Navigate back to the previous page in browser history. Requires browser_navigate to be called first.

Send a raw Chrome DevTools Protocol (CDP) command. Escape hatch for browser operations not covered by browser_navigate, browser_click, browser_console, etc.

**Requires a reachable CDP endpoint.** Available when the user has run '/browser connect' to attach to a running Chrome, or when 'browser.cdp_url' is set in config.yaml. Not currently wired up for cloud backends (Browserbase, Browser Use, Firecrawl) — those expose CDP per session but live-session routing is a follow-up. Camofox is REST-only and will never support CDP. If the tool is in your toolset at all, a CDP endpoint is already reachable.

**CDP method reference:** https://chromedevtools.github.io/devtools-protocol/ — use web_extract on a method's URL (e.g. '/tot/Page/#method-handleJavaScriptDialog') to look up parameters and return shape.

**Common patterns:**
- List tabs: method='Target.getTargets', params={}
- Handle a native JS dialog: method='Page.handleJavaScriptDialog', params={'accept': true, 'promptText': ''}, target_id=<tabId>
- Get all cookies: method='Network.getAllCookies', params={}
- Eval in a specific tab: method='Runtime.evaluate', params={'expression': '...', 'returnByValue': true}, target_id=<tabId>
- Set viewport for a tab: method='Emulation.setDeviceMetricsOverride', params={'width': 1280, 'height': 720, 'deviceScaleFactor': 1, 'mobile': false}, target_id=<tabId>

**Usage rules:**
- Browser-level methods (Target.*, Browser.*, Storage.*): omit target_id and frame_id.
- Page-level methods (Page.*, Runtime.*, DOM.*, Emulation.*, Network.* scoped to a tab): pass target_id from Target.getTargets.
- **Cross-origin iframe scope** (Runtime.evaluate inside an OOPIF, Page.* targeting a frame target, etc.): pass frame_id from the browser_snapshot frame_tree output. This routes through the CDP supervisor's live connection — the only reliable way on Browserbase where stateless CDP calls hit signed-URL expiry.
- Each stateless call (without frame_id) is independent — sessions and event subscriptions do not persist between calls. For stateful workflows, prefer the dedicated browser tools or use frame_id routing.

CDP method name, e.g. 'Target.getTargets', 'Runtime.evaluate', 'Page.handleJavaScriptDialog'.

Method-specific parameters as a JSON object. Omit or pass {} for methods that take no parameters.

Optional. Target/tab ID from Target.getTargets result (each entry's 'targetId'). Use for page-level methods at the top-level tab scope. Mutually exclusive with frame_id.

Optional. Out-of-process iframe (OOPIF) frame_id from browser_snapshot.frame_tree.children[] where is_oopif=true. When set, routes the call through the CDP supervisor's live session for that iframe. Essential for Runtime.evaluate inside cross-origin iframes, especially on Browserbase where fresh per-call CDP connections can't keep up with signed URL rotation. For same-origin iframes, use parent contentWindow/contentDocument from Runtime.evaluate at the top-level page instead.

Timeout in seconds (default 30, max 300).

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.

The element reference from the snapshot (e.g., '@e5', '@e12')

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.

If true, clear the message buffers after reading

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'

Respond to a native JavaScript dialog (alert / confirm / prompt / beforeunload) that is currently blocking the page.

**Workflow:** call ``browser_snapshot`` first — if a dialog is open, it appears in the ``pending_dialogs`` field with ``id``, ``type``, and ``message``. Then call this tool with ``action='accept'`` or ``action='dismiss'``.

**Prompt dialogs:** pass ``prompt_text`` to supply the response string. Ignored for alert/confirm/beforeunload.

**Multiple dialogs:** if more than one dialog is queued (rare — happens when a second dialog fires while the first is still open), pass ``dialog_id`` from the snapshot to disambiguate.

**Availability:** only present when a CDP-capable backend is attached — Browserbase sessions, local Chrome via ``/browser connect``, or ``browser.cdp_url`` in config.yaml. Not available on Camofox (REST-only) or the default Playwright local browser (CDP port is hidden).

'accept' clicks OK / returns the prompt text. 'dismiss' clicks Cancel / returns null from prompt(). For ``beforeunload`` dialogs: 'accept' allows the navigation, 'dismiss' keeps the page.

Response string for a ``prompt()`` dialog. Ignored for other dialog types. Defaults to empty string.

Specific dialog to respond to, from ``browser_snapshot.pending_dialogs[].id``. Required only when multiple dialogs are queued.

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.

Navigate to a URL in the browser. Initializes the session and loads the page. Must be called before other browser tools. For simple information retrieval, prefer web_search or web_extract (faster, cheaper). For plain-text endpoints — URLs ending in .md, .txt, .json, .yaml, .yml, .csv, .xml, raw.githubusercontent.com, or any documented API endpoint — prefer curl via the terminal tool or web_extract; the browser stack is overkill and much slower for these. Use browser tools when you need to interact with a page (click, fill forms, dynamic content). Returns a compact page snapshot with interactive elements and ref IDs — no need to call browser_snapshot separately after navigating.

The URL to navigate to (e.g., 'https://example.com')

Press a keyboard key. Useful for submitting forms (Enter), navigating (Tab), or keyboard shortcuts. Requires browser_navigate to be called first.

Key to press (e.g., 'Enter', 'Tab', 'Escape', 'ArrowDown')

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.

Direction to scroll

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.

If true, returns complete page content. If false (default), returns compact view with interactive elements only.

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.

The element reference from the snapshot (e.g., '@e3')

The text to type into the field

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:<screenshot_path> in your response. Requires browser_navigate to be called first.

What you want to know about the page visually. Be specific about what you're looking for.

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.

clarify

Ask the user a question when you need clarification, feedback, or a decision before proceeding. Supports two modes:

1. **Multiple choice** — provide up to 4 choices. The user picks one or types their own answer via a 5th 'Other' option.
2. **Open-ended** — omit choices entirely. The user types a free-form response.

Use this tool when:
- The task is ambiguous and you need the user to choose an approach
- You want post-task feedback ('How did that work out?')
- You want to offer to save a skill or update memory
- A decision has meaningful trade-offs the user should weigh in on

Do 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.

The question to present to the user.

Choices:
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.

cronjob

Manage scheduled cron jobs with a single compressed tool.

Use action='create' to schedule a new job from a prompt or one or more skills.
Use action='list' to inspect jobs.
Use action='update', 'pause', 'resume', 'remove', or 'run' to manage an existing job.

To 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.

Jobs run in a fresh session with no current-chat context, so prompts must be self-contained.
If skills are provided on create, the future cron run loads those skills in order, then follows the prompt as the task instruction.
On update, passing skills=[] clears attached skills.

NOTE: The agent's final response is auto-delivered to the target. Put the primary
user-facing content in the final response. Cron jobs run autonomously with no user
present — they cannot ask questions or request clarification.

Important safety rule: cron-run sessions should not recursively schedule more cron jobs.

One of: create, list, update, pause, resume, remove, run

Required for update/pause/resume/remove/run

For create: the full self-contained prompt. If skills are also provided, this becomes the task instruction paired with those skills.

For create/update: '30m', 'every 2h', '0 9 * * *', or ISO timestamp

Optional human-friendly name

Optional repeat count. Omit for defaults (once for one-shot, forever for recurring).

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.

Optional ordered list of skill names to load before executing the cron prompt. On update, pass an empty array to clear attached skills.

Optional per-job model override. If provider is omitted, the current main provider is pinned at creation time so the job stays stable.

Provider name (e.g. 'openrouter', 'anthropic', or 'custom:<name>' for a provider defined in custom_providers config — always include the ':<name>' suffix, never pass the bare 'custom'). Omit to use and pin the current provider.

Model name (e.g. 'anthropic/claude-sonnet-4', 'claude-sonnet-4')

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.

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.

REQUIREMENTS when True: ``script`` MUST be set (``prompt`` and ``skills`` are ignored).

DELIVERY 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.

WHEN 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.

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.

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.

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.

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.

TWO MODES (one of 'goal' or 'tasks' is required):
1. Single task: provide 'goal' (+ optional context, toolsets)
2. 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.

