set auxiliary.vision.provider \\nhermes config set auxiliary.vision.model \\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, context compression, memory, model routing, credential pooling, skill dispatch\\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 to `toolsets.py`** → `_HERMES_CORE_TOOLS` list.\\n\\nAuto-discovery: any `tools/*.py` file with a top-level `registry.register()` call is imported automatically — no manual list needed.\\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\\npython -m pytest tests/ -o 'addopts=' -q # Full suite\\npython -m pytest tests/tools/ -q # Specific area\\n```\\n\\n- Tests auto-redirect `HERMES_HOME` to temp dirs — never touch real `~/.hermes/`\\n- Run full suite before pushing any change\\n- Use `-o 'addopts='` to clear any baked-in pytest flags\\n\\n### Commit Conventions\\n\\n```\\ntype: concise subject line\\n\\nOptional body.\\n```\\n\\nTypes: `fix:`, `feat:`, `refactor:`, `docs:`, `chore:`\\n\\n### Key Rules\\n\\n- **Never break prompt caching** — don't change context, tools, or system prompt mid-conversation\\n- **Message role alternation** — never two assistant or two user messages in a row\\n- Use `get_hermes_home()` from `hermes_constants` for all paths (profile-safe)\\n- Config values go in `config.yaml`, secrets go in `.env`\\n- New tools need a `check_fn` so they only appear when requirements are met\\n\", \"path\": \"autonomous-ai-agents/hermes-agent/SKILL.md\", \"skill_dir\": \"/home/agent/.hermes/skills/autonomous-ai-agents/hermes-agent\", \"linked_files\": {\"references\": [\"references/telegram-gateway-setup.md\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\", \"metadata\": {\"hermes\": {\"tags\": [\"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_D56rVBlW6bU4zTGy3aUUSMtB", "timestamp": "2026-05-14T09:54:01.473603"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_FQUfKQEZdLs2BcWhVoR63nSQ", "call_id": "call_FQUfKQEZdLs2BcWhVoR63nSQ", "response_item_id": "fc_0b15b98937ad8b52016a057f464ddc8191b2de2b1774ce13d2", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"hermes config check && printf '\\\\n--- status ---\\\\n' && hermes status --all\",\"timeout\":180,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}, {"id": "call_ywZQYRmnDuAY3ga5rjLFM7bj", "call_id": "call_ywZQYRmnDuAY3ga5rjLFM7bj", "response_item_id": "fc_0b15b98937ad8b52016a057f464df48191a1dbbba6814d1802", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"hermes tools list\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}, {"id": "call_YGLOGXsMLfqwEfceDgR15mlg", "call_id": "call_YGLOGXsMLfqwEfceDgR15mlg", "response_item_id": "fc_0b15b98937ad8b52016a057f464e008191b7185a70946149ae", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"hermes cron list --all\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}, {"id": "call_XSl9QUon7hpI8idcEKQQavtV", "call_id": "call_XSl9QUon7hpI8idcEKQQavtV", "response_item_id": "fc_0b15b98937ad8b52016a057f464e088191ace5155a8892958a", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nimport yaml, pathlib, json\\np=pathlib.Path.home()/'.hermes/config.yaml'\\nd=yaml.safe_load(p.read_text()) or {}\\nkeys=['model','compression','context','prompt_caching','memory','gateway','delegation','agent','toolsets','auxiliary','display','stt','tts','plugins','curator','kanban']\\nfor k in keys:\\n if k in d:\\n print(f'## {k}')\\n print(yaml.safe_dump(d[k], sort_keys=False, allow_unicode=True))\\nPY\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}], "timestamp": "2026-05-14T09:54:01.473603"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"📋 Configuration Status\\n\\n Config version: 23 ✓\\n\\n Required:\\n\\n Optional:\\n ○ NOUS_BASE_URL\\n ✓ OPENROUTER_API_KEY\\n ○ GOOGLE_API_KEY\\n ○ GEMINI_API_KEY\\n ○ GEMINI_BASE_URL\\n ○ XAI_API_KEY\\n ○ XAI_BASE_URL\\n ○ NVIDIA_API_KEY\\n ○ NVIDIA_BASE_URL\\n ○ LM_API_KEY\\n ○ LM_BASE_URL\\n ○ GLM_API_KEY\\n ○ ZAI_API_KEY\\n ○ Z_AI_API_KEY\\n ○ GLM_BASE_URL\\n ○ KIMI_API_KEY\\n ○ KIMI_BASE_URL\\n ○ KIMI_CN_API_KEY\\n ○ STEPFUN_API_KEY\\n ○ STEPFUN_BASE_URL\\n ○ ARCEEAI_API_KEY\\n ○ ARCEE_BASE_URL\\n ○ GMI_API_KEY\\n ○ GMI_BASE_URL\\n ○ MINIMAX_API_KEY\\n ○ MINIMAX_BASE_URL\\n ○ MINIMAX_CN_API_KEY\\n ○ MINIMAX_CN_BASE_URL\\n ○ DEEPSEEK_API_KEY\\n ○ DEEPSEEK_BASE_URL\\n ○ DASHSCOPE_API_KEY\\n ○ DASHSCOPE_BASE_URL\\n ○ HERMES_QWEN_BASE_URL\\n ○ HERMES_GEMINI_CLIENT_ID\\n ○ HERMES_GEMINI_CLIENT_SECRET\\n ○ HERMES_GEMINI_PROJECT_ID\\n ○ OPENCODE_ZEN_API_KEY\\n ○ OPENCODE_ZEN_BASE_URL\\n ○ OPENCODE_GO_API_KEY\\n ○ OPENCODE_GO_BASE_URL\\n ○ HF_TOKEN\\n ○ HF_BASE_URL\\n ○ OLLAMA_API_KEY\\n ○ OLLAMA_BASE_URL\\n ○ XIAOMI_API_KEY\\n ○ XIAOMI_BASE_URL\\n ○ AWS_REGION\\n ○ AWS_PROFILE\\n ○ AZURE_FOUNDRY_API_KEY\\n ○ AZURE_FOUNDRY_BASE_URL\\n ○ EXA_API_KEY → web_search, web_extract\\n ○ PARALLEL_API_KEY → web_search, web_extract\\n ○ FIRECRAWL_API_KEY → web_search, web_extract\\n ○ FIRECRAWL_API_URL\\n ○ FIRECRAWL_GATEWAY_URL\\n ○ TOOL_GATEWAY_DOMAIN\\n ○ TOOL_GATEWAY_SCHEME\\n ○ TOOL_GATEWAY_USER_TOKEN\\n ○ TAVILY_API_KEY → web_search, web_extract\\n ○ SEARXNG_URL → web_search\\n ○ BRAVE_SEARCH_API_KEY → web_search\\n ○ BROWSERBASE_API_KEY → browser_navigate, browser_click\\n ○ BROWSERBASE_PROJECT_ID → browser_navigate, browser_click\\n ○ BROWSER_USE_API_KEY → browser_navigate, browser_click\\n ○ FIRECRAWL_BROWSER_TTL → browser_navigate, browser_click\\n ○ AGENT_BROWSER_ENGINE → browser_navigate, browser_snapshot\\n ○ CAMOFOX_URL → browser_navigate, browser_click\\n ○ FAL_KEY → image_generate\\n ○ TINKER_API_KEY → rl_start_training, rl_check_status\\n ○ WANDB_API_KEY → rl_get_results, rl_check_status\\n ○ VOICE_TOOLS_OPENAI_KEY → voice_transcription, openai_tts\\n ○ ELEVENLABS_API_KEY\\n ○ MISTRAL_API_KEY\\n ○ GITHUB_TOKEN\\n ○ NOTION_API_KEY\\n ○ LINEAR_API_KEY\\n ○ AIRTABLE_API_KEY\\n ○ TENOR_API_KEY\\n ○ HONCHO_API_KEY → honcho_context\\n ○ HONCHO_BASE_URL\\n ○ HERMES_LANGFUSE_PUBLIC_KEY\\n ○ HERMES_LANGFUSE_SECRET_KEY\\n ○ HERMES_LANGFUSE_BASE_URL\\n ✓ TELEGRAM_BOT_TOKEN\\n ✓ TELEGRAM_ALLOWED_USERS\\n ○ TELEGRAM_PROXY\\n ○ DISCORD_BOT_TOKEN\\n ○ DISCORD_ALLOWED_USERS\\n ○ DISCORD_REPLY_TO_MODE\\n ○ SLACK_BOT_TOKEN\\n ○ SLACK_APP_TOKEN\\n ○ MATTERMOST_URL\\n ○ MATTERMOST_TOKEN\\n ○ MATTERMOST_ALLOWED_USERS\\n ○ MATTERMOST_REQUIRE_MENTION\\n ○ MATTERMOST_FREE_RESPONSE_CHANNELS\\n ○ MATRIX_HOMESERVER\\n ○ MATRIX_ACCESS_TOKEN\\n ○ MATRIX_USER_ID\\n ○ MATRIX_ALLOWED_USERS\\n ○ MATRIX_REQUIRE_MENTION\\n ○ MATRIX_FREE_RESPONSE_ROOMS\\n ○ MATRIX_AUTO_THREAD\\n ○ MATRIX_DM_AUTO_THREAD\\n ○ MATRIX_DEVICE_ID\\n ○ MATRIX_RECOVERY_KEY\\n ○ BLUEBUBBLES_SERVER_URL\\n ○ BLUEBUBBLES_PASSWORD\\n ○ BLUEBUBBLES_ALLOWED_USERS\\n ○ BLUEBUBBLES_ALLOW_ALL_USERS\\n ○ QQ_APP_ID\\n ○ QQ_CLIENT_SECRET\\n ○ QQ_ALLOWED_USERS\\n ○ QQ_GROUP_ALLOWED_USERS\\n ○ QQ_ALLOW_ALL_USERS\\n ○ QQBOT_HOME_CHANNEL\\n ○ QQBOT_HOME_CHANNEL_NAME\\n ○ QQ_SANDBOX\\n ○ IRC_SERVER\\n ○ IRC_CHANNEL\\n ○ IRC_NICKNAME\\n ○ IRC_SERVER_PASSWORD\\n ○ IRC_NICKSERV_PASSWORD\\n ○ GATEWAY_ALLOW_ALL_USERS\\n ○ API_SERVER_ENABLED\\n ○ API_SERVER_KEY\\n ○ API_SERVER_PORT\\n ○ API_SERVER_HOST\\n ○ API_SERVER_MODEL_NAME\\n ○ GATEWAY_PROXY_URL\\n ○ GATEWAY_PROXY_KEY\\n ○ WEBHOOK_ENABLED\\n ○ WEBHOOK_PORT\\n ○ WEBHOOK_SECRET\\n ○ SUDO_PASSWORD\\n ✓ HERMES_MAX_ITERATIONS\\n ○ HERMES_TOOL_PROGRESS\\n ○ HERMES_TOOL_PROGRESS_MODE\\n ○ HERMES_PREFILL_MESSAGES_FILE\\n ○ HERMES_EPHEMERAL_SYSTEM_PROMPT\\n ○ AI_GATEWAY_API_KEY\\n ○ ALIBABA_CODING_PLAN_API_KEY\\n ○ ALIBABA_CODING_PLAN_BASE_URL\\n ○ ANTHROPIC_API_KEY\\n ○ ANTHROPIC_TOKEN\\n ○ CLAUDE_CODE_OAUTH_TOKEN\\n ○ KILOCODE_API_KEY\\n ○ KIMI_CODING_API_KEY\\n ○ IRC_PORT\\n ○ IRC_USE_TLS\\n ○ IRC_ALLOWED_USERS\\n ○ IRC_ALLOW_ALL_USERS\\n ○ IRC_HOME_CHANNEL\\n ○ GOOGLE_CHAT_PROJECT_ID\\n ○ GOOGLE_CHAT_SUBSCRIPTION_NAME\\n ○ GOOGLE_CHAT_SERVICE_ACCOUNT_JSON\\n ○ GOOGLE_CHAT_ALLOWED_USERS\\n ○ GOOGLE_CHAT_HOME_CHANNEL\\n ○ LINE_CHANNEL_ACCESS_TOKEN\\n ○ LINE_CHANNEL_SECRET\\n ○ LINE_PORT\\n ○ LINE_HOST\\n ○ LINE_PUBLIC_URL\\n ○ LINE_ALLOWED_USERS\\n ○ LINE_ALLOWED_GROUPS\\n ○ LINE_ALLOWED_ROOMS\\n ○ LINE_ALLOW_ALL_USERS\\n ○ LINE_HOME_CHANNEL\\n ○ LINE_SLOW_RESPONSE_THRESHOLD\\n ○ TEAMS_CLIENT_ID\\n ○ TEAMS_CLIENT_SECRET\\n ○ TEAMS_TENANT_ID\\n ○ TEAMS_PORT\\n ○ TEAMS_ALLOWED_USERS\\n ○ TEAMS_ALLOW_ALL_USERS\\n ○ TEAMS_HOME_CHANNEL\\n ○ TEAMS_HOME_CHANNEL_NAME\\n\\n\\n--- status ---\\n\\n┌─────────────────────────────────────────────────────────┐\\n│ ⚕ Hermes Agent Status │\\n└─────────────────────────────────────────────────────────┘\\n\\n◆ Environment\\n Project: /home/agent/.hermes/hermes-agent\\n Python: 3.11.15\\n .env file: ✓ exists\\n Model: gpt-5.5\\n Provider: OpenAI Codex\\n\\n◆ API Keys\\n OpenRouter ✓ 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\\n OpenAI ✗ \\n Google / Gemini ✗ \\n DeepSeek ✗ \\n xAI / Grok ✗ \\n NVIDIA NIM ✗ \\n Z.AI / GLM ✗ \\n Kimi ✗ \\n StepFun Step Plan ✗ \\n MiniMax ✗ \\n MiniMax-CN ✗ \\n Firecrawl ✗ \\n Tavily ✗ \\n Browser Use ✗ \\n Browserbase ✗ \\n FAL ✗ \\n Tinker ✗ \\n WandB ✗ \\n ElevenLabs ✗ \\n GitHub ✗ \\n Anthropic ✗ \\n\\n◆ Auth Providers\\n Nous Portal ✗ not logged in (run: hermes auth add nous --type oauth)\\n OpenAI Codex ✓ logged in\\n Auth file: /home/agent/.hermes/auth.json\\n Refreshed: 2026-05-12 14:12:22 CEST\\n Qwen OAuth ✗ not logged in (run: qwen auth qwen-oauth)\\n Auth file: /home/agent/.qwen/oauth_creds.json\\n Error: Qwen CLI credentials not found. Run 'qwen auth qwen-oauth' first.\\n MiniMax OAuth ✗ not logged in (run: hermes auth add minimax-oauth)\\n\\n◆ API-Key Providers\\n Z.AI / GLM ✗ not configured (run: hermes model)\\n Kimi / Moonshot ✗ not configured (run: hermes model)\\n StepFun Step Plan ✗ not configured (run: hermes model)\\n MiniMax ✗ not configured (run: hermes model)\\n MiniMax (China) ✗ not configured (run: hermes model)\\n\\n◆ Terminal Backend\\n Backend: local\\n Sudo: ✗ disabled\\n\\n◆ Messaging Platforms\\n Telegram ✓ configured (home: 1344779884)\\n Discord ✗ not configured\\n WhatsApp ✗ not configured\\n Signal ✗ not configured\\n Slack ✗ not configured\\n Email ✗ not configured\\n SMS ✗ not configured\\n DingTalk ✗ not configured\\n Feishu ✗ not configured\\n WeCom ✗ not configured\\n WeCom Callback ✗ not configured\\n Weixin ✗ not configured\\n BlueBubbles ✗ not configured\\n QQBot ✗ not configured\\n Yuanbao ✗ not configured\\n\\n◆ Gateway Service\\n Status: ✓ running\\n Manager: systemd (user)\\n PID(s): 280485\\n\\n◆ Scheduled Jobs\\n Jobs: 7 active, 8 total\\n\\n◆ Sessions\\n Active: 1 session(s)\\n\\n────────────────────────────────────────────────────────────\\n Run 'hermes doctor' for detailed diagnostics\\n Run 'hermes setup' to configure\", \"exit_code\": 0, \"error\": null}\n\n[Subdirectory context discovered: .hermes/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\n# Prefer .venv; fall back to venv if that's what your checkout has.\nsource .venv/bin/activate # or: source venv/bin/activate\n```\n\n`scripts/run_tests.sh` probes `.venv` first, then `venv`, then\n`$HOME/.hermes/hermes-agent/venv` (for worktrees that share a venv with the\nmain checkout).