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), or platform:chat_id:thread_id for a specific destination. Examples: 'telegram:-1001234567890:17585', 'discord:#engineering', 'sms:+15551234567'. WARNING: 'platform:chat_id' without :thread_id loses topic targeting.

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 delegation.max_concurrent_children items (default 3, configurable via config.yaml, no hard ceiling). All run concurrently and results are returned together. Nested delegation requires role='orchestrator' and delegation.max_spawn_depth >= 2.

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 delegation.max_spawn_depth (default 2) 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', '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.

Task goal

Task-specific context

Toolsets for this specific task. Available: 'browser', '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.

Per-task ACP command override (e.g. 'claude'). Overrides the top-level acp_command for this task only.

Per-task ACP args override.

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

Batch mode: tasks to run in parallel (limit configurable via delegation.max_concurrent_children, default 3). 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. Requires delegation.max_spawn_depth >= 2 in config; ignored (treated as 'leaf') when the child would exceed max_spawn_depth or when delegation.orchestrator_enabled=false.

Override ACP command for child agents (e.g. 'claude', 'copilot'). When set, children use ACP subprocess transport instead of inheriting the parent's transport. Enables spawning Claude Code (claude --acp --stdio) or other ACP-capable agents from any parent, including Discord/Telegram/CLI.

Arguments for the ACP command (default: ['--acp', '--stdio']). Only used when acp_command is set. Example: ['--acp', '--stdio', '--model', 'claude-opus-4-6']

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 ...`:

  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 terminal, ...` and print your final result to stdout.

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.

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 (default): find a unique string and replace it.
Patch mode: apply V4A multi-file patches for bulk changes.

Edit mode: 'replace' for targeted find-and-replace, 'patch' for V4A multi-file patches

File path to edit (required for 'replace' mode)

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

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

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

V4A format patch content (required for 'patch' mode). 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)

Send a message to a connected messaging platform, or list available targets.

IMPORTANT: 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.
If the user just says a platform name like 'send to telegram', send directly to the home channel without listing first.

Action to perform. 'send' (default) sends a message. 'list' returns all available channels/contacts across connected platforms.

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:<account_id>' (DM), 'yuanbao:group:<group_code>' (group chat)

The message text to send. To send an image or file, include MEDIA:<local_path> (e.g. 'MEDIA:/tmp/hermes/cache/img_xxx.jpg') in the message — the platform will deliver it as a native media attachment.

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.

Inspect an image from a URL, file path, or tool output when you need closer detail than what's visible in the conversation. If the user's image is already attached to the conversation and you can see it, just answer directly — only call this tool for images referenced by URL/path, images returned inside other tool results (browser screenshots, search thumbnails), or when you need a deeper look at a specific region the main model's vision may have missed.

Image URL (http/https) or local file path to analyze.

Your specific question or request about the image to resolve. The AI will automatically provide a complete image description AND answer your specific question.

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


Zu dem cronjob: bitte halte callkeep kürzer und sage mir wirklich nur wen ich heute anrufen muss, sonst nichts.


Explanation:
The user wants me to find and update a cron job related to "callkeep" - they want it to be shorter, only telling them who they need to call today, nothing else.

Let me first list the cron jobs and also check session history for context about this callkeep cron job.

Question: callkeep cronjob


cronjob

Morgenbriefing 9:30

Morgenbriefing für den Chef (Zeyd). Führe folgende Schritte aus:

1. **Kalender:** Rufe den Google K...

Abend-Check 20:00

Abend-Check für den Chef (Zeyd). Führe folgende Schritte aus:

1. **CallKeep Telefonate prüfen:** Ru...


Question: callkeep cronjob

Summary:
**Summary: CallKeep Deployment & Cronjob Setup on ZimaOS**

**1. What the user wanted to accomplish**
The user needed the CallKeep Docker container rebuilt and redeployed on a ZimaOS/CasaOS server (192.168.178.171) after code changes to `main.py` and `frontend/index.html`. The app had to run as a managed CasaOS app, not a "Legacy App". Additionally, the user asked the assistant to take over daily CallKeep management (adding contacts, logging calls, sending reminders) and requested two automated cronjobs: a morning update at 11:00 showing who to call, and an evening check at 21:00 asking whether calls were completed.