WHEN TO USE delegate_task:
- Reasoning-heavy subtasks (debugging, code review, research synthesis)
- Tasks that would flood your context with intermediate data
- Parallel independent workstreams (research A and B simultaneously)

WHEN NOT TO USE (use these instead):
- Mechanical multi-step work with no reasoning needed -> use execute_code
- Single tool call -> just call the tool directly
- Tasks needing user interaction -> subagents cannot use clarify
- 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.

IMPORTANT:
- Subagents have NO memory of your conversation. Pass all relevant info (file paths, error messages, constraints) via the 'context' field.
- 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.
- 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.
- Leaf subagents (role='leaf', the default) CANNOT call: delegate_task, clarify, memory, send_message, execute_code.
- 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.
- Each subagent gets its own terminal session (separate working directory and state).
- Results are always returned as an array, one entry per task.

What the subagent should accomplish. Be specific and self-contained -- the subagent knows nothing about your conversation history.

Background information the subagent needs: file paths, error messages, project structure, constraints. The more specific you are, the better the subagent performs.

Toolsets to enable for this subagent. Default: inherits your enabled toolsets. Available toolsets: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'video_gen', 'vision', 'web', 'yuanbao'. Common patterns: ['terminal', 'file'] for code work, ['web'] for research, ['browser'] for web interaction, ['terminal', 'file', 'web'] for full-stack tasks.

Task goal

Task-specific context

Toolsets for this specific task. Available: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'video_gen', 'vision', 'web', 'yuanbao'. Use 'web' for network access, 'terminal' for shell, 'browser' for web interaction.

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.

Per-task ACP args override. Leave empty unless acp_command is set.

Per-task role override. See top-level 'role' for semantics.

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 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.

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).

Arguments for the ACP command (default: ['--acp', '--stdio']). Only used when acp_command is set. Leave empty unless acp_command is explicitly provided.

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).

Use 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.

Available via `from hermes_tools import ...`:

  web_search(query: str, limit: int = 5) -> dict
    Returns {"data": {"web": [{"url", "title", "description"}, ...]}}
  web_extract(urls: list[str]) -> dict
    Returns {"results": [{"url", "title", "content", "error"}, ...]} where content is markdown
  read_file(path: str, offset: int = 1, limit: int = 500) -> dict
    Lines are 1-indexed. Returns {"content": "...", "total_lines": N}
  write_file(path: str, content: str) -> dict
    Always overwrites the entire file.
  search_files(pattern: str, target="content", path=".", file_glob=None, limit=50) -> dict
    target: "content" (search inside files) or "files" (find files by name). Returns {"matches": [...]}
  patch(path: str, old_string: str, new_string: str, replace_all: bool = False) -> dict
    Replaces old_string with new_string in the file.
  terminal(command: str, timeout=None, workdir=None) -> dict
    Foreground only (no background/pty). Returns {"output": "...", "exit_code": N}

Limits: 5-minute timeout, 50KB stdout cap, max 50 tool calls per script. terminal() is foreground-only (no background or pty).

Scripts 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().

Print your final result to stdout. Use Python stdlib (json, re, math, csv, datetime, collections, etc.) for processing between tool calls.

Also available (no import needed — built into hermes_tools):
  json_parse(text: str) — json.loads with strict=False; use for terminal() output with control chars
  shell_quote(s: str) — shlex.quote(); use when interpolating dynamic strings into shell commands
  retry(fn, max_attempts=3, delay=2) — retry with exponential backoff for transient failures

Python code to execute. Import tools with `from hermes_tools import web_search, terminal, ...` and print your final result to stdout.

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.

The text prompt describing the desired image. Be detailed and descriptive.

The aspect ratio of the generated image. 'landscape' is 16:9 wide, 'portrait' is 16:9 tall, 'square' is 1:1.

Retrieves and queries up-to-date documentation and code examples from Context7 for any programming library or framework.

You must call 'Resolve Context7 Library ID' tool first to obtain the exact Context7-compatible library ID required to use this tool, UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.

Do not call this tool more than 3 times per question.

Exact Context7-compatible library ID (e.g., '/mongodb/docs', '/vercel/next.js', '/supabase/supabase', '/vercel/next.js/v14.3.0-canary.87') retrieved from 'resolve-library-id' or directly from user query in the format '/org/project' or '/org/project/version'.

The question or task you need help with. Be specific and include relevant details. Good: 'How to set up authentication with JWT in Express.js' or 'React useEffect cleanup function examples'. Bad: 'auth' or 'hooks'. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query.

Resolves a package/product name to a Context7-compatible library ID and returns matching libraries.

You MUST call this function before 'Query Documentation' tool to obtain a valid Context7-compatible library ID UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.

Each result includes:
- Library ID: Context7-compatible identifier (format: /org/project)
- Name: Library or package name
- Description: Short summary
- Code Snippets: Number of available code examples
- Source Reputation: Authority indicator (High, Medium, Low, or Unknown)
- Benchmark Score: Quality indicator (100 is the highest score)
- Versions: List of versions if available. Use one of those versions if the user provides a version in their query. The format of the version is /org/project/version.

For best results, select libraries based on name match, source reputation, snippet coverage, benchmark score, and relevance to your use case.

Selection Process:
1. Analyze the query to understand what library/package the user is looking for
2. Return the most relevant match based on:
- Name similarity to the query (exact matches prioritized)
- Description relevance to the query's intent
- Documentation coverage (prioritize libraries with higher Code Snippet counts)
- Source reputation (consider libraries with High or Medium reputation more authoritative)
- Benchmark Score: Quality indicator (100 is the highest score)

Response Format:
- Return the selected library ID in a clearly marked section
- Provide a brief explanation for why this library was chosen
- If multiple good matches exist, acknowledge this but proceed with the most relevant one
- If no good matches exist, clearly state this and suggest query refinements

For ambiguous queries, request clarification before proceeding with a best-guess match.

IMPORTANT: Do not call this tool more than 3 times per question. If you cannot find what you need after 3 calls, use the best result you have.

The question or task you need help with. This is used to rank library results by relevance to what the user is trying to accomplish. The query is sent to the Context7 API for processing. Do not include any sensitive or confidential information such as API keys, passwords, credentials, personal data, or proprietary code in your query.

Library name to search for and retrieve a Context7-compatible library ID. Use the official library name with proper punctuation — e.g., 'Next.js' instead of 'nextjs', 'Customer.io' instead of 'customerio', 'Three.js' instead of 'threejs'.

memory

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.

WHEN TO SAVE (do this proactively, don't wait to be asked):
- User corrects you or says 'remember this' / 'don't do that again'
- User shares a preference, habit, or personal detail (name, role, timezone, coding style)
- You discover something about the environment (OS, installed tools, project structure)
- You learn a convention, API quirk, or workflow specific to this user's setup
- You identify a stable fact that will be useful again in future sessions

PRIORITY: User preferences and corrections > environment facts > procedural knowledge. The most valuable memory prevents the user from having to repeat themselves.

Do NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts.
If you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.

TWO TARGETS:
- 'user': who the user is -- name, role, preferences, communication style, pet peeves
- 'memory': your notes -- environment facts, project conventions, tool quirks, lessons learned

ACTIONS: add (new entry), replace (update existing -- old_text identifies it), remove (delete -- old_text identifies it).

SKIP: trivial/obvious info, things easily re-discovered, raw data dumps, and temporary task state.

The action to perform.

Which memory store: 'memory' for personal notes, 'user' for user profile.

The entry content. Required for 'add' and 'replace'.

Short unique substring identifying the entry to replace or remove.

Route a hard problem through multiple frontier LLMs collaboratively. Makes 5 API calls (4 reference models + 1 aggregator) with maximum reasoning effort — use sparingly for genuinely difficult problems. Best for: complex math, advanced algorithms, multi-step analytical reasoning, problems benefiting from diverse perspectives.

The complex query or problem to solve using multiple AI models. Should be a challenging problem that benefits from diverse perspectives and collaborative reasoning.

patch

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.