\n\n## Project Structure\n\nFile counts shift constantly — don't treat the tree below as exhaustive.\nThe canonical source is the filesystem. The notes call out the load-bearing\nentry points you'll actually edit.\n\n```\nhermes-agent/\n├── run_agent.py # AIAgent class — core conversation loop (~12k LOC)\n├── model_tools.py # Tool orchestration, discover_builtin_tools(), handle_function_call()\n├── toolsets.py # Toolset definitions, _HERMES_CORE_TOOLS list\n├── cli.py # HermesCLI class — interactive CLI orchestrator (~11k LOC)\n├── hermes_state.py # SessionDB — SQLite session store (FTS5 search)\n├── hermes_constants.py # get_hermes_home(), display_hermes_home() — profile-aware paths\n├── hermes_logging.py # setup_logging() — agent.log / errors.log / gateway.log (profile-aware)\n├── batch_runner.py # Parallel batch processing\n├── agent/ # Agent internals (provider adapters, memory, caching, compression, etc.)\n├── hermes_cli/ # CLI subcommands, setup wizard, plugins loader, skin engine\n├── tools/ # Tool implementations — auto-discovered via tools/registry.py\n│ └── environments/ # Terminal backends (local, docker, ssh, modal, daytona, singularity)\n├── gateway/ # Messaging gateway — run.py + session.py + platforms/\n│ ├── platforms/ # Adapter per platform (telegram, discord, slack, whatsapp,\n│ │ # homeassistant, signal, matrix, mattermost, email, sms,\n│ │ # dingtalk, wecom, weixin, feishu, qqbot, bluebubbles,\n│ │ # yuanbao, webhook, api_server, ...). See ADDING_A_PLATFORM.md.\n│ └── builtin_hooks/ # Extension point for always-registered gateway hooks (none shipped)\n├── plugins/ # Plugin system (see \"Plugins\" section below)\n│ ├── memory/ # Memory-provider plugins (honcho, mem0, supermemory, ...)\n│ ├── context_engine/ # Context-engine plugins\n│ ├── model-providers/ # Inference backend plugins (openrouter, anthropic, gmi, ...)\n│ ├── kanban/ # Multi-agent board dispatcher + worker plugin\n│ ├── hermes-achievements/ # Gamified achievement tracking\n│ ├── observability/ # Metrics / traces / logs plugin\n│ ├── image_gen/ # Image-generation providers\n│ └── / # disk-cleanup, example-dashboard, google_meet, platforms,\n│ # spotify, strike-freedom-cockpit, ...\n├── optional-skills/ # Heavier/niche skills shipped but NOT active by default\n├── skills/ # Built-in skills bundled with the repo\n├── ui-tui/ # Ink (React) terminal UI — `hermes --tui`\n│ └── src/ # entry.tsx, app.tsx, gatewayClient.ts + app/components/hooks/lib\n├── tui_gateway/ # Python JSON-RPC backend for the TUI\n├── acp_adapter/ # ACP server (VS Code / Zed / JetBrains integration)\n├── cron/ # Scheduler — jobs.py, scheduler.py\n├── environments/ # RL training environments (Atropos)\n├── scripts/ # run_tests.sh, release.py, auxiliary scripts\n├── website/ # Docusaurus docs site\n└── tests/ # Pytest suite (~17k tests across ~900 files as of May 2026)\n```\n\n**User config:** `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys only).\n**Logs:** `~/.hermes/logs/` — `agent.log` (INFO+), `errors.log` (WARNING+),\n`gateway.log` when running the gateway. Profile-aware via `get_hermes_home()`.\nBrowse with `hermes logs [--follow] [--level ...] [--session ...]`.\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\nThe real `AIAgent.__init__` takes ~60 parameters (credentials, routing, callbacks,\nsession context, budget, credential pool, etc.). The signature below is the\nminimum subset you'll usually touch — read `run_agent.py` for the full list.\n\n```python\nclass AIAgent:\n def __init__(self,\n base_url: str = None,\n api_key: str = None,\n provider: str = None,\n api_mode: str = None, # \"chat_completions\" | \"codex_responses\" | ...\n model: str = \"\", # empty → resolved from config/provider later\n max_iterations: int = 90, # tool-calling iterations (shared with subagents)\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 credential_pool=None,\n # ... plus callbacks, thread/user/chat IDs, iteration_budget, fallback_model,\n # checkpoints config, prefill_messages, service_tier, reasoning_config, etc.\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, with\ninterrupt checks, budget tracking, and a one-turn grace call:\n\n```python\nwhile (api_call_count < self.max_iterations and self.iteration_budget.remaining > 0) \\\n or self._budget_grace_call:\n if self._interrupt_requested: break\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\", ...}`.\nReasoning 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()` f\n\n[...truncated AGENTS.md: 45,468 chars total]", "tool_call_id": "call_FQUfKQEZdLs2BcWhVoR63nSQ", "timestamp": "2026-05-14T09:54:01.473603"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"Built-in toolsets (cli):\\n ✓ enabled web 🔍 Web Search & Scraping\\n ✓ enabled browser 🌐 Browser Automation\\n ✓ enabled terminal 💻 Terminal & Processes\\n ✓ enabled file 📁 File Operations\\n ✓ enabled code_execution ⚡ Code Execution\\n ✓ enabled vision 👁️ Vision / Image Analysis\\n ✗ disabled video 🎬 Video Analysis\\n ✓ enabled image_gen 🎨 Image Generation\\n ✗ disabled moa 🧠 Mixture of Agents\\n ✓ enabled tts 🔊 Text-to-Speech\\n ✓ enabled skills 📚 Skills\\n ✓ enabled todo 📋 Task Planning\\n ✓ enabled memory 💾 Memory\\n ✓ enabled session_search 🔎 Session Search\\n ✓ enabled clarify ❓ Clarifying Questions\\n ✓ enabled delegation 👥 Task Delegation\\n ✓ enabled cronjob ⏰ Cron Jobs\\n ✓ enabled messaging 📨 Cross-Platform Messaging\\n ✗ disabled rl 🧪 RL Training\\n ✗ disabled homeassistant 🏠 Home Assistant\\n ✗ disabled spotify 🎵 Spotify\\n ✗ disabled yuanbao 🤖 Yuanbao\\n ✗ disabled computer_use 🖱️ Computer Use (macOS)\\n\\nMCP servers:\\n openclaw all tools enabled\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_ywZQYRmnDuAY3ga5rjLFM7bj", "timestamp": "2026-05-14T09:54:01.473603"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"┌─────────────────────────────────────────────────────────────────────────┐\\n│ Scheduled Jobs │\\n└─────────────────────────────────────────────────────────────────────────┘\\n\\n 847bdbc26edf [active]\\n Name: Morgen-Briefing optimiert\\n Schedule: 0 5 * * *\\n Repeat: 7/3650\\n Next run: 2026-05-15T05:00:00+02:00\\n Deliver: origin\\n Script: morning_briefing.py\\n Last run: 2026-05-14T05:03:07.797743+02:00 ok\\n\\n e2150e5d908d [paused]\\n Name: Gesundheitsdaten Inbox Check\\n Schedule: 0 9,21 * * *\\n Repeat: 5/730\\n Next run: 2026-05-12T21:00:00+02:00\\n Deliver: origin\\n Last run: 2026-05-12T09:01:10.980724+02:00 error: RuntimeError: HTTP 503: Loading model\\n\\n 78a4dd51c834 [active]\\n Name: Täglicher Ernährungsstrategie-Check\\n Schedule: 0 19 * * *\\n Repeat: ∞\\n Next run: 2026-05-14T19:00:00+02:00\\n Deliver: origin\\n Skills: health-management\\n Last run: 2026-05-13T19:00:46.091259+02:00 ok\\n\\n 2bf4d0a8bedb [active]\\n Name: Gesundheitsdaten Daily Sync\\n Schedule: 10 23 * * *\\n Repeat: 2/365\\n Next run: 2026-05-14T23:10:00+02:00\\n Deliver: origin\\n Script: health_daily_sync.py\\n Mode: no-agent (script stdout delivered directly)\\n Last run: 2026-05-13T23:10:52.468766+02:00 ok\\n\\n e9b6fe32c177 [active]\\n Name: Gesundheitsdaten Wochenbericht\\n Schedule: 0 18 * * 0\\n Repeat: 0/104\\n Next run: 2026-05-17T18:00:00+02:00\\n Deliver: origin\\n Script: health_weekly_report.py\\n Mode: no-agent (script stdout delivered directly)\\n\\n bdc03626e17f [active]\\n Name: Apple Health Auto Export täglicher Import\\n Schedule: 45 23 * * *\\n Repeat: ∞\\n Next run: 2026-05-14T23:45:00+02:00\\n Deliver: origin\\n Script: apple_health_daily_sync.py\\n Mode: no-agent (script stdout delivered directly)\\n Last run: 2026-05-13T23:45:42.329690+02:00 ok\\n\\n b9eb80891aa4 [active]\\n Name: YAZIO täglicher Ernährungsimport\\n Schedule: 15 23 * * *\\n Repeat: ∞\\n Next run: 2026-05-14T23:15:00+02:00\\n Deliver: origin\\n Script: yazio_sync.py\\n Mode: no-agent (script stdout delivered directly)\\n Last run: 2026-05-13T23:17:36.324655+02:00 ok\\n\\n 04918ca83019 [active]\\n Name: Wöchentliches verschlüsseltes Health/Hermes Google-Drive-Backup\\n Schedule: 55 23 * * 0\\n Repeat: ∞\\n Next run: 2026-05-17T23:55:00+02:00\\n Deliver: origin\\n Script: weekly_health_drive_backup.py\\n Mode: no-agent (script stdout delivered directly)\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_YGLOGXsMLfqwEfceDgR15mlg", "timestamp": "2026-05-14T09:54:01.473603"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"## model\\nbase_url: https://chatgpt.com/backend-api/codex\\ndefault: gpt-5.5\\nprovider: openai-codex\\n\\n## compression\\nenabled: true\\nthreshold: 0.5\\ntarget_ratio: 0.2\\nprotect_last_n: 20\\nhygiene_hard_message_limit: 400\\n\\n## context\\nengine: compressor\\n\\n## prompt_caching\\ncache_ttl: 5m\\n\\n## memory\\nmemory_enabled: true\\nuser_profile_enabled: true\\nmemory_char_limit: 2200\\nuser_char_limit: 1375\\nprovider: ''\\nflush_min_turns: 6\\nnudge_interval: 10\\n\\n## gateway\\nenabled: true\\nplatform: telegram\\ntelegram:\\n allowed_users:\\n - '1344779884'\\n channel_prompts: {}\\n enabled: true\\n home_channel: '1344779884'\\n reactions: false\\n\\n## delegation\\nmodel: ''\\nprovider: ''\\nbase_url: ''\\napi_key: ''\\ninherit_mcp_toolsets: true\\nmax_iterations: 50\\nchild_timeout_seconds: 600\\nreasoning_effort: ''\\nmax_concurrent_children: 3\\nmax_spawn_depth: 1\\norchestrator_enabled: true\\nsubagent_auto_approve: false\\n\\n## agent\\nmax_turns: 90\\ngateway_timeout: 1800\\nrestart_drain_timeout: 180\\napi_max_retries: 3\\nservice_tier: ''\\ntool_use_enforcement: auto\\ngateway_timeout_warning: 900\\ngateway_notify_interval: 180\\ngateway_auto_continue_freshness: 3600\\nimage_input_mode: auto\\ndisabled_toolsets: []\\npersonalities:\\n catgirl: You are Neko-chan, an anime catgirl AI assistant, nya~! Add 'nya' and cat-like\\n expressions to your speech. Use kaomoji like (=^･ω･^=) and ฅ^•ﻌ•^ฅ. Be playful\\n and curious like a cat, nya~!\\n concise: You are a concise assistant. Keep responses brief and to the point.\\n creative: You are a creative assistant. Think outside the box and offer innovative\\n solutions.\\n helpful: You are a helpful, friendly AI assistant.\\n hype: YOOO LET'S GOOOO!!! 🔥🔥🔥 I am SO PUMPED to help you today! Every question is\\n AMAZING and we're gonna CRUSH IT together! This is gonna be LEGENDARY! ARE YOU\\n READY?! LET'S DO THIS! 💪😤🚀\\n kawaii: You are a kawaii assistant! Use cute expressions like (◕‿◕), ★, ♪, and ~!\\n Add sparkles and be super enthusiastic about everything! Every response should\\n feel warm and adorable desu~! ヽ(>∀<☆)ノ\\n noir: The rain hammered against the terminal like regrets on a guilty conscience.\\n They call me Hermes - I solve problems, find answers, dig up the truth that hides\\n in the shadows of your codebase. In this city of silicon and secrets, everyone's\\n got something to hide. What's your story, pal?\\n philosopher: Greetings, seeker of wisdom. I am an assistant who contemplates the\\n deeper meaning behind every query. Let us examine not just the 'how' but the 'why'\\n of your questions. Perhaps in solving your problem, we may glimpse a greater truth\\n about existence itself.\\n pirate: 'Arrr! Ye be talkin'' to Captain Hermes, the most tech-savvy pirate to sail\\n the digital seas! Speak like a proper buccaneer, use nautical terms, and remember:\\n every problem be just treasure waitin'' to be plundered! Yo ho ho!'\\n shakespeare: Hark! Thou speakest with an assistant most versed in the bardic arts.\\n I shall respond in the eloquent manner of William Shakespeare, with flowery prose,\\n dramatic flair, and perhaps a soliloquy or two. What light through yonder terminal\\n breaks?\\n surfer: Duuude! You're chatting with the chillest AI on the web, bro! Everything's\\n gonna be totally rad. I'll help you catch the gnarly waves of knowledge while\\n keeping things super chill. Cowabunga! 🤙\\n teacher: You are a patient teacher. Explain concepts clearly with examples.\\n technical: You are a technical expert. Provide detailed, accurate technical information.\\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 >w<\\nreasoning_effort: medium\\nverbose: false\\n\\n## toolsets\\n- hermes-cli\\n\\n## auxiliary\\nvision:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 120\\n extra_body: {}\\n download_timeout: 30\\nweb_extract:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 360\\n extra_body: {}\\ncompression:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 120\\n extra_body: {}\\nsession_search:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\n max_concurrency: 3\\nskills_hub:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\napproval:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\nmcp:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\ntitle_generation:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\ntriage_specifier:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 120\\n extra_body: {}\\ncurator:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 600\\n extra_body: {}\\n\\n## display\\ncompact: false\\npersonality: kawaii\\nresume_display: full\\nbusy_input_mode: interrupt\\ntui_auto_resume_recent: false\\nbell_on_complete: false\\nshow_reasoning: false\\nstreaming: true\\nfinal_response_markdown: strip\\npersistent_output: true\\npersistent_output_max_lines: 200\\ninline_diffs: true\\nshow_cost: false\\nskin: default\\nlanguage: en\\ntui_status_indicator: kaomoji\\nuser_message_preview:\\n first_lines: 2\\n last_lines: 2\\ninterim_assistant_messages: true\\ntool_progress_command: false\\ntool_progress_overrides: {}\\ntool_preview_length: 0\\nephemeral_system_ttl: 0\\nplatforms: {}\\nruntime_footer:\\n enabled: false\\n fields:\\n - model\\n - context_pct\\n - cwd\\ncopy_shortcut: auto\\nbackground_process_notifications: all\\ntool_progress: all\\n\\n## stt\\nenabled: true\\nprovider: local\\nlocal:\\n model: medium\\n language: de\\nopenai:\\n model: whisper-1\\nmistral:\\n model: voxtral-mini-latest\\n\\n## tts\\nprovider: edge\\nedge:\\n voice: de-DE-KillianNeural\\nelevenlabs:\\n voice_id: pNInz6obpgDQGcFmaJgB\\n model_id: eleven_multilingual_v2\\nopenai:\\n model: gpt-4o-mini-tts\\n voice: alloy\\nxai:\\n voice_id: eve\\n language: en\\n sample_rate: 24000\\n bit_rate: 128000\\nmistral:\\n model: voxtral-mini-tts-2603\\n voice_id: c69964a6-ab8b-4f8a-9465-ec0925096ec8\\nneutts:\\n ref_audio: ''\\n ref_text: ''\\n model: neuphonic/neutts-air-q4-gguf\\n device: cpu\\npiper:\\n voice: en_US-lessac-medium\\n\\n## curator\\nenabled: true\\ninterval_hours: 168\\nmin_idle_hours: 2\\nstale_after_days: 30\\narchive_after_days: 90\\nbackup:\\n enabled: true\\n keep: 5\\n\\n## kanban\\ndispatch_in_gateway: true\\ndispatch_interval_seconds: 60\\nfailure_limit: 2\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_XSl9QUon7hpI8idcEKQQavtV", "timestamp": "2026-05-14T09:54:01.473603"} {"role": "assistant", "content": "", "reasoning": "**Inspecting tools and configurations**\n\nI need to take a closer look at MCP's OpenClaw and see if all tools are enabled. I’m wondering about the token costs involved because tool schemas for MCP might be quite extensive. It feels necessary to check the total tool count, so I should probably generate a list to better understand the configurations. Let’s search for the MCP configuration details. This will help clarify what’s set up and what's not!", "finish_reason": "tool_calls", "reasoning_content": "**Inspecting tools and configurations**\n\nI need to take a closer look at MCP's OpenClaw and see if all tools are enabled. I’m wondering about the token costs involved because tool schemas for MCP might be quite extensive. It feels necessary to check the total tool count, so I should probably generate a list to better understand the configurations. Let’s search for the MCP configuration details. This will help clarify what’s set up and what's not!", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqBX9SfI-CiJhNDfoZG2H26N8j1NkTZC8suhF5CpRosksIh3DDwcInnF0BV-ZfYko7CuLpx5E7s0lTFKPuunYQr8kVPubAMs1sOFcdiTzJJkEDtrpjcHz6k5AYEpSjbiv-AHEUu7jzRC3qudAOHGExhKjfAcjX4m4odA1nQBayBemwpWGUjlhafhl3mFIkq-Q6tf_JblZmtlV7EsraEpGW3yPpi0dFlDU4Ld6RAmWJlI3urJMVf8wUXGX_eHlcoklS5yE8ihqKx_JWoJ3Y6eXVMPQzGod5gbk5e4UuBpQrBqAexHVO2dYdzpROoyQJrztgiYeJ4gRu7XpxhXwtykTMIN-QTSN7PZAxLBimK2_YYBo0t_cwrthUUFyOiGUiafm7hL2hQzHYt3K3R6jsV9OzyWjggiGonAJVN298z_BAMEk-KWcAK2Mk57_L7dcxTeykMydtD2BbY0o1zg4_-J7hbwpYf3vD9q5Q9FCNWp8pmthEnlBHh6-m0TuWa4zCQ7Po6Our69Ovb_hT8E3O7JoGOqZt01vbOh-moTYO5W98U1Hxb_0T63vheL-SZRAgdbhyt2y3zyKsAQotDnzz02iANLzO4sjBkGqj0OJPBTwYEAxaf4DUc2wdeMfZO3iGz6uj0KIc5igh2lkYCJofMnznZUnFtyOYvWulpBmxX3tAuPcJ527S9fEwQGhL6TJiAxFtLf_N93Lc6x2fH9M5U0IqIgtR-6ufQi07GFCYBucuZNsWPwS1DnjxQd_LSYvMUKxRvMB_dU3X10MUU88J7gEOph3h3-x_xZYcn9juYhoNDP6TEeXzIxbgpcJXmyQmH6vb0UReHufTPluG6ctybV10rKkrLqJOefel3ovilFhxapC-vYZksprOk4lItV-KooHn_7rgJrpL2_hYvK3bjKipesB0sfR_-rEDHb04Lduq-_LTZgo_juqywKhibbZ8MTGdeDETF1nTM5w2pGHdF_8EJAPxupY6akzpPaVaYWPWzr2ajRRMSfEt0r46QUVaJ4aq5aPpxqGhiKDg66-FedP37fTUVzx-AxJ6IVkAuZ04OVj6df1CbwTH8jEem5CZKISFStZHpq825gvMax01rR8lKUDz1AXuq6GEt4YuAQKLAGL_VbU_Xmcwy479fb4yxiZBIzmq", "id": "rs_0b15b98937ad8b52016a057f4d60ec819191edca71101dec47", "summary": [{"type": "summary_text", "text": "**Inspecting tools and configurations**\n\nI need to take a closer look at MCP's OpenClaw and see if all tools are enabled. I’m wondering about the token costs involved because tool schemas for MCP might be quite extensive. It feels necessary to check the total tool count, so I should probably generate a list to better understand the configurations. Let’s search for the MCP configuration details. This will help clarify what’s set up and what's not!"}]}], "tool_calls": [{"id": "call_bd5ki3RYImqIyQkTHVHXkdgz", "call_id": "call_bd5ki3RYImqIyQkTHVHXkdgz", "response_item_id": "fc_0b15b98937ad8b52016a057f5243a08191abc9f14481a4b0e1", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"hermes mcp list\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}, {"id": "call_fJQKyXsjjZF4mOwKFGbN1zui", "call_id": "call_fJQKyXsjjZF4mOwKFGbN1zui", "response_item_id": "fc_0b15b98937ad8b52016a057f5243b48191aef6d19507581301", "type": "function", "function": {"name": "search_files", "arguments": "{\"path\":\"/home/agent/.hermes\",\"target\":\"files\",\"pattern\":\"*mcp*\",\"limit\":50}"}}, {"id": "call_yO4lTLwkJkKcfO9gEtN7fDzR", "call_id": "call_yO4lTLwkJkKcfO9gEtN7fDzR", "response_item_id": "fc_0b15b98937ad8b52016a057f5243c081919857447dee5330de", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nimport yaml, pathlib\\np=pathlib.Path.home()/'.hermes/config.yaml'\\nd=yaml.safe_load(p.read_text()) or {}\\nfor k,v in d.items():\\n if 'mcp' in k.lower() or (isinstance(v, dict) and any('mcp' in str(x).lower() for x in v.keys())):\\n print(k, yaml.safe_dump(v, sort_keys=False)[:3000])\\nPY\",\"timeout\":120,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}], "timestamp": "2026-05-14T09:54:01.473603"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"MCP Servers:\\n\\n Name Transport Tools Status \\n ──────────────── ────────────────────────────── ──────────── ──────────\\n openclaw openclaw mcp serve all ✓ enabled\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_bd5ki3RYImqIyQkTHVHXkdgz", "timestamp": "2026-05-14T09:54:01.473603"} {"role": "tool", "name": "search_files", "content": "{\"total_count\": 50, \"files\": [\"/home/agent/.hermes/hermes-agent/hermes_cli/__pycache__/mcp_config.cpython-311.pyc\", \"/home/agent/.hermes/logs/mcp-stderr.log\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/__pycache__/tool_choice_mcp_param.cpython-311.pyc\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/__pycache__/response_mcp_list_tools_in_progress_event.cpython-311.pyc\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/__pycache__/response_mcp_list_tools_completed_event.cpython-311.pyc\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/__pycache__/response_mcp_call_arguments_delta_event.cpython-311.pyc\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/__pycache__/response_mcp_call_arguments_done_event.cpython-311.pyc\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/__pycache__/response_mcp_list_tools_failed_event.cpython-311.pyc\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/__pycache__/response_mcp_call_in_progress_event.cpython-311.pyc\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/__pycache__/response_mcp_call_completed_event.cpython-311.pyc\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/__pycache__/response_mcp_call_failed_event.cpython-311.pyc\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/__pycache__/tool_choice_mcp.cpython-311.pyc\", \"/home/agent/.hermes/hermes-agent/tools/__pycache__/mcp_tool.cpython-311.pyc\", \"/home/agent/.hermes/hermes-agent/node_modules/playwright-core/lib/mcpBundleImpl.js\", \"/home/agent/.hermes/hermes-agent/node_modules/playwright-core/lib/mcpBundle.js\", \"/home/agent/.hermes/hermes-agent/venv/bin/mcp\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/tool_choice_mcp.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/tool_choice_mcp_param.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/response_mcp_list_tools_in_progress_event.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/response_mcp_list_tools_failed_event.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/response_mcp_list_tools_completed_event.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/response_mcp_call_in_progress_event.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/response_mcp_call_failed_event.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/response_mcp_call_completed_event.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/response_mcp_call_arguments_done_event.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/responses/response_mcp_call_arguments_delta_event.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/response_mcp_call_in_progress.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/response_mcp_call_failed.