REPLACE MODE (mode='replace', default): find a unique string and replace it. REQUIRED PARAMETERS: mode, path, old_string, new_string.
PATCH MODE (mode='patch'): apply V4A multi-file patches for bulk changes. REQUIRED PARAMETERS: mode, patch.

Edit mode. 'replace' (default): requires path + old_string + new_string. 'patch': requires patch content only.

REQUIRED when mode='replace'. File path to edit.

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.

REQUIRED when mode='replace'. Replacement text. Pass empty string '' to delete the matched text.

Replace all occurrences instead of requiring a unique match (default: false)

REQUIRED when mode='patch'. V4A format patch content. Format:
*** Begin Patch
*** Update File: path/to/file
@@ context hint @@
 context line
-removed line
+added line
*** End Patch

process

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).

list poll log wait kill write submit close

Action to perform on background processes

Process session ID (from terminal background output). Required for all actions except 'list'.

Text to send to process stdin (for 'write' and 'submit' actions)

Max seconds to block for 'wait' action. Returns partial output on timeout.

Line offset for 'log' action (default: last 200 lines)

Max lines to return for 'log' action

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.

Path to the file to read (absolute, relative, or ~/path)

Line number to start reading from (1-indexed, default: 1)

Maximum number of lines to read (default: 500, max: 2000)

Search file contents or find files by name. Use this instead of grep/rg/find/ls in terminal. Ripgrep-backed, faster than shell equivalents.

Content search (target='content'): Regex search inside files. Output modes: full matches with line numbers, file paths only, or match counts.

File search (target='files'): Find files by glob pattern (e.g., '*.py', '*config*'). Also use this instead of ls — results sorted by modification time.

Regex pattern for content search, or glob pattern (e.g., '*.py') for file search

'content' searches inside file contents, 'files' searches for files by name

Directory or file to search in (default: current working directory)

Filter files by pattern in grep mode (e.g., '*.py' to only search Python files)

Maximum number of results to return (default: 50)

Skip first N results for pagination (default: 0)

Output format for grep mode: 'content' shows matching lines with line numbers, 'files_only' lists file paths, 'count' shows match counts per file

Number of context lines before and after each match (grep mode only)

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.

TWO MODES:
1. 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.
2. Keyword search (with query): Search for specific topics across all past sessions. Returns LLM-generated summaries of matching sessions.

USE THIS PROACTIVELY when:
- The user says 'we did this before', 'remember when', 'last time', 'as I mentioned'
- The user asks about a topic you worked on before but don't have in current context
- The user references a project, person, or concept that seems familiar but isn't in memory
- You want to check if you've solved a similar problem before
- The user asks 'what did we do about X?' or 'how did we fix Y?'

Don'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.

Search 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.

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).

Optional: only search messages from specific roles (comma-separated). E.g. 'user,assistant' to skip tool outputs.

Max sessions to summarize (default: 3, max: 5).

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.

Actions: 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.

On delete, pass `absorbed_into=<umbrella>` 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.

Create when: complex task succeeded (5+ calls), errors overcome, user-corrected approach worked, non-trivial workflow discovered, or user asks you to remember a procedure.
Update 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.

After difficult/iterative tasks, offer to save as a skill. Skip for simple one-offs. Confirm with user before creating/deleting.

Good skills: trigger conditions, numbered steps with exact commands, pitfalls section, verification steps. Use skill_view() to see format examples.

Pinned skills are protected from deletion only — skill_manage(action='delete') will refuse with a message pointing the user to `hermes curator unpin <name>`. Patches and edits go through on pinned skills so you can still improve them as pitfalls come up; pin only guards against irrecoverable loss.

create patch edit delete write_file remove_file

The action to perform.

Skill name (lowercase, hyphens/underscores, max 64 chars). Must match an existing skill for patch/edit/delete/write_file/remove_file.

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.

Text to find in the file (required for 'patch'). Must be unique unless replace_all=true. Include enough surrounding context to ensure uniqueness.

Replacement text (required for 'patch'). Can be empty string to delete the matched text.

For 'patch': replace all occurrences instead of requiring a unique match (default: false).

Optional category/domain for organizing the skill (e.g., 'devops', 'data-science', 'mlops'). Creates a subdirectory grouping. Only used with 'create'.

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.

Content for the file. Required for 'write_file'.

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.

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.

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').

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.

List available skills (name + description). Use skill_view(name) to load full content.

Optional category filter to narrow results

terminal

Execute shell commands on a Linux environment. Filesystem usually persists between calls.

Do NOT use cat/head/tail to read files — use read_file instead.
Do NOT use grep/rg/find to search — use search_files instead.
Do NOT use ls to list directories — use search_files(target='files') instead.
Do NOT use sed/awk to edit files — use patch instead.
Do NOT use echo/cat heredoc to create files — use write_file instead.
Reserve terminal for: builds, installs, git, processes, scripts, network, package managers, and anything that needs a shell.

Foreground (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.
Background: Set background=true to get a session_id. Two patterns:
  (1) Long-lived processes that never exit (servers, watchers).
  (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.
For 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.
After starting a server, verify readiness with a health check or log signal, then run tests in a separate terminal() call. Avoid blind sleep loops.
Use process(action="poll") for progress checks, process(action="wait") to block until done.
Working directory: Use 'workdir' for per-command cwd.
PTY mode: Set pty=true for interactive CLI tools (Codex, Claude Code, Python REPL).

Do NOT use vim/nano/interactive tools without pty=true — they hang without a pseudo-terminal. Pipe git output to cat if it might page.

The command to execute on the VM

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.

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.

Working directory for this command (absolute path). Defaults to the session working directory.

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.

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.

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.

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.<name>), not model-selected.

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.

Optional custom file path to save the audio. Defaults to ~/.hermes/audio_cache/<timestamp>.mp3

todo

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.

Writing:
- Provide 'todos' array to create/update items
- merge=false (default): replace the entire list with a fresh plan
- merge=true: update existing items by id, add any new ones

Each item: {id: string, content: string, status: pending|in_progress|completed|cancelled}
List order is priority. Only ONE item in_progress at a time.
Mark items completed immediately when done. If something fails, cancel it and add a revised item.

Always returns the full current list.

Task items to write. Omit to read current list.

Unique item identifier

Task description

Current status

true: update existing items by id, add new ones. false (default): replace the entire list.

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.

Image URL (http/https), local file path, or data: URL to load.

Your specific question or request about the image. Optional context the model uses on the next turn after seeing the image.

Extract content from web page URLs. Returns page content in markdown format. Also works with PDF URLs (arxiv papers, documents, etc.) — pass the PDF link directly and it converts to markdown text. Pages under 5000 chars return full markdown; larger pages are LLM-summarized and capped at ~5000 chars per page. Pages over 2M chars are refused. If a URL fails or times out, use the browser tool to access it instead.

List of URLs to extract content from (max 5 URLs per call)

Search the web for information. Returns up to 5 results by default with titles, URLs, and descriptions. The query is passed through to the configured backend, so operators such as site:domain, filetype:pdf, intitle:word, -term, and "exact phrase" may work when the backend supports them.

The search query to look up on the web. You may include backend-supported operators such as site:example.com, filetype:pdf, intitle:word, -term, or "exact phrase".

Maximum number of results to return. Defaults to 5.

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).

Path to the file to write (will be created if it doesn't exist, overwritten if it does)

Complete content to write to the file

Retrieve or update a peer card from Honcho — a curated list of key facts about that peer (name, role, preferences, communication style, patterns). Pass `card` to update; omit `card` to read.  If the card is empty, the result includes a `hint` field explaining why (observation disabled, fresh peer, dialectic layer still warming up, etc.) — this is NOT an error.  Peer cards accumulate over time from observed conversation.

Peer to query. Built-in aliases: 'user' (default), 'ai'. Or pass any peer ID from this workspace.

New peer card as a list of fact strings. Omit to read the current card.

Semantic search over Honcho's stored context about a peer. Returns raw excerpts ranked by relevance — no LLM synthesis. Cheaper and faster than honcho_reasoning. Good when you want to find specific past facts and reason over them yourself.

What to search for in Honcho's memory.

Token budget for returned context (default 800, max 2000).