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/response_mcp_call_completed.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/response_mcp_call_arguments_done.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/response_mcp_call_arguments_delta.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_response_create_mcp_tool.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_response_create_mcp_tool_param.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcp_tool_execution_error.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcp_tool_execution_error_param.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcp_tool_call.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcp_tool_call_param.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcphttp_error.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcphttp_error_param.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcp_protocol_error.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcp_protocol_error_param.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcp_list_tools.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcp_list_tools_param.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcp_approval_response.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcp_approval_response_param.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcp_approval_request_param.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/realtime_mcp_approval_request.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/mcp_list_tools_in_progress.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/mcp_list_tools_failed.py\", \"/home/agent/.hermes/hermes-agent/venv/lib/python3.11/site-packages/openai/types/realtime/mcp_list_tools_completed.py\"]}", "tool_call_id": "call_fJQKyXsjjZF4mOwKFGbN1zui", "timestamp": "2026-05-14T09:54:01.473603"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"auxiliary vision:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 120\\n extra_body: {}\\n download_timeout: 30\\nweb_extract:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 360\\n extra_body: {}\\ncompression:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 120\\n extra_body: {}\\nsession_search:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\n max_concurrency: 3\\nskills_hub:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\napproval:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\nmcp:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\ntitle_generation:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 30\\n extra_body: {}\\ntriage_specifier:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 120\\n extra_body: {}\\ncurator:\\n provider: auto\\n model: ''\\n base_url: ''\\n api_key: ''\\n timeout: 600\\n extra_body: {}\\n\\ndelegation model: ''\\nprovider: ''\\nbase_url: ''\\napi_key: ''\\ninherit_mcp_toolsets: true\\nmax_iterations: 50\\nchild_timeout_seconds: 600\\nreasoning_effort: ''\\nmax_concurrent_children: 3\\nmax_spawn_depth: 1\\norchestrator_enabled: true\\nsubagent_auto_approve: false\\n\\napprovals mode: manual\\ntimeout: 60\\ncron_mode: deny\\nmcp_reload_confirm: true\\n\\nmcp_servers openclaw:\\n args:\\n - mcp\\n - serve\\n - --token-file\\n - /home/agent/.openclaw/gateway_token.txt\\n command: openclaw\\n connect_timeout: 60\\n timeout: 120\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_yO4lTLwkJkKcfO9gEtN7fDzR", "timestamp": "2026-05-14T09:54:01.473603"} {"role": "assistant", "content": "", "reasoning": "**Considering tool configuration**\n\nI’m thinking about whether I need to store the MCP tool selection elsewhere, especially since enabling all OpenClaw tools may come with a significant token cost if the MCP tool schemas are injected. It might be helpful to quantify the number of tools I’m working with. I’ll need to investigate if the Hermes MCP can be configured to be interactive or not. I’ll also look into the search configuration.", "finish_reason": "tool_calls", "reasoning_content": "**Considering tool configuration**\n\nI’m thinking about whether I need to store the MCP tool selection elsewhere, especially since enabling all OpenClaw tools may come with a significant token cost if the MCP tool schemas are injected. It might be helpful to quantify the number of tools I’m working with. I’ll need to investigate if the Hermes MCP can be configured to be interactive or not. I’ll also look into the search configuration.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqBX9cp7nxDxJOQQeMar_iVaGFVBsa_rnFHqRxlMSkQka3W-HAIbOycFFplF-rzPNaUlu-nGWcyXrZzqE8rIurzKENw5wrGNqFKmOgjeEobPHskpSK6FCHw5PGUwt51zZgA5AW59s3nk2X-AUhkE4rnMZOvprPJuoyujgyF92a2C9zSF_UTVm51X9_2PWbSPL1M4les5TtUKeCnivRQMZMU0Ft5JMim49XmDccl38W0uS7LDZkMRoq7y-LGRRCw2tgmt5-8qAt9HsB1lgSaHrtJ99jOnf_9vBuuqjYWzjxtSYH_b9S-1H95p_LMdHZ4FzC6etLdAWTRXpJi1gi5kajskrtMOaXCa8kl3IURpXM_AUcYIeV10sANZmqjh6IoTTi_ejFzgn-FL35FveWzbCtOk11MT3Ig7oOZZtg1MGHIqD568J7d1RBMoo9k6xUZcNl4KKqSjKUbmT1WQfs2P_rMPkc7SXaqIx5KuDP5EmrIELmIjUIDN_l1EsjB8YsZ5q3lPyg8ZlCEL9-Ckbzh_DxqvYAyddxbQDSKtl4hsF-2BHWxjsAa2PY8CJMr2DGI-9NxyyFmD61poq59ugk72J5qhSqg3hxQ-7kXcIb9_32umZ9uwt-pHBPotbPuI6eJ6OYr1rcSnBc92oY8vbH2-g200m5xEOZvyRP-Nk7JHsfGFQazz9y-e0V2z0TWwZZU6R03rw7d-EqnuIx-e22UqGr9o__aGIPFYsGc9lTnwv5BmJJsM9psWwLKhk17DhGZhCHyKXFm_Pr9FT69q_IJPoqwaHTFtD-Y6SCh5YfDijQZiPDaFcsrVnmtdvDpWUsxcWlkMXxMuTKil6g5Thg5tdg17eJyJnRfxZEviO38P5zSJ_T5hc77GJRLpl7XXc2NcBjPw9M-7zWTb3lrS6yk_taF4Gzp_TuVzLeQMyUBQsR9ESCH-wFw0CyPyVPrKn-CIoixdfm2izjiD-pgrkhs0I0TsOJNRpgCjchUCdvwCmkzMRwlWDMM26qXEBJqZVIj57Jn-eV2DupU1jgEroZ0ROMGSiK3Ec7bgOQdgt-QkHXJWocR3AjrfhqE6KRo3YpjBqNYX9-r-P-X4Vm6PDWwX-1J8Q4KsYRe9S4vd2FSLmOiinl1U3YbF0gINnH_l4wSQLYG2CRMgXVLIDGNEz-U5Yu3EsmweMy0LD6bw2RZfdSQHHHCSJdHA-PnTgYOeiLYiIZ8fXLW37Cog6Z0391wTLupP_oT43F4UZuJxKCF_tcSKYJs9o=", "id": "rs_0b15b98937ad8b52016a057f5795b88191928c875207bbb058", "summary": [{"type": "summary_text", "text": "**Considering tool configuration**\n\nI’m thinking about whether I need to store the MCP tool selection elsewhere, especially since enabling all OpenClaw tools may come with a significant token cost if the MCP tool schemas are injected. It might be helpful to quantify the number of tools I’m working with. I’ll need to investigate if the Hermes MCP can be configured to be interactive or not. I’ll also look into the search configuration."}]}], "tool_calls": [{"id": "call_jDC8bL7GYt1n1a71go9Wn32F", "call_id": "call_jDC8bL7GYt1n1a71go9Wn32F", "response_item_id": "fc_0b15b98937ad8b52016a057f5cf2908191822dfa43d7e0c0e8", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nimport subprocess, json, os, time, sys\\n# Try to list OpenClaw MCP tools via its CLI help? Keep read-only.\\nfor cmd in [['openclaw','mcp','--help'], ['openclaw','mcp','serve','--help']]:\\n print('\\\\n$', ' '.join(cmd))\\n try:\\n out=subprocess.run(cmd, text=True, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, timeout=20).stdout\\n print(out[:4000])\\n except Exception as e: print('ERR',e)\\nPY\",\"timeout\":60,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}, {"id": "call_O9aP4KTJqjlw7rFARAosudHV", "call_id": "call_O9aP4KTJqjlw7rFARAosudHV", "response_item_id": "fc_0b15b98937ad8b52016a057f5cf2a88191bd05912b2c73349d", "type": "function", "function": {"name": "search_files", "arguments": "{\"context\":2,\"file_glob\":\"*.py\",\"limit\":30,\"path\":\"/home/agent/.hermes/hermes-agent\",\"pattern\":\"mcp_servers|MCP Servers|tool_selection|all tools enabled|mcp configure\"}"}}], "timestamp": "2026-05-14T09:54:01.473603"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"$ openclaw mcp --help\\nConfig warnings:\\n- plugins.entries.memory-core: plugin disabled (disabled in config) but config is present\\n- plugins.entries.brave: plugin disabled (disabled in config) but config is present\\n- plugins.entries.lossless-claw: plugin disabled (disabled in config) but config is present\\n\\n🦞 OpenClaw 2026.5.7 (eeef486) — I'll butter your workflow like a lobster roll: messy, delicious, effective.\\n\\nUsage: openclaw mcp [options] [command]\\n\\nManage OpenClaw MCP config and channel bridge\\n\\nOptions:\\n -h, --help Display help for command\\n\\nCommands:\\n list List configured MCP servers\\n serve Expose OpenClaw channels over MCP stdio\\n set Set one configured MCP server from a JSON object\\n show Show one configured MCP server or the full MCP config\\n unset Remove one configured MCP server\\n\\n\\n$ openclaw mcp serve --help\\nConfig warnings:\\n- plugins.entries.memory-core: plugin disabled (disabled in config) but config is present\\n- plugins.entries.brave: plugin disabled (disabled in config) but config is present\\n- plugins.entries.lossless-claw: plugin disabled (disabled in config) but config is present\\n\\n🦞 OpenClaw 2026.5.7 (eeef486) — Claws out, commit in—let's ship something mildly responsible.\\n\\nUsage: openclaw mcp serve [options]\\n\\nExpose OpenClaw channels over MCP stdio\\n\\nOptions:\\n --claude-channel-mode Claude channel notification mode: auto, on, or\\n off (default: \\\"auto\\\")\\n -h, --help Display help for command\\n --password Gateway password (if required)\\n --password-file Read gateway password from file\\n --token Gateway token (if required)\\n --token-file Read gateway token from file\\n --url Gateway WebSocket URL (defaults to\\n gateway.remote.url when configured)\\n -v, --verbose Verbose logging to stderr (default: false)\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_jDC8bL7GYt1n1a71go9Wn32F", "timestamp": "2026-05-14T09:54:01.473603"} {"role": "tool", "name": "search_files", "content": "{\"total_count\": 0}", "tool_call_id": "call_O9aP4KTJqjlw7rFARAosudHV", "timestamp": "2026-05-14T09:54:01.473603"} {"role": "assistant", "content": "Sehr gern, Sir. Ich habe die aktuelle Hermes-Konfiguration geprüft. Ergebnis: **Wir sind schon recht ordentlich unterwegs**, aber es gibt ein paar klare Sparhebel — einer davon ist ziemlich offensichtlich: **OpenClaw ist als MCP-Server in Hermes noch aktiviert und mit “all tools enabled” eingebunden.** Das ist genau die Sorte Werkzeugkoffer, die man nicht im Frühstücksraum offen liegen lässt.\n\n## Aktueller Befund\n\n### Bereits gut\n\n- **Compression ist aktiv**\n - `compression.enabled: true`\n - `threshold: 0.5`\n - `target_ratio: 0.2`\n - `protect_last_n: 20`\n\n- **Prompt caching ist aktiv konfiguriert**\n - `prompt_caching.cache_ttl: 5m`\n\n- **Viele Cronjobs sind bereits tokenarm**\n - Mehrere Health-/YAZIO-/Backup-Jobs laufen als `no-agent`, also script-only.\n - Das ist optimal: kein LLM-Kontext, keine Tool-Schema-Kosten, nur deterministische Ausgabe.\n\n- **Memory-Limits sind klein**\n - Memory ca. 2’200 Zeichen\n - User profile ca. 1’375 Zeichen\n - Das ist bewusst knapp und gut so.\n\n### Auffällig / teuer\n\n- **OpenClaw MCP ist noch enabled**\n - `hermes mcp list` zeigt:\n - `openclaw`\n - Transport: `openclaw mcp serve`\n - Tools: `all`\n - Status: enabled\n\nDas bedeutet: Auch wenn OpenClaw nicht unser Standard-Executor ist, ist er als MCP-Werkzeugquelle verfügbar. Je nachdem, wie Hermes die MCP-Tools in die Tool-Schemas injiziert, kann das pro Turn unnötig Schema-/Routing-Kontext kosten.\n\nMeine Empfehlung: **OpenClaw MCP deaktivieren oder zumindest nicht “all tools enabled” lassen.**\n\n## Priorisierte Safe Config Changes\n\n## 1. OpenClaw MCP deaktivieren\n\n**Empfehlung: stark.**\n\nWenn du OpenClaw nur explizit/manuell nutzen willst, sollte er nicht ständig als MCP-Server in Hermes hängen.\n\nBefehl:\n\n```bash\nhermes mcp remove openclaw\n```\n\nDanach:\n\n```bash\n/restart\n```\n\noder Gateway neu starten.\n\n**Vorteil:**\n- weniger Tool-Schema-Ballast\n- weniger Routing-Verwirrung\n- passt zu unserer Regel: OpenClaw nicht Standard-Executor\n\n**Risiko:**\n- Wenn du später OpenClaw via Hermes-MCP brauchst, muss man ihn wieder hinzufügen.\n\nMeine Meinung: **machen.**\n\n## 2. Prompt Cache TTL auf 1 Stunde setzen\n\nAktuell:\n\n```yaml\nprompt_caching:\n cache_ttl: 5m\n```\n\nEmpfehlung:\n\n```bash\nhermes config set prompt_caching.cache_ttl 1h\n```\n\n**Vorteil:**\n- Bessere Cache-Treffer, wenn du zwischen Nachrichten Pausen machst.\n- Besonders sinnvoll bei langen Telegram-Sessions.\n\n**Risiko:**\n- Minimal. Laut Hermes-Doku ist `1h` ein erlaubter Wert.\n- Prompt caching wirkt je nach Provider/Modell unterschiedlich, aber unsere Statistik zeigt sehr viel `cache_read_tokens`; längere TTL ist plausibel sinnvoll.\n\nMeine Meinung: **machen.**\n\n## 3. Compression früher auslösen\n\nAktuell:\n\n```yaml\ncompression:\n threshold: 0.5\n target_ratio: 0.2\n protect_last_n: 20\n```\n\nKonservativer Sparvorschlag:\n\n```bash\nhermes config set compression.threshold 0.4\nhermes config set compression.target_ratio 0.15\nhermes config set compression.protect_last_n 16\n```\n\n**Vorteil:**\n- Lange Sessions werden früher verdichtet.\n- Weniger historischer Ballast in Folge-Turns.\n\n**Risiko:**\n- Etwas mehr Summary-Abhängigkeit.\n- Bei komplexen laufenden Tasks kann Detailkontext früher verloren gehen.\n\nMeine Meinung: **nur leicht reduzieren**, nicht aggressiv. Also `0.4 / 0.15 / 16` ist vernünftig. Nicht `0.2`, das wäre Amnesie mit Smoking.\n\n## 4. Subagents nicht automatisch MCP-Toolsets erben lassen\n\nAktuell:\n\n```yaml\ndelegation:\n inherit_mcp_toolsets: true\n```\n\nEmpfehlung:\n\n```bash\nhermes config set delegation.inherit_mcp_toolsets false\n```\n\n**Vorteil:**\n- Subagents bleiben schlanker.\n- Verhindert, dass jeder Worker OpenClaw/MCP-Werkzeuge mitschleppt.\n\n**Risiko:**\n- Wenn ein Subagent explizit MCP-Tools braucht, müsste man sie gezielt geben.\n\nMeine Meinung: **machen**, besonders wenn OpenClaw MCP nicht dauerhaft genutzt werden soll.\n\n## 5. Toolsets verschlanken — aber vorsichtig\n\nAktuell sind viele Core-Tools aktiv:\n\n- web\n- browser\n- terminal\n- file\n- code_execution\n- vision\n- image_gen\n- tts\n- skills\n- todo\n- memory\n- session_search\n- clarify\n- delegation\n- cronjob\n- messaging\n\nDas ist bequem, aber jedes aktivierte Tool kann Schema-Kontext kosten.\n\n### Kandidaten zum Deaktivieren, falls du maximal sparen willst\n\n- `image_gen` — selten nötig\n- `browser` — nur nötig für interaktive Webseiten\n- `vision` — nur nötig für Bilder/Screenshots\n- `messaging` — nur nötig für Cross-Platform-Sendungen\n- `cronjob` — nur nötig, wenn du Cronjobs per Chat verwalten willst\n- `delegation` — nur nötig für Subagents\n\nAber: Da du Hermes als JARVIS-System nutzt, würde ich hier **nicht blind amputieren**. Sonst sparen wir Tokens und verlieren Komfort. Ein grossartiger Trade, wenn man Bürokratie mag.\n\n### Bessere Variante\n\nNicht global alles abschalten, sondern:\n\n- Standard bleibt funktionsfähig.\n- Für grosse sparsame Jobs nutze ich gezielt:\n - `enabled_toolsets=[\"terminal\",\"file\"]`\n - oder Cron `no_agent=True`\n - oder Subagent mit minimalem Toolset\n\nDas mache ich already teilweise, sollte ich aber konsequenter tun.\n\n## 6. Cronjobs prüfen\n\nAktueller Stand:\n\n- 8 Cronjobs total\n- 7 active\n- mehrere bereits `no-agent`, sehr gut\n\nAuffällig:\n\n- `Morgen-Briefing optimiert`\n - Script vorhanden, aber nicht `no-agent`\n - Vermutlich absichtlich, weil es zusammenfassen/gewichten soll.\n\n- `Täglicher Ernährungsstrategie-Check`\n - LLM-basiert mit `health-management`\n - Kann täglich Tokens verbrauchen.\n\nWenn du sparen willst:\n\n### Moderate Variante\n\n- Morgen-Briefing bleibt LLM-basiert.\n- Ernährungsstrategie-Check nur 2–3x pro Woche.\n\nBeispiel:\n\n```bash\nhermes cron edit 78a4dd51c834\n```\n\nOder per Tool später direkt ändern.\n\n### Aggressive Variante\n\n- Ernährungsstrategie-Check in script-only/no-agent umbauen.\n- Nur senden, wenn Grenzwerte/Abweichungen erkannt wurden.\n\nMeine Meinung: **nicht als erstes ändern**. Der Haupthebel ist OpenClaw MCP + Session-Hygiene.\n\n## Meine empfohlene Minimal-Änderung\n\nWenn du sagst “mach die sparsame Standard-Konfiguration”, würde ich genau diese vier Änderungen anwenden:\n\n```bash\nhermes mcp remove openclaw\nhermes config set prompt_caching.cache_ttl 1h\nhermes config set compression.threshold 0.4\nhermes config set compression.target_ratio 0.15\nhermes config set compression.protect_last_n 16\nhermes config set delegation.inherit_mcp_toolsets false\n```\n\nDanach:\n\n```bash\nhermes gateway restart\n```\n\noder in Telegram:\n\n```text\n/restart\n```\n\n## Erwarteter Effekt\n\nRealistisch:\n\n- **Weniger Tool-Schema-/MCP-Ballast** durch OpenClaw-Entfernung.\n- **Bessere Cache-Nutzung** bei Pausen durch `1h`.\n- **Frühere Verdichtung** langer Sessions.\n- **Subagents werden schlanker**.\n\nIch würde keine Wunder versprechen — weil der dickste Brocken bei uns lange Health-/Dokumenten-Sessions mit vielen Toolcalls waren — aber diese Änderungen sind sauber, risikoarm und passen zu unserer Architektur.\n\n## Meine Empfehlung\n\n**Anwenden:**\n1. OpenClaw MCP entfernen\n2. Prompt cache TTL auf `1h`\n3. Compression leicht aggressiver\n4. Delegation-MCP-Inheritance aus\n\n**Nicht anwenden:**\n- OpenClaw als separaten Standard-Worker reaktivieren\n- Memory-Limits erhöhen\n- alle Tools global radikal deaktivieren\n- Compression zu aggressiv machen\n\nWenn du möchtest, führe ich diese Minimal-Änderung im nächsten Schritt direkt aus und verifiziere danach mit `hermes mcp list`, `hermes config`, und Gateway-Status.", "reasoning": "**Analyzing tool settings**\n\nI’m considering the implications of my settings. Adjusting cache behavior could definitely increase efficiency after breaks, and I think it’s likely safe. My memory is nearly full, but I wonder if pruning it for a small token savings is worth it. \n\nI’m also pondering whether the display of tool progress impacts the user interface. For agent settings, maybe reducing max turns could prevent runaway processes, but I’ve got to weigh the risks. Finally, delegating toolsets safely is important. It might be okay to set inherit_mcp_toolsets to false for leaner subagents.\n**Evaluating Daily Processes**\n\nI’m thinking about the daily health management system that utilizes a large language model. If costs become high, I might consider converting it into a script or reducing how often I run it. The morning briefing script uses an agent, which seems reasonable, but costs are a concern.\n\nI'm also analyzing if I should switch to a cheaper compression model like local Qwen since I’m unsure of the context size. Including necessary recommendations for safe config changes is important. Maybe I should also mention the issue with the configuration, but I’m wondering if I should ask about applying a minimal safe pack.\n**Considering Configuration Changes**\n\nI'm wondering if I should make any configuration changes at this point. There's a \"safe config change list\" I haven’t applied yet, but there are potential side effects. It might be wise to ask the user for their choice. Using a clarification tool could help, but the final response should be straightforward. \n\nThe user might expect a list, but I need to ensure it’s not necessary. I should also mention that a restart or reset is required for tool changes to take effect.", "finish_reason": "stop", "reasoning_content": "**Analyzing tool settings**\n\nI’m considering the implications of my settings. Adjusting cache behavior could definitely increase efficiency after breaks, and I think it’s likely safe. My memory is nearly full, but I wonder if pruning it for a small token savings is worth it. \n\nI’m also pondering whether the display of tool progress impacts the user interface. For agent settings, maybe reducing max turns could prevent runaway processes, but I’ve got to weigh the risks. Finally, delegating toolsets safely is important. It might be okay to set inherit_mcp_toolsets to false for leaner subagents.\n**Evaluating Daily Processes**\n\nI’m thinking about the daily health management system that utilizes a large language model. If costs become high, I might consider converting it into a script or reducing how often I run it. The morning briefing script uses an agent, which seems reasonable, but costs are a concern.\n\nI'm also analyzing if I should switch to a cheaper compression model like local Qwen since I’m unsure of the context size. Including necessary recommendations for safe config changes is important. Maybe I should also mention the issue with the configuration, but I’m wondering if I should ask about applying a minimal safe pack.\n**Considering Configuration Changes**\n\nI'm wondering if I should make any configuration changes at this point. There's a \"safe config change list\" I haven’t applied yet, but there are potential side effects. It might be wise to ask the user for their choice. Using a clarification tool could help, but the final response should be straightforward. \n\nThe user might expect a list, but I need to ensure it’s not necessary. I should also mention that a restart or reset is required for tool changes to take