Ask Honcho a natural language question and get a synthesized answer. Uses Honcho's LLM (dialectic reasoning) — higher cost than honcho_profile or honcho_search. Can query about any peer via alias or explicit peer ID. Pass reasoning_level to control depth: minimal (fast/cheap), low (default), medium, high, max (deep/expensive). Omit for configured default.

A natural language question.

Override the default reasoning depth. Omit to use the configured default (typically low). Guide:
- minimal: quick factual lookups (name, role, simple preference)
- low: straightforward questions with clear answers
- medium: multi-aspect questions requiring synthesis across observations
- high: complex behavioral patterns, contradictions, deep analysis
- max: thorough audit-level analysis, leave no stone unturned

Retrieve full session context from Honcho — summary, peer representation, peer card, and recent messages. No LLM synthesis. Cheaper than honcho_reasoning. Use this to see what Honcho knows about the current conversation and the specified peer.

Optional focus query to filter context. Omit for full session context snapshot.

Write or delete a conclusion about a peer in Honcho's memory. Conclusions are persistent facts that build a peer's profile. You MUST pass exactly one of: `conclusion` (to create) or `delete_id` (to delete). Passing neither is an error. Deletion is only for PII removal — Honcho self-heals incorrect conclusions over time.

A factual statement to persist. Provide this when creating a conclusion. Do not send it together with delete_id.

Conclusion ID to delete for PII removal. Provide this when deleting a conclusion. Do not send it together with conclusion.


[Recent channel messages]
[nachlakes] Hola

[New message]
[nachlakes]


¡Hola, Igna!

Explanation: The user just said "Hola" - this is a simple greeting. I should respond briefly and directly, as per their preferences. No need for anything elaborate.


[Note: model was just switched from deepseek-v4-pro to gpt-5.5 via OpenAI Codex. Adjust your self-identification accordingly.]

[nachlakes] Hola


Hola, Chicho. Acá estoy — ahora corriendo como GPT-5.5 vía OpenAI Codex.


[nachlakes] Che estoy al tanto de que vos como chatgpt 5.5 Ahora a través de codex podes usar imagen 2 vía hermes. Fijate y si no te sale imvesitfa al respecto y activarlo que quiero que trabajemos en algunos edit


Explanation:
**Investigating image generation**

I need to address the user’s request about activating the image generation feature. It seems like I should load the "hermes-agent" to configure and use the Hermes image feature. I'll need to dig a bit deeper into how this works and ensure that everything is set up correctly for the user. Let's explore this together! I wonder what steps I need to take to activate it effectively.


hermes-agent

---
name: hermes-agent
description: Complete guide to using and extending Hermes Agent — CLI usage, setup, configuration, spawning additional agents, gateway platforms, skills, voice, tools, profiles, and a concise contributor reference. Load this skill when helping users configure Hermes, troubleshoot issues, spawn agent instances, or make code contributions.
version: 2.0.0
author: Hermes Agent + Teknium
license: MIT
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]
---

# Hermes Agent

Hermes 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.

What makes Hermes different:

- **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.
- **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.
- **Multi-platform gateway** — the same agent runs on Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Email, and 8+ other platforms with full tool access, not just chat.
- **Provider-agnostic** — swap models and providers mid-workflow without changing anything else. Credential pools rotate across multiple API keys automatically.
- **Profiles** — run multiple independent Hermes instances with isolated configs, sessions, skills, and memory.
- **Extensible** — plugins, MCP servers, custom tools, webhook triggers, cron scheduling, and the full Python ecosystem.

People 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.

**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.

**Docs:** https://hermes-agent.nousresearch.com/docs/

## Quick Start

```bash
# Install
curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash

# Interactive chat (default)
hermes

# Single query
hermes chat -q "What is the capital of France?"

# Setup wizard
hermes setup

# Change model/provider
hermes model

# Check health
hermes doctor
```

---

## CLI Reference

### Global Flags

```
hermes [flags] [command]

  --version, -V             Show version
  --resume, -r SESSION      Resume session by ID or title
  --continue, -c [NAME]     Resume by name, or most recent session
  --worktree, -w            Isolated git worktree mode (parallel agents)
  --skills, -s SKILL        Preload skills (comma-separate or repeat)
  --profile, -p NAME        Use a named profile
  --yolo                    Skip dangerous command approval
  --pass-session-id         Include session ID in system prompt
```

No subcommand defaults to `chat`.

### Chat

```
hermes chat [flags]
  -q, --query TEXT          Single query, non-interactive
  -m, --model MODEL         Model (e.g. anthropic/claude-sonnet-4)
  -t, --toolsets LIST       Comma-separated toolsets
  --provider PROVIDER       Force provider (openrouter, anthropic, nous, etc.)
  -v, --verbose             Verbose output
  -Q, --quiet               Suppress banner, spinner, tool previews
  --checkpoints             Enable filesystem checkpoints (/rollback)
  --source TAG              Session source tag (default: cli)
```

### Configuration

```
hermes setup [section]      Interactive wizard (model|terminal|gateway|tools|agent)
hermes model                Interactive model/provider picker
hermes config               View current config
hermes config edit          Open config.yaml in $EDITOR
hermes config set KEY VAL   Set a config value
hermes config path          Print config.yaml path
hermes config env-path      Print .env path
hermes config check         Check for missing/outdated config
hermes config migrate       Update config with new options
hermes login [--provider P] OAuth login (nous, openai-codex)
hermes logout               Clear stored auth
hermes doctor [--fix]       Check dependencies and config
hermes status [--all]       Show component status
```

### Tools & Skills

```
hermes tools                Interactive tool enable/disable (curses UI)
hermes tools list           Show all tools and status
hermes tools enable NAME    Enable a toolset
hermes tools disable NAME   Disable a toolset

hermes skills list          List installed skills
hermes skills search QUERY  Search the skills hub
hermes skills install ID    Install a skill
hermes skills inspect ID    Preview without installing
hermes skills config        Enable/disable skills per platform
hermes skills check         Check for updates
hermes skills update        Update outdated skills
hermes skills uninstall N   Remove a hub skill
hermes skills publish PATH  Publish to registry
hermes skills browse        Browse all available skills
hermes skills tap add REPO  Add a GitHub repo as skill source
```

### MCP Servers

```
hermes mcp serve            Run Hermes as an MCP server
hermes mcp add NAME         Add an MCP server (--url or --command)
hermes mcp remove NAME      Remove an MCP server
hermes mcp list             List configured servers
hermes mcp test NAME        Test connection
hermes mcp configure NAME   Toggle tool selection
```

### Dashboard (Web UI)

The official Hermes dashboard provides a web UI for managing config, API keys, sessions, cron, skills, and models. It also includes an optional in-browser terminal tab (`--tui`). It binds to localhost by default for security (exposes API keys and config).

```bash
hermes dashboard                      # Start on localhost:9119
hermes dashboard --status             # Check if running
hermes dashboard --stop               # Stop all dashboard processes
hermes dashboard --skip-build         # Skip npm build (use existing dist)
hermes dashboard --tui                # Enable in-browser terminal tab
```

**Exposing externally via Tailscale Funnel:**

The dashboard **rejects any HTTP Host header that doesn't match the bound address**. Since Tailscale Funnel forwards the original domain name as the Host header, a direct funnel to 127.0.0.1:9119 results in 403 errors. The fix is a thin reverse proxy that strips the Host header before forwarding:

```bash
# 1. Start dashboard on localhost
cd ~/.hermes
./hermes-agent/venv/bin/python -m hermes_cli.main dashboard \
  --host 127.0.0.1 --port 9119 --no-open --skip-build &

# 2. Start the Host-header-rewriting proxy (script shipped with this skill)
python3 ~/.hermes/skills/autonomous-ai-agents/hermes-agent/scripts/dashboard-funnel-proxy.py &

# 3. Expose via Tailscale Funnel (dashboard on /, gateway on /gateway/)
tailscale funnel --bg --set-path / http://127.0.0.1:9118/
tailscale funnel --bg --set-path /gateway/ http://127.0.0.1:8080/
```

The dashboard is then accessible at `https://<tailnet-name>.ts.net/`.