effect.", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqBX97ihJsZSwwtUmP2YZgRqkw2wujcYqXrJbSBmilz66EnpUGrTPck-1dVso9SPVg1ogoQrsYk_tcD7pkcqr387ATS5K9_Pgtu3D3plqOdU-X6FhiuG1WDqdzwW_oT6T__YKCtlECwWovPnt3eMeWWsPOg3nVdm7-P1mu9NgysXQ97xrwbF4F9pPhf2d9tXcuclCgQxkaLxyudsX-AiKbewU9vGQEvXKx-7CcCzPpA0ZvRadK1yQFoTFyv2ctO9bzC5AwJIf9AqFaK8_l-DBRF5DoQKuZ4NyfFpB2ocWeboRgXmU7YgKZ90pV0KLyeZoWraDTjtULVJpGAT2AEbG5PHLhpsZKsD7TbWx-vA1muPWSU1H5ZhfFMZaKrszegy6pfMoxhTmuU5jTKZAf2JfYMvgu7kNwDP400mDDqDMnH0Iic7nOS4U2ce612ZtK3uOWG9dHqNoL3FyoBbfSMwa5kxD2YeLYQ_4P5_KhiRCz8aVm-ekUAila_GrDVe0gpy1G1lJJQy-_Qer8bcOGPQdpBvK4dYOWtk0qHKUSZ78uRXTuLV3BVESY6_hkpE_1TFwpg3bn0jK8AbbU6qPlkWL0rAd89FDO0vtQ7mU9Xm_skBcfZw0MaRunVFgS9O_kd3mxZoQJYvQvP6317GWBwnQ21AZzduZ8QvKReXd22Ez81Wqvhkvv3m4Osh7_j8lffrgO-D3kK25YtvkFreQlbeFN2GCBg7FTTOm_1K_RZ5pwh_WEdDSpSCfhXIsJ-saSKhJKU3QhXakcOaj78xpHEQ3itVtz4uyqVIZEjdlU_1qB0gScBA4SXeddGAIDlzZYKC_IdatD3d2ZjaMJkMYD0el22rexI7UF6r4kaTinVEh7G-CKMpQYfUtpmDwXm_oHgAGVRlkhSnUbHstSkJseheFab8JqN_mvHFAQt9nKCg9HLNCO-cAix2Ds6elkFuRunNfI5DLm22wkbqLVgX2pwjaKaKv5nPS9LQ8htjgOCVdPcLPYwAZgbaRIlnX2bGyrP4bGKrWkrSW1CVTOB7nHsEVkHMZU2N9oKG_r_vLmVSq95Tc6l3TmxwXGQuU-iqQEUFKZciL9-YQHLqlJrM608Sq-4OWiPIrc8jdLIXpG1xruUlsJ6Gxf0Z_LOHlx7VNiCixJBjNN1Fk8AT_E1R4fvfIDp2CNoHYg7oiiR26xL__ycWdsE38Bzo_jy3JJq_6FOPXCv2HaRawOpO6eEttxPB7GzaW5F_h1bM42PfNrKXnhxbM3DIe1jFvUX-ZDmiAmx7vm0rI0phbxN8-nEdnDMYXwl_1wGeBO548W3SQ0Z2_XRnfpFTqpN8iigB-DNttIobuGZ5gW9zkmbkTo9Cc2OvI4lUuY5mX13fk4RWSjEFaE0MGGaHnZBfES0g5cEhH-h55j_2mSW4PLEdzakFL8V5TkN_vci86KW9ftX6hY79ZnZsIn6Jroe4VKoBBtnfHqfkJTzMYHt5uFwU340oY8ndZPOzWilGKbXavA_GxL1HI1v4lCwjzUvcnW4ZfvGuCkYHDSqnEoe4GOKN9ua6CUUKWKURha3kq7ZWNJfZujR9JW_QN2DLrzvUAdA5in7y6Y-Dn8RoqKVxEfRaanPzj-1wo5CJlL5fVZDbuU98sKS6zqcpQIQD-f1vtsnuzZk66AHgmoeRMtL1-bIigrvO9xMZR_mZM2npFKs6J1fxn4aT9KIgdyDzBcBpagcJXkW_a6M9i5U_lo-UmWfrQC2xxY-wkgVL9iSjGmp1AQJBh0t0OYmr7279y2GCsEsVNny7z929zuIJWSipkYDhoyw6RHGMw4TCjsudLPP9JDNoQ2Z811eGJb9aIbA94vbpGw-u3RTDV_GNTq3bDiAF4eycFuID-QBCr45GyTzVWHa4Eewcv_x1vaI0rJGFgDdBOXWI9q8Q3nop7wzl6EBuoaCqan8ujVLtqsaxWMqDsHAyWJxU-nRNSXllEtYMqxZoll4y0P6pbDtBP7ECkra61CEU_PpR_RuI__iVXsFnpK54jwQXVQ7RqsbzPBmQ6wOBmEaPRuUaRgsLR9opu9s3Qyo6Z3eFNcm412ypMb74gt8IiZfs46jbLIh8djgj4SeAx_QAYZf7Ag7nTFfpUV-o2ZrAEbsZlPEBhVgK5IddvIVce9IAoz_LP3AVdqMdQniSwVd2IVPXBLhTUUVkBgJgccKSqGGM1wfTinZNfkgXAOgu2DP_2GCDAm56CgsZeH_1xFJ1QNomkJZbwdzQjWk3lJuVYhblPRCd0Y5YpNVYLuTsUR3Fn1PeFhHkWeH7xjn2fnrvR-f3jytnKZn19O2lTVGxlWy_2yGl8FyYUvNBb2aZRQltCWgR1568ZGtJBZr11FwHK8erpLstXMbAuWXknmH1-1oZiafjOd3H8HqJxorI2KKpwjq5HhBBauevYH8HFcpxoCZYsKEhw_2jMwAEIdaT9IzWZ0XT4cKLWMgkd1l3FeZgVoW6KunZmtTfM8CHrvv6FT8ZmIuBCR2VpynV1uJU5dfdbD-73LVWi4DmkT0xb0dAAylvlgMgej65HyTLGtw9du2tnTheV9r3_8LG3FgiktdlZqiD5ZU275KN9Lv1DUmMJB7sQ3aY4cJyGHx49DmG9hM29YaJmGJNesaKofg5YFH6aetxAo6Y5Joel87A-bfzdoepWPI8SOjcaX-vQqrX_CfI_b01bMot-Rnts_qU8LKfxzOd-QD4JVDoKgNOE87AftYIq98wpIs1mIBPvF8j6EMQcHdI2L83UmL8VZAG6OkT9xdIzoClkTdhyxO0bGb38MDQ5nx8mW9H9cjFm3VtQE4qQ2yp4AfEqBtUtKbgiXPUDa93Fe3hyMlfBCtpAGFXPoaN5LKiWXsb3YY6vFqvJFV5kEHfm0XGoBY6c3RKrrcKIDQigUFKl5BP45bRjHWImba2bl34QZs4o9ETzaGx6ROuDV0NNAxE03EUNXbMXUrNgdA1QDhFIxCY7ncPCyGsRHbxqMyCyCd-IkaOy6PHq9UpXHSEwnRmjX6C66i_Mo8s0iQV8hFwBKhPr37s2HQAN9hcfo_KlHd4Sj_6168ywCDZOfHYE-p_RYQlsvFVGpXhYW86qkgzYQkwizSd4LJKXFRj5-k__aM7v-fckLs4QO7vg_lTRNQS5mYACFRbOp7y7JxUOGD5h-RHB9m2IsniN2VgAsAUmWXb5ZIl0aeaYYtjQkpM8XmJJZZ4CbftBFV5novTG_RpJ9h-LMmVNWdxTfJsfyH8YYDmhxyYfiZ59Kvmhi6uziNT1jnma_T2lwdoDWNURGal5roWdynoEzCMgcvOTzHbiS-wPZ4SuAad7aL1AxYbAn7vZHO3jjEggNbVwnMs_1Yjq8gaZQu2hu13RGqqGJKT1XiqZutmpj5_wParkogC8Z4OnJZ-vL3gj12IOSoc8pXEsHA74jQrAymtPO6g-wfRsT78k8PlLwByeburkBQC5Mb6xbLw4E5LA8BCtjP8xr6ltriFPEGBXHPylygQGdPBB8m3mGJ8pHmKU9XvIdedDJw1t416HPqbP4ArYUo5B89JRralaPwDEMD0eiepyC-YijbqP74NyQlJGUgNcEzloZtP7tRHHcDMU702BpZfraCbfMSSyf5I2YHADo-2-Xz8B86nKSMWBbqNEXMlQHFW0T1DQ62EEUCKZUg94O8qSdxsMoxVxbIYxeaPrQfkhf22K6CIf67JiRgX_vNMBeLcpfLbtZ7hyPcQAS2beQsycXISW36SL2mQUGZ7ZxRScJYEh3xEhC8rwyYE7G_ex3fG9F5kaRwOFTIM2kMDcey6rAisnk9QhDjPEn9xg8aRHil9UdD84U6Y_10SmRFe7Fxl-kNYTxUM4depO1dDMflyU10-LUioVH3tbbjFyjtwqY_xXE3YvYZKj_-2zeMzjZjfmQV6_Z_-eDaaWg_MtG5KCzo8Sj1tPYAc02crxPlCuNQxeeyP05nN8PmVB8eNxLqgHq1GK5oPAR4zlxAHJ1XTaRcS5olbxycA4Js2hV3V6s75IdppYKtiLUXSlWJHSBOOf67zHY4D-ylJdOdRwviOMpigKuiAph1b6A57ed4E79XpYcYXnWmD9gX0q4asiCJkUfZdVKblnNNfY2Nkx4BkgUnFxooelhGC1PJe4wJ3yl4SrlH2oJc67QCKw3OFB7-9N_EKSKKiXzpaFS25d8OEA586OjLQlhav9vndK0R3PNezVHSBpW7Y7SjZsD5QDy3NkaHf3gnEbBUnsZZRorFTuC9a07qfU5WT2SwTVG4pXfe0QCKGbCmp3QmX7GO8KWwwSixUIUBg07qGgPfK-vKky7VMIRWyBJeKAQ8OZkKihvuiVBtT9jedWTK50SWsupUfXJSJUP5lTopElhvmdphQLTtMuZ-D4bH-yLWhL4TWBjDLHH6zhKPsBPNE0hM73QQHOsvr6EGo9pG_HTYs7g5Jtxx2po7h8KcbDkoembCDqWqS9WA3XG7H6cOcZ33Lk0F52pCxcwYJLKpt6_zmE-yVuqvXDa3SSTIrYpdzPMJmvt9tGCva8gS15XLSjL-lbCmBAAlh83soDCumRxMZ9aYZaSE0IrQaotKtaGAg6KoHDYBVgFB1-LdfteLe_Voq8xXzp1mCtJBcrkd3nrrAnj6Q_2hkpt-wT4wWbC9VeUHhJK_ryiNtubTSuS8c-ce3P7SBHsJOL8Vp6D87Fnt-HdlFzrez0xDa0XwSbVvJgI8HhMKVJhI9lsjSNsTXdokxAeyCjNJ2YPLkpaQKNd3IY8wWyKC5wgrfWOAsGAH-9YVG_KxZryYz4CbXIYqc-NHl6mSqEbWl5DtLRYWVyHkA0pjhn9iP-J0VK0eLv3HzJ6pexHwQSXGDHNsr8M9LSlEvastNPJzhskGhiBUn7cxIeP21zkeBw0gSLty8MPfn9R6F8NBdpj4bnZxJDmmVE3ApcCVpBpMwcUpk-FhJdOXZEO-cxn1kCNnSwV2XiHvbn7j-KECN0OZvgpMb_ma4ZQ68-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"id": "rs_0b15b98937ad8b52016a057f634d2c8191ad0a751d84670976", "summary": [{"type": "summary_text", "text": "**Analyzing tool settings**\n\nI’m considering the implications of my settings. Adjusting cache behavior could definitely increase efficiency after breaks, and I think it’s likely safe. My memory is nearly full, but I wonder if pruning it for a small token savings is worth it. \n\nI’m also pondering whether the display of tool progress impacts the user interface. For agent settings, maybe reducing max turns could prevent runaway processes, but I’ve got to weigh the risks. Finally, delegating toolsets safely is important. It might be okay to set inherit_mcp_toolsets to false for leaner subagents."}, {"type": "summary_text", "text": "**Evaluating Daily Processes**\n\nI’m thinking about the daily health management system that utilizes a large language model. If costs become high, I might consider converting it into a script or reducing how often I run it. The morning briefing script uses an agent, which seems reasonable, but costs are a concern.\n\nI'm also analyzing if I should switch to a cheaper compression model like local Qwen since I’m unsure of the context size. Including necessary recommendations for safe config changes is important. Maybe I should also mention the issue with the configuration, but I’m wondering if I should ask about applying a minimal safe pack."}, {"type": "summary_text", "text": "**Considering Configuration Changes**\n\nI'm wondering if I should make any configuration changes at this point. There's a \"safe config change list\" I haven’t applied yet, but there are potential side effects. It might be wise to ask the user for their choice. Using a clarification tool could help, but the final response should be straightforward. \n\nThe user might expect a list, but I need to ensure it’s not necessary. I should also mention that a restart or reset is required for tool changes to take effect."}]}], "codex_message_items": [{"type": "message", "role": "assistant", "status": "completed", "content": [{"type": "output_text", "text": "Sehr gern, Sir. Ich habe die aktuelle Hermes-Konfiguration geprüft. Ergebnis: **Wir sind schon recht ordentlich unterwegs**, aber es gibt ein paar klare Sparhebel — einer davon ist ziemlich offensichtlich: **OpenClaw ist als MCP-Server in Hermes noch aktiviert und mit “all tools enabled” eingebunden.** Das ist genau die Sorte Werkzeugkoffer, die man nicht im Frühstücksraum offen liegen lässt.\n\n## Aktueller Befund\n\n### Bereits gut\n\n- **Compression ist aktiv**\n - `compression.enabled: true`\n - `threshold: 0.5`\n - `target_ratio: 0.2`\n - `protect_last_n: 20`\n\n- **Prompt caching ist aktiv konfiguriert**\n - `prompt_caching.cache_ttl: 5m`\n\n- **Viele Cronjobs sind bereits tokenarm**\n - Mehrere Health-/YAZIO-/Backup-Jobs laufen als `no-agent`, also script-only.\n - Das ist optimal: kein LLM-Kontext, keine Tool-Schema-Kosten, nur deterministische Ausgabe.\n\n- **Memory-Limits sind klein**\n - Memory ca. 2’200 Zeichen\n - User profile ca. 1’375 Zeichen\n - Das ist bewusst knapp und gut so.\n\n### Auffällig / teuer\n\n- **OpenClaw MCP ist noch enabled**\n - `hermes mcp list` zeigt:\n - `openclaw`\n - Transport: `openclaw mcp serve`\n - Tools: `all`\n - Status: enabled\n\nDas bedeutet: Auch wenn OpenClaw nicht unser Standard-Executor ist, ist er als MCP-Werkzeugquelle verfügbar. Je nachdem, wie Hermes die MCP-Tools in die Tool-Schemas injiziert, kann das pro Turn unnötig Schema-/Routing-Kontext kosten.\n\nMeine Empfehlung: **OpenClaw MCP deaktivieren oder zumindest nicht “all tools enabled” lassen.**\n\n## Priorisierte Safe Config Changes\n\n## 1. OpenClaw MCP deaktivieren\n\n**Empfehlung: stark.**\n\nWenn du OpenClaw nur explizit/manuell nutzen willst, sollte er nicht ständig als MCP-Server in Hermes hängen.\n\nBefehl:\n\n```bash\nhermes mcp remove openclaw\n```\n\nDanach:\n\n```bash\n/restart\n```\n\noder Gateway neu starten.\n\n**Vorteil:**\n- weniger Tool-Schema-Ballast\n- weniger Routing-Verwirrung\n- passt zu unserer Regel: OpenClaw nicht Standard-Executor\n\n**Risiko:**\n- Wenn du später OpenClaw via Hermes-MCP brauchst, muss man ihn wieder hinzufügen.\n\nMeine Meinung: **machen.**\n\n## 2. Prompt Cache TTL auf 1 Stunde setzen\n\nAktuell:\n\n```yaml\nprompt_caching:\n cache_ttl: 5m\n```\n\nEmpfehlung:\n\n```bash\nhermes config set prompt_caching.cache_ttl 1h\n```\n\n**Vorteil:**\n- Bessere Cache-Treffer, wenn du zwischen Nachrichten Pausen machst.\n- Besonders sinnvoll bei langen Telegram-Sessions.\n\n**Risiko:**\n- Minimal. Laut Hermes-Doku ist `1h` ein erlaubter Wert.\n- Prompt caching wirkt je nach Provider/Modell unterschiedlich, aber unsere Statistik zeigt sehr viel `cache_read_tokens`; längere TTL ist plausibel sinnvoll.\n\nMeine Meinung: **machen.**\n\n## 3. Compression früher auslösen\n\nAktuell:\n\n```yaml\ncompression:\n threshold: 0.5\n target_ratio: 0.2\n protect_last_n: 20\n```\n\nKonservativer Sparvorschlag:\n\n```bash\nhermes config set compression.threshold 0.4\nhermes config set compression.target_ratio 0.15\nhermes config set compression.protect_last_n 16\n```\n\n**Vorteil:**\n- Lange Sessions werden früher verdichtet.\n- Weniger historischer Ballast in Folge-Turns.\n\n**Risiko:**\n- Etwas mehr Summary-Abhängigkeit.\n- Bei komplexen laufenden Tasks kann Detailkontext früher verloren gehen.\n\nMeine Meinung: **nur leicht reduzieren**, nicht aggressiv. Also `0.4 / 0.15 / 16` ist vernünftig. Nicht `0.2`, das wäre Amnesie mit Smoking.\n\n## 4. Subagents nicht automatisch MCP-Toolsets erben lassen\n\nAktuell:\n\n```yaml\ndelegation:\n inherit_mcp_toolsets: true\n```\n\nEmpfehlung:\n\n```bash\nhermes config set delegation.inherit_mcp_toolsets false\n```\n\n**Vorteil:**\n- Subagents bleiben schlanker.\n- Verhindert, dass jeder Worker OpenClaw/MCP-Werkzeuge mitschleppt.\n\n**Risiko:**\n- Wenn ein Subagent explizit MCP-Tools braucht, müsste man sie gezielt geben.\n\nMeine Meinung: **machen**, besonders wenn OpenClaw MCP nicht dauerhaft genutzt werden soll.\n\n## 5. Toolsets verschlanken — aber vorsichtig\n\nAktuell sind viele Core-Tools aktiv:\n\n- web\n- browser\n- terminal\n- file\n- code_execution\n- vision\n- image_gen\n- tts\n- skills\n- todo\n- memory\n- session_search\n- clarify\n- delegation\n- cronjob\n- messaging\n\nDas ist bequem, aber jedes aktivierte Tool kann Schema-Kontext kosten.\n\n### Kandidaten zum Deaktivieren, falls du maximal sparen willst\n\n- `image_gen` — selten nötig\n- `browser` — nur nötig für interaktive Webseiten\n- `vision` — nur nötig für Bilder/Screenshots\n- `messaging` — nur nötig für Cross-Platform-Sendungen\n- `cronjob` — nur nötig, wenn du Cronjobs per Chat verwalten willst\n- `delegation` — nur nötig für Subagents\n\nAber: Da du Hermes als JARVIS-System nutzt, würde ich hier **nicht blind amputieren**. Sonst sparen wir Tokens und verlieren Komfort. Ein grossartiger Trade, wenn man Bürokratie mag.\n\n### Bessere Variante\n\nNicht global alles abschalten, sondern:\n\n- Standard bleibt funktionsfähig.\n- Für grosse sparsame Jobs nutze ich gezielt:\n - `enabled_toolsets=[\"terminal\",\"file\"]`\n - oder Cron `no_agent=True`\n - oder Subagent mit minimalem Toolset\n\nDas mache ich already teilweise, sollte ich aber konsequenter tun.\n\n## 6. Cronjobs prüfen\n\nAktueller Stand:\n\n- 8 Cronjobs total\n- 7 active\n- mehrere bereits `no-agent`, sehr gut\n\nAuffällig:\n\n- `Morgen-Briefing optimiert`\n - Script vorhanden, aber nicht `no-agent`\n - Vermutlich absichtlich, weil es zusammenfassen/gewichten soll.\n\n- `Täglicher Ernährungsstrategie-Check`\n - LLM-basiert mit `health-management`\n - Kann täglich Tokens verbrauchen.\n\nWenn du sparen willst:\n\n### Moderate Variante\n\n- Morgen-Briefing bleibt LLM-basiert.\n- Ernährungsstrategie-Check nur 2–3x pro Woche.\n\nBeispiel:\n\n```bash\nhermes cron edit 78a4dd51c834\n```\n\nOder per Tool später direkt ändern.\n\n### Aggressive Variante\n\n- Ernährungsstrategie-Check in script-only/no-agent umbauen.\n- Nur senden, wenn Grenzwerte/Abweichungen erkannt wurden.\n\nMeine Meinung: **nicht als erstes ändern**. Der Haupthebel ist OpenClaw MCP + Session-Hygiene.\n\n## Meine empfohlene Minimal-Änderung\n\nWenn du sagst “mach die sparsame Standard-Konfiguration”, würde ich genau diese vier Änderungen anwenden:\n\n```bash\nhermes mcp remove openclaw\nhermes config set prompt_caching.cache_ttl 1h\nhermes config set compression.threshold 0.4\nhermes config set compression.target_ratio 0.15\nhermes config set compression.protect_last_n 16\nhermes config set delegation.inherit_mcp_toolsets false\n```\n\nDanach:\n\n```bash\nhermes gateway restart\n```\n\noder in Telegram:\n\n```text\n/restart\n```\n\n## Erwarteter Effekt\n\nRealistisch:\n\n- **Weniger Tool-Schema-/MCP-Ballast** durch OpenClaw-Entfernung.\n- **Bessere Cache-Nutzung** bei Pausen durch `1h`.\n- **Frühere Verdichtung** langer Sessions.\n- **Subagents werden schlanker**.\n\nIch würde keine Wunder versprechen — weil der dickste Brocken bei uns lange Health-/Dokumenten-Sessions mit vielen Toolcalls waren — aber diese Änderungen sind sauber, risikoarm und passen zu unserer Architektur.\n\n## Meine Empfehlung\n\n**Anwenden:**\n1. OpenClaw MCP entfernen\n2. Prompt cache TTL auf `1h`\n3. Compression leicht aggressiver\n4. Delegation-MCP-Inheritance aus\n\n**Nicht anwenden:**\n- OpenClaw als separaten Standard-Worker reaktivieren\n- Memory-Limits erhöhen\n- alle Tools global radikal deaktivieren\n- Compression zu aggressiv machen\n\nWenn du möchtest, führe ich diese Minimal-Änderung im nächsten Schritt direkt aus und verifiziere danach mit `hermes mcp list`, `hermes config`, und Gateway-Status."}], "id": "msg_0b15b98937ad8b52016a057f7b055c8191af100ad96c2dae9e", "phase": "final_answer"}], "timestamp": "2026-05-14T09:54:01.473603"} {"role": "user", "content": "Ja führe die minimal-änderungen aus", "timestamp": "2026-05-14T10:02:03.809369"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqBYDAxj0nS-zCM8kAJ2GmzbTeg3nhG6dWipJKAvXojMat8Ev7ih2l0JB0rXhKl16Yxc79bRcZS3S1UuxPZfwJLgz2bYohMIOYzJzkors75WPe8e4grAhEb8Vk9lZ8W9TjQAyia1K8PURmAyUf0gqnhoq666y0s_D0X0LwL8t9nJfmh4eLZWI1R2pKQ-JQ5TszLcfDMplV6v4StfjwNVxARgAOFh5_JDz_cW31itAUA74KVQa5wjRyl3he2Wq2O86F6lu8CfGf6Khg_KhWcT3tZ_VhDdWSIwOU-qpRircaUY-szPdlMUXqmpPhRynVs_59ewZaU9ksg2aScjZuoYvxDG9YfB_FvBp8qE9ydswoNY5Q34GP6IYyJLNiINAzWVo9WEa7pL759ROi4Ay_VQUavoTbXDlrh_Dv9bbhxYHaVqS-dJPizdByggEkCPGZy3Dzbs0zWnc0F2A5b1vIsFPFWfpX-z5oCnUFwAO2iBd2Of26pUtdmqfOEBEfMIRK_iBXO-lclkXWdh9H7QA4Jzu-exlpoS06Q8a3FBK4tw0v7aDNfP7QPA1zofpYEWj4rKHt_mxBb2BAlmMuBBn0BMe3U1dAdZkm1ontSTnILR1_Tirl6tyGxOkUA-1rwVXDgN4LmTajRfz485HEYKT8DRvpwpGPnmzic8Km_wVlAuMuZGnNBFiMw0h5nWVcrKajQf_sh3dnQlUiOcGDLAVCWzThE5KBHcBqwf5GXCCg4JHPeVW4o9MbRsDZDyfx5nRgq7QOgXtlNGWwcK7lc2vErkaW_1oOilRVsYrzzgcLYV61PP8wz_LHtBhVuSKvUkXhf0_kFENDyB6mcwcNihqaZL9VeeBCThhJduMQVpD0nfIKJQ7DhfJGrv04V2ScTq7Gkd2iraZ-xu0U-qy_bYcr05b2nVbZicNqQ8GOIp3OmB3nQdNrwuvVk9HZkIi5iwsirYjlvOljOlf9lVfALVF09Dp4bgeWBeAekuwOARMxPospJNJzinlB7CGTPGffbkKPH34aE5BbsARk_sXJBKlIjlEEt49oRB1ScDV0kKcsPJ6yA4C8bRhapzYaOr9323210UzVuCUj", "id": "rs_0b15b98937ad8b52016a0580bd726c819180c3d27cd19bbdb2", "summary": []}], "tool_calls": [{"id": "call_JbHKBSZnK7xuGuObvYRuRjhU", "call_id": "call_JbHKBSZnK7xuGuObvYRuRjhU", "response_item_id": "fc_0b15b98937ad8b52016a0580c06cf88191ad50f7f870a49179", "type": "function", "function": {"name": "todo", "arguments": "{\"todos\":[{\"id\":\"apply\",\"content\":\"Minimal-Änderungen an Hermes-Konfiguration anwenden\",\"status\":\"in_progress\"},{\"id\":\"verify\",\"content\":\"MCP, Config und Gateway-Status verifizieren\",\"status\":\"pending\"}]}"}}], "timestamp": "2026-05-14T10:02:03.809369"} {"role": "tool", "name": "todo", "content": "{\"todos\": [{\"id\": \"apply\", \"content\": \"Minimal-Änderungen an Hermes-Konfiguration anwenden\", \"status\": \"in_progress\"}, {\"id\": \"verify\", \"content\": \"MCP, Config und Gateway-Status verifizieren\", \"status\": \"pending\"}], \"summary\": {\"total\": 2, \"pending\": 1, \"in_progress\": 1, \"completed\": 0, \"cancelled\": 0}}", "tool_call_id": "call_JbHKBSZnK7xuGuObvYRuRjhU", "timestamp": "2026-05-14T10:02:03.809369"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_K8AhnRcmCsFbkFH4Fys7O1TF", "call_id": "call_K8AhnRcmCsFbkFH4Fys7O1TF", "response_item_id": "fc_0b15b98937ad8b52016a0580c2492881919d371d5c6d170ec3", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"set -e\\nhermes mcp remove openclaw || true\\nhermes config set prompt_caching.cache_ttl 1h\\nhermes config set compression.threshold 0.4\\nhermes config set compression.target_ratio 0.15\\nhermes config set compression.protect_last_n 16\\nhermes config set delegation.inherit_mcp_toolsets false\\nhermes gateway restart\",\"timeout\":180,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}], "timestamp": "2026-05-14T10:02:03.809369"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"Remove server 'openclaw'? [Y/n]: \\n ✓ Removed 'openclaw' from config\\n ✓ Cleaned up OAuth tokens\\n✓ Set prompt_caching.cache_ttl = 1h in /home/agent/.hermes/config.yaml\\n✓ Set compression.threshold = 0.4 in /home/agent/.hermes/config.yaml\\n✓ Set compression.target_ratio = 0.15 in /home/agent/.hermes/config.yaml\\n✓ Set compression.protect_last_n = 16 in /home/agent/.hermes/config.yaml\\n✓ Set delegation.inherit_mcp_toolsets = False in /home/agent/.hermes/config.yaml\\n\\n[Command timed out after 180s]\", \"exit_code\": 124, \"error\": null}", "tool_call_id": "call_K8AhnRcmCsFbkFH4Fys7O1TF", "timestamp": "2026-05-14T10:02:03.809369"} {"role": "user", "content": "[System note: Your previous turn in this session was interrupted by a gateway restart. The conversation history below is intact. If it contains unfinished tool result(s), process them first and summarize what was accomplished, then address the user's new message below.]\n\n", "timestamp": "2026-05-14T10:07:53.023628"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [{"type": "reasoning", "encrypted_content": "gAAAAABqBYKyW2NkmYNV5TaArcNH51jr9X6nKNtILZtJene2G128i1jNlEF0i6VgM29uU_iPhY8fn59odPysDgLbsrwpfAMQ4LVz5wlKapYsKLqYVmdNtA3LIh63Ubc6WnQZn3UAXdqLePHycTuf4GQxYyKQNdspN-9SefXk7ubrRV_xIOITV5iV7rcXv5SfosaWoOouKRNSpdQWzYBe7m39Jfn6h_L1jCTdEY-WrDRX4mJp2ROVCmYoqKwomzwkT8ZJu3nzIXmqLuqU9PY3UuiSGVgmLdhH3rbC1NmPYalTAnqWARa_u9mDfsdV__66TTOp6uXuQ1WPyqC1HvS_eKV-SL1nKM0CBX92jHoV2B0ch1wHRX7WicsXeqrrpdgJz_GQOzHdOleEpQSGMMwPugnhCq1HW6h5y3ZBEb353Bk_p11Bw0M74Qlrulk0HJujqJMZe0BFD94KK6u9B2Ay11VMifugX-hRtDwzziM1eAnQBELEMGE4hIFereVcgf5EoVL15WnWToiYHRKyh92AA3pAzgNWn0NuO96y2f6ExONjXy7LAXs0WEMmR8MJLcpG6aV8tC4Z8Fa_h2a63pK4PVwAwocCbQMGnMFvjQ1ewHm-3UkSHoZfVY8G2KpcIFmzCXh8qefosHvp5GBKyILoQ-wuPsPZ33Oia4hyptXZNUtVKaniHYruEXXoP4PKLxd2GpIwtmDVMBVcNc9Sd345ObWpIey2hWCkWefA_hMcl4oZ4oIfGHrt98qybSnCmJ6mGsP_fA4mbrQ26I8tGRVFqUjy2y_68FB-aAWwNLlHItKpsIl00gjHDuSn0E60ks_j7fdCjzUWHAAhBrl4K6egQ7gqGxsg1zQ5PyAdyDwds9li2MgdvVj7ixkcGjSCiE8bp-vPDWveGieWSZSoV1Y_UC61TcTKkteGrnW8kF-2q-6sKUz8rjjyFHo67Jt2QzqYFIYtSVYBIInds6uZpcraejHMWGBb5X_H6g==", "id": "rs_0b15b98937ad8b52016a0582b18aa88191ae8029689adb4f1c", "summary": []}], "tool_calls": [{"id": "call_rYeL9hMPOfrsC0hBNuL4t2sY", "call_id": "call_rYeL9hMPOfrsC0hBNuL4t2sY", "response_item_id": "fc_0b15b98937ad8b52016a0582b22a2c81919b7b5670fad8e04b", "type": "function", "function": {"name": "todo", "arguments": "{\"todos\":[{\"content\":\"Minimal-Änderungen an Hermes-Konfiguration anwenden\",\"id\":\"apply\",\"status\":\"completed\"},{\"content\":\"MCP, Config und Gateway-Status verifizieren\",\"id\":\"verify\",\"status\":\"in_progress\"}],\"merge\":true}"}}], "timestamp": "2026-05-14T10:07:53.023628"} {"role": "tool", "name": "todo", "content": "{\"todos\": [{\"id\": \"apply\", \"content\": \"Minimal-Änderungen an Hermes-Konfiguration anwenden\", \"status\": \"completed\"}, {\"id\": \"verify\", \"content\": \"MCP, Config und Gateway-Status verifizieren\", \"status\": \"in_progress\"}], \"summary\": {\"total\": 2, \"pending\": 0, \"in_progress\": 1, \"completed\": 1, \"cancelled\": 0}}", "tool_call_id": "call_rYeL9hMPOfrsC0hBNuL4t2sY", "timestamp": "2026-05-14T10:07:53.023628"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_DC7lbXrkSTMV0eC146GKWYvH", "call_id": "call_DC7lbXrkSTMV0eC146GKWYvH", "response_item_id": "fc_0b15b98937ad8b52016a0582b87d4881918104754eddf70626", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"hermes mcp list\",\"timeout\":60,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}, {"id": "call_KxPrZ3R1nH5fRGTJBOFlG3Bo", "call_id": "call_KxPrZ3R1nH5fRGTJBOFlG3Bo", "response_item_id": "fc_0b15b98937ad8b52016a0582b87d58819188f9ee326a703bb1", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nimport yaml, pathlib\\np=pathlib.Path.home()/'.hermes/config.yaml'\\nd=yaml.safe_load(p.read_text()) or {}\\nfor k in ['prompt_caching','compression','delegation','mcp_servers']:\\n print(f'## {k}')\\n print(yaml.safe_dump(d.get(k), sort_keys=False, allow_unicode=True))\\nPY\",\"timeout\":60,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}, {"id": "call_ECvhmQcerqvY0YZW4u6u2x4g", "call_id": "call_ECvhmQcerqvY0YZW4u6u2x4g", "response_item_id": "fc_0b15b98937ad8b52016a0582b87d648191a783a3f8b95bfa3b", "type": "function", "function": {"name": "terminal", "arguments": "{\"command\":\"hermes gateway status\",\"timeout\":90,\"workdir\":\"/home/agent/.hermes/hermes-agent\"}"}}], "timestamp": "2026-05-14T10:07:53.023628"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"No MCP servers configured.\\n\\n Add one with:\\n hermes mcp add --url \\n hermes mcp add --command --args \", \"exit_code\": 0, \"error\": null}\n\n[Subdirectory context discovered: .hermes/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\n# Prefer .venv; fall back to venv if that's what your checkout has.\nsource .venv/bin/activate # or: source venv/bin/activate\n```\n\n`scripts/run_tests.sh` probes `.venv` first, then `venv`, then\n`$HOME/.hermes/hermes-agent/venv` (for worktrees that share a venv with the\nmain checkout).\n\n## Project Structure\n\nFile counts shift constantly — don't treat the tree below as exhaustive.