**Alternative: nginx reverse proxy** (handles WebSocket upgrade transparently — recommended when you need the Chat tab):
```nginx
# /etc/nginx/sites-enabled/hermes-dashboard
server {
    listen 127.0.0.1:9117;
    server_name _;
    location / {
        proxy_pass http://127.0.0.1:9119;
        proxy_set_header Host 127.0.0.1:9119;
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection "upgrade";
        proxy_read_timeout 86400s;
        proxy_send_timeout 86400s;
        proxy_buffering off;
    }
}
```
Then funnel `/` to nginx instead of the Python proxy:
```bash
tailscale funnel --bg --set-path / http://127.0.0.1:9117/
tailscale funnel --bg --set-path /gateway/ http://127.0.0.1:8080/
```
Restart nginx after config changes: `sudo systemctl reload nginx`.

IMPORTANT: Put the dashboard on the root path `/`, NOT on `/dashboard/`. The dashboard's HTML uses root-relative asset paths (`/assets/`, `/favicon.ico`, `/api/`, `/sessions`, etc.). If you put it under a path prefix like `/dashboard/`, the browser resolves those assets against `/` and they don't reach the dashboard. Moving the existing gateway proxy from `/` to `/gateway/` frees up `/` for the dashboard.

**Pitfalls:**
- The dashboard **refuses** to bind to a non-localhost address without `--insecure`. This is intentional — it exposes API keys and config. Do NOT use `--insecure` on untrusted networks. Always bind to 127.0.0.1 and proxy through Tailscale.
- `tailscale serve` (tailnet-only) and `tailscale funnel` (public internet) are mutually exclusive. Setting up `serve` for an additional path **removes** the `funnel`. Use `funnel --bg --set-path` for all paths if you need public access.
- The dashboard uses a session token embedded in the HTML. No separate login step.
- The proxy script at `scripts/dashboard-funnel-proxy.py` is a stateless Python stdlib HTTP reverse proxy — no dependencies needed.
- **Chat tab WebSocket rejected behind reverse proxy (403):** when the dashboard binds to `127.0.0.1`, `_ws_client_is_allowed()` in `hermes_cli/web_server.py` rejects non-loopback WebSocket clients with a 403. Behind nginx/Tailscale Funnel, the browser's real IP appears as the client, not `127.0.0.1`. Symptom: "events feed disconnected" / "session ended" on `/api/events` and `/api/pty`. **Fix:** bind to `0.0.0.0` with `--insecure` (safe when nginx/Funnel is the only ingress). Full diagnosis in `references/dashboard-ws-reverse-proxy-403.md`.
- The Chat tab requires `--tui` (or `HERMES_DASHBOARD_TUI=1`). Without it, the WebSocket endpoints are disabled entirely (`_DASHBOARD_EMBEDDED_CHAT_ENABLED = False`). Always pass `--tui` when you want the embedded terminal.

### Gateway (Messaging Platforms)

```
hermes gateway run          Start gateway foreground
hermes gateway install      Install as background service
hermes gateway start/stop   Control the service
hermes gateway restart      Restart the service
hermes gateway status       Check status
hermes gateway setup        Configure platforms
```

Supported platforms: Telegram, Discord, Slack, WhatsApp, Signal, Email, SMS, Matrix, Mattermost, Home Assistant, DingTalk, Feishu, WeCom, API Server, Webhooks, Open WebUI.

Platform docs: https://hermes-agent.nousresearch.com/docs/user-guide/messaging/

### Sessions

```
hermes sessions list        List recent sessions
hermes sessions browse      Interactive picker
hermes sessions export OUT  Export to JSONL
hermes sessions rename ID T Rename a session
hermes sessions delete ID   Delete a session
hermes sessions prune       Clean up old sessions (--older-than N days)
hermes sessions stats       Session store statistics
```

### Cron Jobs

```bash
hermes cron list            List jobs (--all for disabled)
hermes cron create SCHED    Create: '30m', 'every 2h', '0 9 * * *'
hermes cron edit ID         Edit schedule, prompt, delivery
hermes cron pause/resume ID Control job state
hermes cron run ID          Trigger on next tick
hermes cron remove ID       Delete a job
hermes cron status          Scheduler status
```

For watching long-running background processes and notifying on completion, see `references/cron-watchdog-pattern.md` for the PID-watch + marker-file pattern.

### Webhooks

```
hermes webhook subscribe N  Create route at /webhooks/<name>
hermes webhook list         List subscriptions
hermes webhook remove NAME  Remove a subscription
hermes webhook test NAME    Send a test POST
```

### Profiles

```
hermes profile list         List all profiles
hermes profile create NAME  Create (--clone, --clone-all, --clone-from)
hermes profile use NAME     Set sticky default
hermes profile delete NAME  Delete a profile
hermes profile show NAME    Show details
hermes profile alias NAME   Manage wrapper scripts
hermes profile rename A B   Rename a profile
hermes profile export NAME  Export to tar.gz
hermes profile import FILE  Import from archive
```

### Credential Pools

```
hermes auth add             Interactive credential wizard
hermes auth list [PROVIDER] List pooled credentials
hermes auth remove P INDEX  Remove by provider + index
hermes auth reset PROVIDER  Clear exhaustion status
```

### Other

```
hermes insights [--days N]  Usage analytics
hermes update               Update to latest version
hermes pairing list/approve/revoke  DM authorization
hermes plugins list/install/remove  Plugin management
hermes honcho setup/status  Honcho memory integration
hermes memory setup/status/off  Memory provider config
hermes completion bash|zsh  Shell completions
hermes acp                  ACP server (IDE integration)
hermes claw migrate         Migrate from OpenClaw
hermes uninstall            Uninstall Hermes
```

---

## Slash Commands (In-Session)

Type these during an interactive chat session.

### Session Control
```
/new (/reset)        Fresh session
/clear               Clear screen + new session (CLI)
/retry               Resend last message
/undo                Remove last exchange
/title [name]        Name the session
/compress            Manually compress context
/stop                Kill background processes
/rollback [N]        Restore filesystem checkpoint
/background <prompt> Run prompt in background
/queue <prompt>      Queue for next turn
/resume [name]       Resume a named session
```

### Configuration
```
/config              Show config (CLI)
/model [name]        Show or change model
/provider            Show provider info
/prompt [text]       View/set system prompt (CLI)
/personality [name]  Set personality
/reasoning [level]   Set reasoning (none|low|medium|high|xhigh|show|hide)
/verbose             Cycle: off → new → all → verbose
/voice [on|off|tts]  Voice mode
/yolo                Toggle approval bypass
/skin [name]         Change theme (CLI)
/statusbar           Toggle status bar (CLI)
```

### Tools & Skills
```
/tools               Manage tools (CLI)
/toolsets            List toolsets (CLI)
/skills              Search/install skills (CLI)
/skill <name>        Load a skill into session
/cron                Manage cron jobs (CLI)
/reload-mcp          Reload MCP servers
/plugins             List plugins (CLI)
```

### Info
```
/help                Show commands
/commands [page]     Browse all commands (gateway)
/usage               Token usage
/insights [days]     Usage analytics
/status              Session info (gateway)
/profile             Active profile info
```

### Exit
```
/quit (/exit, /q)    Exit CLI
```

---

## Key Paths & Config

```
~/.hermes/config.yaml       Main configuration
~/.hermes/.env              API keys and secrets
~/.hermes/skills/           Installed skills
~/.hermes/sessions/         Session transcripts
~/.hermes/logs/             Gateway and error logs
~/.hermes/auth.json         OAuth tokens and credential pools
~/.hermes/hermes-agent/     Source code (if git-installed)
```

Profiles use `~/.hermes/profiles/<name>/` with the same layout.