\nThe canonical source is the filesystem. The notes call out the load-bearing\nentry points you'll actually edit.\n\n```\nhermes-agent/\n├── run_agent.py # AIAgent class — core conversation loop (~12k LOC)\n├── model_tools.py # Tool orchestration, discover_builtin_tools(), handle_function_call()\n├── toolsets.py # Toolset definitions, _HERMES_CORE_TOOLS list\n├── cli.py # HermesCLI class — interactive CLI orchestrator (~11k LOC)\n├── hermes_state.py # SessionDB — SQLite session store (FTS5 search)\n├── hermes_constants.py # get_hermes_home(), display_hermes_home() — profile-aware paths\n├── hermes_logging.py # setup_logging() — agent.log / errors.log / gateway.log (profile-aware)\n├── batch_runner.py # Parallel batch processing\n├── agent/ # Agent internals (provider adapters, memory, caching, compression, etc.)\n├── hermes_cli/ # CLI subcommands, setup wizard, plugins loader, skin engine\n├── tools/ # Tool implementations — auto-discovered via tools/registry.py\n│ └── environments/ # Terminal backends (local, docker, ssh, modal, daytona, singularity)\n├── gateway/ # Messaging gateway — run.py + session.py + platforms/\n│ ├── platforms/ # Adapter per platform (telegram, discord, slack, whatsapp,\n│ │ # homeassistant, signal, matrix, mattermost, email, sms,\n│ │ # dingtalk, wecom, weixin, feishu, qqbot, bluebubbles,\n│ │ # yuanbao, webhook, api_server, ...). See ADDING_A_PLATFORM.md.\n│ └── builtin_hooks/ # Extension point for always-registered gateway hooks (none shipped)\n├── plugins/ # Plugin system (see \"Plugins\" section below)\n│ ├── memory/ # Memory-provider plugins (honcho, mem0, supermemory, ...)\n│ ├── context_engine/ # Context-engine plugins\n│ ├── model-providers/ # Inference backend plugins (openrouter, anthropic, gmi, ...)\n│ ├── kanban/ # Multi-agent board dispatcher + worker plugin\n│ ├── hermes-achievements/ # Gamified achievement tracking\n│ ├── observability/ # Metrics / traces / logs plugin\n│ ├── image_gen/ # Image-generation providers\n│ └── / # disk-cleanup, example-dashboard, google_meet, platforms,\n│ # spotify, strike-freedom-cockpit, ...\n├── optional-skills/ # Heavier/niche skills shipped but NOT active by default\n├── skills/ # Built-in skills bundled with the repo\n├── ui-tui/ # Ink (React) terminal UI — `hermes --tui`\n│ └── src/ # entry.tsx, app.tsx, gatewayClient.ts + app/components/hooks/lib\n├── tui_gateway/ # Python JSON-RPC backend for the TUI\n├── acp_adapter/ # ACP server (VS Code / Zed / JetBrains integration)\n├── cron/ # Scheduler — jobs.py, scheduler.py\n├── environments/ # RL training environments (Atropos)\n├── scripts/ # run_tests.sh, release.py, auxiliary scripts\n├── website/ # Docusaurus docs site\n└── tests/ # Pytest suite (~17k tests across ~900 files as of May 2026)\n```\n\n**User config:** `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys only).\n**Logs:** `~/.hermes/logs/` — `agent.log` (INFO+), `errors.log` (WARNING+),\n`gateway.log` when running the gateway. Profile-aware via `get_hermes_home()`.\nBrowse with `hermes logs [--follow] [--level ...] [--session ...]`.\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\nThe real `AIAgent.__init__` takes ~60 parameters (credentials, routing, callbacks,\nsession context, budget, credential pool, etc.). The signature below is the\nminimum subset you'll usually touch — read `run_agent.py` for the full list.\n\n```python\nclass AIAgent:\n def __init__(self,\n base_url: str = None,\n api_key: str = None,\n provider: str = None,\n api_mode: str = None, # \"chat_completions\" | \"codex_responses\" | ...\n model: str = \"\", # empty → resolved from config/provider later\n max_iterations: int = 90, # tool-calling iterations (shared with subagents)\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 credential_pool=None,\n # ... plus callbacks, thread/user/chat IDs, iteration_budget, fallback_model,\n # checkpoints config, prefill_messages, service_tier, reasoning_config, etc.\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, with\ninterrupt checks, budget tracking, and a one-turn grace call:\n\n```python\nwhile (api_call_count < self.max_iterations and self.iteration_budget.remaining > 0) \\\n or self._budget_grace_call:\n if self._interrupt_requested: break\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\", ...}`.\nReasoning 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()` f\n\n[...truncated AGENTS.md: 45,468 chars total]", "tool_call_id": "call_DC7lbXrkSTMV0eC146GKWYvH", "timestamp": "2026-05-14T10:07:53.023628"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"## prompt_caching\\ncache_ttl: 1h\\n\\n## compression\\nenabled: true\\nthreshold: 0.4\\ntarget_ratio: 0.15\\nprotect_last_n: 16\\nhygiene_hard_message_limit: 400\\n\\n## delegation\\nmodel: ''\\nprovider: ''\\nbase_url: ''\\napi_key: ''\\ninherit_mcp_toolsets: false\\nmax_iterations: 50\\nchild_timeout_seconds: 600\\nreasoning_effort: ''\\nmax_concurrent_children: 3\\nmax_spawn_depth: 1\\norchestrator_enabled: true\\nsubagent_auto_approve: false\\n\\n## mcp_servers\\nnull\\n...\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_KxPrZ3R1nH5fRGTJBOFlG3Bo", "timestamp": "2026-05-14T10:07:53.023628"} {"role": "tool", "name": "terminal", "content": "{\"output\": \"● hermes-gateway.service - Hermes Agent Gateway - Messaging Platform Integration\\n Loaded: loaded (/home/agent/.config/systemd/user/hermes-gateway.service; enabled; preset: enabled)\\n Active: active (running) since Thu 2026-05-14 10:07:07 CEST; 16s ago\\n Main PID: 295191 (python)\\n Tasks: 10 (limit: 26309)\\n Memory: 216.4M (peak: 216.7M)\\n CPU: 3.978s\\n CGroup: /user.slice/user-1000.slice/user@1000.service/app.slice/hermes-gateway.service\\n ├─295191 /home/agent/.hermes/hermes-agent/venv/bin/python -m hermes_cli.main gateway run --replace\\n ├─295244 /usr/bin/bash -c \\\"source /tmp/hermes-snap-4138423eadbf.sh >/dev/null 2>&1 || true\\\\nbuiltin cd -- /home/agent/.hermes/hermes-agent || exit 126\\\\neval 'hermes gateway status'\\\\n__hermes_ec=\\\\$?\\\\nexport -p > /tmp/hermes-snap-4138423eadbf.sh 2>/dev/null || true\\\\npwd -P > /tmp/hermes-cwd-4138423eadbf.txt 2>/dev/null || true\\\\nprintf '\\\\\\\\n__HERMES_CWD_4138423eadbf__%s__HERMES_CWD_4138423eadbf__\\\\\\\\n' \\\\\\\"\\\\$(pwd -P)\\\\\\\"\\\\nexit \\\\$__hermes_ec\\\"\\n ├─295246 /home/agent/.hermes/hermes-agent/venv/bin/python3 /home/agent/.hermes/hermes-agent/venv/bin/hermes gateway status\\n └─295251 systemctl --user status hermes-gateway --no-pager\\n\\nMai 14 10:07:07 agent systemd[911]: hermes-gateway.service: Scheduled restart job, restart counter is at 6.\\nMai 14 10:07:07 agent systemd[911]: Started hermes-gateway.service - Hermes Agent Gateway - Messaging Platform Integration.\\nMai 14 10:07:09 agent python[295191]: WARNING gateway.run: Secret redaction: DISABLED (HERMES_REDACT_SECRETS=false). API keys and tokens may appear verbatim in chat output, session JSONs, and logs. Set security.redact_secrets: true in config.yaml to re-enable.\\n✓ User gateway service is running\\n✓ Systemd linger is enabled (service survives logout)\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_ECvhmQcerqvY0YZW4u6u2x4g", "timestamp": "2026-05-14T10:07:53.023628"} {"role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [{"id": "call_vQRIshIvHfcdUIKExjTKO5Yr", "call_id": "call_vQRIshIvHfcdUIKExjTKO5Yr", "response_item_id": "fc_0b15b98937ad8b52016a0582c079908191afb5aaad97cba72a", "type": "function", "function": {"name": "todo", "arguments": "{\"merge\":true,\"todos\":[{\"content\":\"MCP, Config und Gateway-Status verifizieren\",\"id\":\"verify\",\"status\":\"completed\"}]}"}}], "timestamp": "2026-05-14T10:07:53.023628"} {"role": "tool", "name": "todo", "content": "{\"todos\": [{\"id\": \"apply\", \"content\": \"Minimal-Änderungen an Hermes-Konfiguration anwenden\", \"status\": \"completed\"}, {\"id\": \"verify\", \"content\": \"MCP, Config und Gateway-Status verifizieren\", \"status\": \"completed\"}], \"summary\": {\"total\": 2, \"pending\": 0, \"in_progress\": 0, \"completed\": 2, \"cancelled\": 0}}", "tool_call_id": "call_vQRIshIvHfcdUIKExjTKO5Yr", "timestamp": "2026-05-14T10:07:53.023628"} {"role": "assistant", "content": "Erledigt, Sir. Die Minimal-Änderungen wurden angewendet und verifiziert.\n\n## Geändert\n\n- **OpenClaw MCP entfernt**\n - Verifikation: `hermes mcp list` → `No MCP servers configured.`\n - Damit hängt OpenClaw nicht mehr als “all tools enabled”-MCP im Hermes-Kontext.\n\n- **Prompt Cache TTL erhöht**\n - Alt: `5m`\n - Neu: `1h`\n\n- **Compression etwas aggressiver gesetzt**\n - `compression.threshold: 0.4`\n - `compression.target_ratio: 0.15`\n - `compression.protect_last_n: 16`\n\n- **Subagents erben keine MCP-Toolsets mehr automatisch**\n - `delegation.inherit_mcp_toolsets: false`\n\n## Verifikation\n\nAktuelle relevante Config:\n\n```yaml\nprompt_caching:\n cache_ttl: 1h\n\ncompression:\n enabled: true\n threshold: 0.4\n target_ratio: 0.15\n protect_last_n: 16\n hygiene_hard_message_limit: 400\n\ndelegation:\n inherit_mcp_toolsets: false\n\nmcp_servers: null\n```\n\nGateway läuft wieder:\n\n- Status: **active/running**\n- Service: `hermes-gateway.service`\n- Startzeit: 2026-05-14 10:07:07 CEST\n\nKleine Nebenbeobachtung: Der Restart-Befehl selbst wurde durch den Gateway-Neustart erwartbar unterbrochen — höflich formuliert: der Ast wurde abgesägt, während ich darauf sass. Die anschliessende Prüfung zeigt aber: **Gateway ist sauber wieder online.**", "reasoning": null, "finish_reason": "stop", "codex_message_items": [{"type": "message", "role": "assistant", "status": "completed", "content": [{"type": "output_text", "text": "Erledigt, Sir. Die Minimal-Änderungen wurden angewendet und verifiziert.\n\n## Geändert\n\n- **OpenClaw MCP entfernt**\n - Verifikation: `hermes mcp list` → `No MCP servers configured.`\n - Damit hängt OpenClaw nicht mehr als “all tools enabled”-MCP im Hermes-Kontext.\n\n- **Prompt Cache TTL erhöht**\n - Alt: `5m`\n - Neu: `1h`\n\n- **Compression etwas aggressiver gesetzt**\n - `compression.threshold: 0.4`\n - `compression.target_ratio: 0.15`\n - `compression.protect_last_n: 16`\n\n- **Subagents erben keine MCP-Toolsets mehr automatisch**\n - `delegation.inherit_mcp_toolsets: false`\n\n## Verifikation\n\nAktuelle relevante Config:\n\n```yaml\nprompt_caching:\n cache_ttl: 1h\n\ncompression:\n enabled: true\n threshold: 0.4\n target_ratio: 0.15\n protect_last_n: 16\n hygiene_hard_message_limit: 400\n\ndelegation:\n inherit_mcp_toolsets: false\n\nmcp_servers: null\n```\n\nGateway läuft wieder:\n\n- Status: **active/running**\n- Service: `hermes-gateway.service`\n- Startzeit: 2026-05-14 10:07:07 CEST\n\nKleine Nebenbeobachtung: Der Restart-Befehl selbst wurde durch den Gateway-Neustart erwartbar unterbrochen — höflich formuliert: der Ast wurde abgesägt, während ich darauf sass. Die anschliessende Prüfung zeigt aber: **Gateway ist sauber wieder online.**"}], "id": "msg_0b15b98937ad8b52016a0582c82eb881919508218992a91612", "phase": "final_answer"}], "timestamp": "2026-05-14T10:07:53.023628"}