### Config Sections

Edit with `hermes config edit` or `hermes config set section.key value`.

| Section | Key options |
|---------|-------------|
| `model` | `default`, `provider`, `base_url`, `api_key`, `context_length` |
| `agent` | `max_turns` (90), `tool_use_enforcement` |
| `terminal` | `backend` (local/docker/ssh/modal), `cwd`, `timeout` (180) |
| `compression` | `enabled`, `threshold` (0.50), `target_ratio` (0.20) |
| `display` | `skin`, `tool_progress`, `show_reasoning`, `show_cost` |
| `stt` | `enabled`, `provider` (local/groq/openai) |
| `tts` | `provider` (edge/elevenlabs/openai/kokoro/fish) |
| `memory` | `memory_enabled`, `user_profile_enabled`, `provider` |
| `security` | `tirith_enabled`, `website_blocklist` |
| `delegation` | `model`, `provider`, `max_iterations` (50) |
| `smart_model_routing` | `enabled`, `cheap_model` |
| `checkpoints` | `enabled`, `max_snapshots` (50) |

Full config reference: https://hermes-agent.nousresearch.com/docs/user-guide/configuration

### Providers

18 providers supported. Set via `hermes model` or `hermes setup`.

### Reasoning effort gotcha

Hermes' persistent reasoning setting lives at `agent.reasoning_effort` in `~/.hermes/config.yaml`.

Use one of these:
```bash
hermes config set agent.reasoning_effort xhigh
```
Or inside Hermes:
```text
/reasoning xhigh
```

Do not rely on a top-level config key like `OPENAI_REASONING_EFFORT: xhigh` for Hermes CLI/gateway behavior. Hermes reads `agent.reasoning_effort`, not that top-level key.

Also, reasoning support is model/provider-specific:
- OpenAI Codex / GPT-5 Responses-style models: effort values like `low|medium|high|xhigh` can apply.
- OpenRouter models that expose effort controls: effort can apply.
- DeepSeek and some Kimi/Moonshot models: reasoning is selected by choosing a thinking/reasoner model variant, not by an effort dropdown.
- Some Mistral models only support a reasoning toggle, not `xhigh`.
- Web UI may clamp or clear unsupported effort values per model/provider.

So `agent.reasoning_effort: xhigh` is a good global default, but it will only be honored by models/providers that actually support effort-style reasoning.

| Provider | Auth | Key env var |
|----------|------|-------------|
| OpenRouter | API key | `OPENROUTER_API_KEY` |
| Anthropic | API key | `ANTHROPIC_API_KEY` |
| Nous Portal | OAuth | `hermes login --provider nous` |
| OpenAI Codex | OAuth | `hermes login --provider openai-codex` |
| GitHub Copilot | Token | `COPILOT_GITHUB_TOKEN` |
| DeepSeek | API key | `DEEPSEEK_API_KEY` |
| Hugging Face | Token | `HF_TOKEN` |
| Z.AI / GLM | API key | `GLM_API_KEY` |
| MiniMax | API key | `MINIMAX_API_KEY` |
| Kimi / Moonshot | API key | `KIMI_API_KEY` |
| Alibaba / DashScope | API key | `DASHSCOPE_API_KEY` |
| Kilo Code | API key | `KILOCODE_API_KEY` |
| Custom endpoint | Config | `model.base_url` + `model.api_key` in config.yaml |

Plus: AI Gateway, OpenCode Zen, OpenCode Go, MiniMax CN, GitHub Copilot ACP.

Full provider docs: https://hermes-agent.nousresearch.com/docs/integrations/providers

### Toolsets

Enable/disable via `hermes tools` (interactive) or `hermes tools enable/disable NAME`.

| Toolset | What it provides |
|---------|-----------------|
| `web` | Web search and content extraction |
| `browser` | Browser automation (Browserbase, Camofox, or local Chromium) |
| `terminal` | Shell commands and process management |
| `file` | File read/write/search/patch |
| `code_execution` | Sandboxed Python execution |
| `vision` | Image analysis |
| `image_gen` | AI image generation |
| `tts` | Text-to-speech |
| `skills` | Skill browsing and management |
| `memory` | Persistent cross-session memory |
| `session_search` | Search past conversations |
| `delegation` | Subagent task delegation |
| `cronjob` | Scheduled task management |
| `clarify` | Ask user clarifying questions |
| `moa` | Mixture of Agents (off by default) |
| `homeassistant` | Smart home control (off by default) |

Tool changes take effect on `/reset` (new session). They do NOT apply mid-conversation to preserve prompt caching.

---

## Voice & Transcription

### STT (Voice → Text)

Voice messages from messaging platforms are auto-transcribed.

Provider priority (auto-detected):
1. **Local faster-whisper** — free, no API key: `pip install faster-whisper`
2. **Groq Whisper** — free tier: set `GROQ_API_KEY`
3. **OpenAI Whisper** — paid: set `VOICE_TOOLS_OPENAI_KEY`

Config:
```yaml
stt:
  enabled: true
  provider: local        # local, groq, openai
  local:
    model: base          # tiny, base, small, medium, large-v3
```

### TTS (Text → Voice)

| Provider | Env var | Free? |
|----------|---------|-------|
| Edge TTS | None | Yes (default) |
| ElevenLabs | `ELEVENLABS_API_KEY` | Free tier |
| OpenAI | `VOICE_TOOLS_OPENAI_KEY` | Paid |
| Kokoro (local) | None | Free |
| Fish Audio | `FISH_AUDIO_API_KEY` | Free tier |

Voice commands: `/voice on` (voice-to-voice), `/voice tts` (always voice), `/voice off`.

---

## Spawning Additional Hermes Instances

Run additional Hermes processes as fully independent subprocesses — separate sessions, tools, and environments.

### When to Use This vs delegate_task

| | `delegate_task` | Spawning `hermes` process |
|-|-----------------|--------------------------|
| Isolation | Separate conversation, shared process | Fully independent process |
| Duration | Minutes (bounded by parent loop) | Hours/days |
| Tool access | Subset of parent's tools | Full tool access |
| Interactive | No | Yes (PTY mode) |
| Use case | Quick parallel subtasks | Long autonomous missions |

### One-Shot Mode

```
terminal(command="hermes chat -q 'Research GRPO papers and write summary to ~/research/grpo.md'", timeout=300)

# Background for long tasks:
terminal(command="hermes chat -q 'Set up CI/CD for ~/myapp'", background=true)
```

### Interactive PTY Mode (via tmux)

Hermes uses prompt_toolkit, which requires a real terminal. Use tmux for interactive spawning:

```
# Start
terminal(command="tmux new-session -d -s agent1 -x 120 -y 40 'hermes'", timeout=10)

# Wait for startup, then send a message
terminal(command="sleep 8 && tmux send-keys -t agent1 'Build a FastAPI auth service' Enter", timeout=15)

# Read output
terminal(command="sleep 20 && tmux capture-pane -t agent1 -p", timeout=5)

# Send follow-up
terminal(command="tmux send-keys -t agent1 'Add rate limiting middleware' Enter", timeout=5)

# Exit
terminal(command="tmux send-keys -t agent1 '/exit' Enter && sleep 2 && tmux kill-session -t agent1", timeout=10)
```

### Multi-Agent Coordination

```
# Agent A: backend
terminal(command="tmux new-session -d -s backend -x 120 -y 40 'hermes -w'", timeout=10)
terminal(command="sleep 8 && tmux send-keys -t backend 'Build REST API for user management' Enter", timeout=15)

# Agent B: frontend
terminal(command="tmux new-session -d -s frontend -x 120 -y 40 'hermes -w'", timeout=10)
terminal(command="sleep 8 && tmux send-keys -t frontend 'Build React dashboard for user management' Enter", timeout=15)

# Check progress, relay context between them
terminal(command="tmux capture-pane -t backend -p | tail -30", timeout=5)
terminal(command="tmux send-keys -t frontend 'Here is the API schema from the backend agent: ...' Enter", timeout=5)
```

### Session Resume

```
# Resume most recent session
terminal(command="tmux new-session -d -s resumed 'hermes --continue'", timeout=10)

# Resume specific session
terminal(command="tmux new-session -d -s resumed 'hermes --resume 20260225_143052_a1b2c3'", timeout=10)
```

### Tips

- **Prefer `delegate_task` for quick subtasks** — less overhead than spawning a full process
- **Use `-w` (worktree mode)** when spawning agents that edit code — prevents git conflicts
- **Set timeouts** for one-shot mode — complex tasks can take 5-10 minutes
- **Use `hermes chat -q` for fire-and-forget** — no PTY needed
- **Use tmux for interactive sessions** — raw PTY mode has `\r` vs `\n` issues with prompt_toolkit
- **For scheduled tasks**, use the `cronjob` tool instead of spawning — handles delivery and retry

---

## Troubleshooting

### Voice not working
1. Check `stt.enabled: true` in config.yaml
2. Verify provider: `pip install faster-whisper` or set API key
3. Restart gateway: `/restart`

### Tool not available
1. `hermes tools` — check if toolset is enabled for your platform
2. Some tools need env vars (check `.env`)
3. `/reset` after enabling tools

### Model/provider issues
1. `hermes doctor` — check config and dependencies
2. `hermes login` — re-authenticate OAuth providers
3. Check `.env` has the right API key

### Changes not taking effect
- **Tools/skills:** `/reset` starts a new session with updated toolset
- **Config changes:** `/restart` reloads gateway config
- **Code changes:** Restart the CLI or gateway process

### Skills not showing
1. `hermes skills list` — verify installed
2. `hermes skills config` — check platform enablement
3. Load explicitly: `/skill name` or `hermes -s name`

### `hermes update` hit a merge conflict

Symptoms: gateway fails with `SyntaxError: expected 'except' or 'finally' block` in `api_server.py`, or `git status` shows `both modified` files.

Root cause: local customizations (e.g., custom API endpoints, method renames) were stashed before the update, then re-applied on top of refactored upstream code, leaving conflict markers (`<<<<<<< Updated upstream`) in source files.

Fix:
```bash
cd ~/.hermes/hermes-agent
# Check for conflict markers:
grep -rn "<<<<<<\|======\|>>>>>>" gateway/
# Discard stale local changes:
git checkout -- gateway/platforms/api_server.py gateway/platforms/discord.py gateway/run.py
# Also clean .orig files and clear pycache:
find gateway/ -name '*.orig' -delete
find . -type d -name '__pycache__' -exec rm -rf {} + 2>/dev/null
# Restart:
hermes gateway run --replace
```

To preserve local customizations across updates:
- Don't let `hermes update` auto-restore the stash — review the diff first with `git stash show -p stash@{0}`
- If the upstream already includes your changes, drop the stash entirely
- For persistent local patches, consider a fork or document them as patches to re-apply after update

### Gateway issues
Check logs first:
```bash
grep -i "failed to send\\|error" ~/.hermes/logs/gateway.log | tail -20
```

---

## Where to Find Things

| Looking for... | Location |
|----------------|----------|
| Config options | `hermes config edit` or [Configuration docs](https://hermes-agent.nousresearch.com/docs/user-guide/configuration) |
| Available tools | `hermes tools list` or [Tools reference](https://hermes-agent.nousresearch.com/docs/reference/tools-reference) |
| Slash commands | `/help` in session or [Slash commands reference](https://hermes-agent.nousresearch.com/docs/reference/slash-commands) |
| Skills catalog | `hermes skills browse` or [Skills catalog](https://hermes-agent.nousresearch.com/docs/reference/skills-catalog) |
| Provider setup | `hermes model` or [Providers guide](https://hermes-agent.nousresearch.com/docs/integrations/providers) |
| Platform setup | `hermes gateway setup` or [Messaging docs](https://hermes-agent.nousresearch.com/docs/user-guide/messaging/) |
| MCP servers | `hermes mcp list` or [MCP guide](https://hermes-agent.nousresearch.com/docs/user-guide/features/mcp) |
| Profiles | `hermes profile list` or [Profiles docs](https://hermes-agent.nousresearch.com/docs/user-guide/profiles) |
| Cron jobs | `hermes cron list` or [Cron docs](https://hermes-agent.nousresearch.com/docs/user-guide/features/cron) |
| Memory | `hermes memory status` or [Memory docs](https://hermes-agent.nousresearch.com/docs/user-guide/features/memory) |
| Env variables | `hermes config env-path` or [Env vars reference](https://hermes-agent.nousresearch.com/docs/reference/environment-variables) |
| CLI commands | `hermes --help` or [CLI reference](https://hermes-agent.nousresearch.com/docs/reference/cli-commands) |
| Gateway logs | `~/.hermes/logs/gateway.log` |
| Session files | `~/.hermes/sessions/` or `hermes sessions browse` |
| Source code | `~/.hermes/hermes-agent/` |

---

## Contributor Quick Reference

For occasional contributors and PR authors. Full developer docs: https://hermes-agent.nousresearch.com/docs/developer-guide/

### Project Layout

```
hermes-agent/
├── run_agent.py          # AIAgent — core conversation loop
├── model_tools.py        # Tool discovery and dispatch
├── toolsets.py           # Toolset definitions
├── cli.py                # Interactive CLI (HermesCLI)
├── hermes_state.py       # SQLite session store
├── agent/                # Prompt builder, compression, display, adapters
├── hermes_cli/           # CLI subcommands, config, setup, commands
│   ├── commands.py       # Slash command registry (CommandDef)
│   ├── config.py         # DEFAULT_CONFIG, env var definitions
│   └── main.py           # CLI entry point and argparse
├── tools/                # One file per tool
│   └── registry.py       # Central tool registry
├── gateway/              # Messaging gateway
│   └── platforms/        # Platform adapters (telegram, discord, etc.)
├── cron/                 # Job scheduler
├── tests/                # ~3000 pytest tests
└── website/              # Docusaurus docs site
```

Config: `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys).

### Adding a Tool (3 files)

**1. Create `tools/your_tool.py`:**
```python
import json, os
from tools.registry import registry

def check_requirements() -> bool:
    return bool(os.getenv("EXAMPLE_API_KEY"))

def example_tool(param: str, task_id: str = None) -> str:
    return json.dumps({"success": True, "data": "..."})

registry.register(
    name="example_tool",
    toolset="example",
    schema={"name": "example_tool", "description": "...", "parameters": {...}},
    handler=lambda args, **kw: example_tool(
        param=args.get("param", ""), task_id=kw.get("task_id")),
    check_fn=check_requirements,
    requires_env=["EXAMPLE_API_KEY"],
)
```

**2. Add import** in `model_tools.py` → `_discover_tools()` list.

**3. Add to `toolsets.py`** → `_HERMES_CORE_TOOLS` list.

All handlers must return JSON strings. Use `get_hermes_home()` for paths, never hardcode `~/.hermes`.

### Adding a Slash Command

1. Add `CommandDef` to `COMMAND_REGISTRY` in `hermes_cli/commands.py`
2. Add handler in `cli.py` → `process_command()`
3. (Optional) Add gateway handler in `gateway/run.py`

All consumers (help text, autocomplete, Telegram menu, Slack mapping) derive from the central registry automatically.

### Agent Loop (High Level)

```
run_conversation():
  1. Build system prompt
  2. Loop while iterations < max:
     a. Call LLM (OpenAI-format messages + tool schemas)
     b. If tool_calls → dispatch each via handle_function_call() → append results → continue
     c. If text response → return
  3. Context compression triggers automatically near token limit
```

### Testing

```bash
source venv/bin/activate  # or .venv/bin/activate
python -m pytest tests/ -o 'addopts=' -q   # Full suite
python -m pytest tests/tools/ -q            # Specific area
```

- Tests auto-redirect `HERMES_HOME` to temp dirs — never touch real `~/.hermes/`
- Run full suite before pushing any change
- Use `-o 'addopts='` to clear any baked-in pytest flags

### Commit Conventions

```
type: concise subject line

Optional body.
```

Types: `fix:`, `feat:`, `refactor:`, `docs:`, `chore:`

### Key Rules

- **Never break prompt caching** — don't change context, tools, or system prompt mid-conversation
- **Message role alternation** — never two assistant or two user messages in a row
- Use `get_hermes_home()` from `hermes_constants` for all paths (profile-safe)
- Config values go in `config.yaml`, secrets go in `.env`
- New tools need a `check_fn` so they only appear when requirements are met

To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'


Explanation:
**Investigating image tools**

I need to check if the image_generate tool is already available since the user mentioned imagen2 via Hermes, which might involve the tool's backend. It seems I have access to the image_generate tool. Maybe I should test it? I’ll also need to activate the image_gen toolset for Discord if it’s not turned on yet. I’ll explore the configuration and see if I can find details about Imagen 2 or OpenRouter using the terminal.

terminal

hermes tools list | grep -i -E 'image|vision|gen' || true


{"output": "✓ enabled  vision  👁  Vision / Image Analysis\n  ✓ enabled  image_gen  🎨 Image Generation\n  ✗ disabled  video_gen  🎬 Video Generation\n  ✓ enabled  moa  🧠 Mixture of Agents", "exit_code": 0, "error": null}

[Subdirectory context discovered: hermes-agent/AGENTS.md]
# Hermes Agent - Development Guide

Instructions for AI coding assistants and developers working on the hermes-agent codebase.

## Development Environment

```bash
# Prefer .venv; fall back to venv if that's what your checkout has.
source .venv/bin/activate   # or: source venv/bin/activate
```

`scripts/run_tests.sh` probes `.venv` first, then `venv`, then
`$HOME/.hermes/hermes-agent/venv` (for worktrees that share a venv with the
main checkout).

## Project Structure

File counts shift constantly — don't treat the tree below as exhaustive.
The canonical source is the filesystem. The notes call out the load-bearing
entry points you'll actually edit.

```
hermes-agent/
├── run_agent.py          # AIAgent class — core conversation loop (~12k LOC)
├── model_tools.py        # Tool orchestration, discover_builtin_tools(), handle_function_call()
├── toolsets.py           # Toolset definitions, _HERMES_CORE_TOOLS list
├── cli.py                # HermesCLI class — interactive CLI orchestrator (~11k LOC)
├── hermes_state.py       # SessionDB — SQLite session store (FTS5 search)
├── hermes_constants.py   # get_hermes_home(), display_hermes_home() — profile-aware paths
├── hermes_logging.py     # setup_logging() — agent.log / errors.log / gateway.log (profile-aware)
├── batch_runner.py       # Parallel batch processing
├── agent/                # Agent internals (provider adapters, memory, caching, compression, etc.)
├── hermes_cli/           # CLI subcommands, setup wizard, plugins loader, skin engine
├── tools/                # Tool implementations — auto-discovered via tools/registry.py
│   └── environments/     # Terminal backends (local, docker, ssh, modal, daytona, singularity)
├── gateway/              # Messaging gateway — run.py + session.py + platforms/
│   ├── platforms/        # Adapter per platform (telegram, discord, slack, whatsapp,
│   │                     #   homeassistant, signal, matrix, mattermost, email, sms,
│   │                     #   dingtalk, wecom, weixin, feishu, qqbot, bluebubbles,
│   │                     #   yuanbao, webhook, api_server, ...). See ADDING_A_PLATFORM.md.
│   └── builtin_hooks/    # Extension point for always-registered gateway hooks (none shipped)
├── plugins/              # Plugin system (see "Plugins" section below)
│   ├── memory/           # Memory-provider plugins (honcho, mem0, supermemory, ...)
│   ├── context_engine/   # Context-engine plugins
│   ├── model-providers/  # Inference backend plugins (openrouter, anthropic, gmi, ...)
│   ├── kanban/           # Multi-agent board dispatcher + worker plugin
│   ├── hermes-achievements/  # Gamified achievement tracking
│   ├── observability/    # Metrics / traces / logs plugin
│   ├── image_gen/        # Image-generation providers
│   └── <others>/         # disk-cleanup, example-dashboard, google_meet, platforms,
│                         #   spotify, strike-freedom-cockpit, ...
├── optional-skills/      # Heavier/niche skills shipped but NOT active by default
├── skills/               # Built-in skills bundled with the repo
├── ui-tui/               # Ink (React) terminal UI — `hermes --tui`
│   └── src/              # entry.tsx, app.tsx, gatewayClient.ts + app/components/hooks/lib
├── tui_gateway/          # Python JSON-RPC backend for the TUI
├── acp_adapter/          # ACP server (VS Code / Zed / JetBrains integration)
├── cron/                 # Scheduler — jobs.py, scheduler.py
├── environments/         # RL training environments (Atropos)
├── scripts/              # run_tests.sh, release.py, auxiliary scripts
├── website/              # Docusaurus docs site
└── tests/                # Pytest suite (~17k tests across ~900 files as of May 2026)
```

**User config:** `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys only).
**Logs:** `~/.hermes/logs/` — `agent.log` (INFO+), `errors.log` (WARNING+),
`gateway.log` when running the gateway. Profile-aware via `get_hermes_home()`.
Browse with `hermes logs [--follow] [--level ...] [--session ...]`.

## File Dependency Chain

```
tools/registry.py  (no deps — imported by all tool files)
       ↑
tools/*.py  (each calls registry.register() at import time)
       ↑
model_tools.py  (imports tools/registry + triggers tool discovery)
       ↑
run_agent.py, cli.py, batch_runner.py, environments/
```

---

## AIAgent Class (run_agent.py)

The real `AIAgent.__init__` takes ~60 parameters (credentials, routing, callbacks,
session context, budget, credential pool, etc.). The signature below is the
minimum subset you'll usually touch — read `run_agent.py` for the full list.

```python
class AIAgent:
    def __init__(self,
        base_url: str = None,
        api_key: str = None,
        provider: str = None,
        api_mode: str = None,              # "chat_completions" | "codex_responses" | ...
        model: str = "",                   # empty → resolved from config/provider later
        max_iterations: int = 90,          # tool-calling iterations (shared with subagents)
        enabled_toolsets: list = None,
        disabled_toolsets: list = None,
        quiet_mode: bool = False,
        save_trajectories: bool = False,
        platform: str = None,              # "cli", "telegram", etc.
        session_id: str = None,
        skip_context_files: bool = False,
        skip_memory: bool = False,
        credential_pool=None,
        # ... plus callbacks, thread/user/chat IDs, iteration_budget, fallback_model,
        # checkpoints config, prefill_messages, service_tier, reasoning_config, etc.
    ): ...

    def chat(self, message: str) -> str:
        """Simple interface — returns final response string."""

    def run_conversation(self, user_message: str, system_message: str = None,
                         conversation_history: list = None, task_id: str = None) -> dict:
        """Full interface — returns dict with final_response + messages."""
```

### Agent Loop

The core loop is inside `run_conversation()` — entirely synchronous, with
interrupt checks, budget tracking, and a one-turn grace call:

```python
while (api_call_count < self.max_iterations and self.iteration_budget.remaining > 0) \
        or self._budget_grace_call:
    if self._interrupt_requested: break
    response = client.chat.completions.create(model=model, messages=messages, tools=tool_schemas)
    if response.tool_calls:
        for tool_call in response.tool_calls:
            result = handle_function_call(tool_call.name, tool_call.args, task_id)
            messages.append(tool_result_message(result))
        api_call_count += 1
    else:
        return response.content
```

Messages follow OpenAI format: `{"role": "system/user/assistant/tool", ...}`.
Reasoning content is stored in `assistant_msg["reasoning"]`.

---

## CLI Architecture (cli.py)

- **Rich** for banner/panels, **prompt_toolkit** for input with autocomplete
- **KawaiiSpinner** (`agent/display.py`) — animated faces during API calls, `┊` activity feed for tool results
- `load_cli_config()` in cli.py merges hardcoded defaults + user config YAML
- **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
- `process_command()` is a method on `HermesCLI` — dispatches on canonical command name resolved via `resolve_command()` from the central registry
- Skill slash commands: `agent/skill_commands.py` scans `~/.hermes/skills/`, injects as **user message** (not system prompt) to preserve prompt caching

### Slash Command Registry (`hermes_cli/commands.py`)

All slash commands are defined in a central `COMMAND_REGISTRY` list of `CommandDef` objects. Every downstream consumer derives from this registry automatically:

- **CLI** — `process_command()` resolves aliases via `resolve_command()`, dispatches on canonical name
- **Gateway** — `GATEWAY_KNOWN_COMMANDS` frozenset for hook emission, `resolve_command()` f

[...truncated AGENTS.md: 50,073 chars total]


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