**2. Actions taken and outcomes**
- **Deployment (multiple attempts):** The assistant initially rebuilt the image using bare `docker` commands, which caused CasaOS to flag the container as a "Legacy App". The correct workflow was established: stop/remove the old container, then build and start via `docker compose` from the CasaOS app directory so ZimaOS tracks it properly.
- **Successful rebuild:** The image was rebuilt with the current source code, the container `CallKeep` was started on port 3002, and verification showed HTTP 200, `/api/options` returning only `frequencies` and `directions` (no moods/relationships), and the `summary` column present in the SQLite database.
- **Data check:** The database at `/media/HDD_1TB/CallKeep/callkeep.db` was preserved across rebuilds, though test contacts were lost in one early cycle before the compose-based workflow was fixed.
- **Contact & call management:** The assistant created a contact named "Anneanne" (ID 9, weekly frequency) and logged test calls via `POST /api/kiwi/log-call`, including one with a summary ("Oma geht es gut, freut sich auf Besuch") to confirm the field persisted.
- **Cronjobs created:**
  - *CallKeep Morgen-Update* (job_id `bebe58017f95`): scheduled daily at `0 11 * * *`, checks `http://localhost:3002/api/dashboard` and reports who is overdue, due soon, or already called.
  - *CallKeep Abend-Check* (job_id `d85e68578d14`): scheduled daily at `0 21 * * *`, asks whether planned calls were made, whether additional calls need logging, and if any follow-ups should be scheduled for the next day.
- **Assistant role accepted:** The user explicitly asked the assistant to manage CallKeep going forward. The assistant updated its memory entry to record the app path, port, compose-based rebuild procedure, and the `POST /api/kiwi/log-call` endpoint.

**3. Key decisions, solutions found, and conclusions**
- **Critical fix for "Legacy App" problem:** Never use bare `docker run` or `docker build` directly for CasaOS-managed apps. The correct sequence is to operate from `/var/lib/casaos/apps/callkeep/` and use `docker compose` (or `docker --config /tmp/docker-config compose`) so the Dashboard recognizes the container as managed.
- **Docker config permission workaround:** The server repeatedly showed `WARNING: Error loading config file: open /DATA/.docker/config.json: permission denied`. The working solution was to set `DOCKER_CONFIG=/tmp/docker-config` or invoke `docker --config /tmp/docker-config compose`, since the user `az-a` lacked permissions on `/DATA/.docker/config.json` and could not use `sudo` with environment variables for Docker config.
- **Compose is the single source of truth:** `/var/lib/casaos/apps/callkeep/docker-compose.yml` defines the build context as `/media/HDD_1TB/CallKeep`, volume mounts the host path to `/data`, and names the container `CallKeep`. Rebuilding via compose ensures the CasaOS metadata and container state stay in sync.
- **API behavior verified:** The simplified frontend and backend were confirmed active: contact form reduced to Name/Frequency/Notes; call form reduced to Contact/Direction/Duration/Date/Summary/Follow-up/Next Call; moods and relationships removed.

**4. Specific commands, files, URLs, and technical details**
- **App source path:** `/media/HDD_1TB/CallKeep/`
- **CasaOS compose file:** `/var/lib/casaos/apps/callkeep/docker-compose.yml`
- **Database:** `/media/HDD_1TB/CallKeep/callkeep.db` (SQLite, auto-migrates `summary` column)
- **Port:** `3002` mapped to host
- **Docker compose workaround command:**
  ```bash
  cd /var/lib/casaos/apps/callkeep/
  DOCKER_CONFIG=/tmp/docker-config docker compose build --no-cache
  DOCKER_CONFIG=/tmp/docker-config docker compose up -d
  ```
  or equivalently:
  ```bash
  docker --config /tmp/docker-config compose build --no-cache
  docker --config /tmp/docker-config compose up -d
  ```
- **Verification commands used:**
  ```bash
  curl -s -o /dev/null -w "HTTP %{http_code}\n" http://localhost:3002/
  curl -s http://localhost:3002/api/options
  curl -s http://localhost:3002/api/dashboard
  curl -s http://localhost:3002/api/stats
  ```
- **Log call endpoint tested:**
  ```bash
  curl -s "http://localhost:3002/api/kiwi/log-call?contact_name=Anneanne&direction=Ausgehend&duration_minutes=5"
  curl -s "http://localhost:3002/api/kiwi/log-call?contact_name=Anneanne&direction=Eingehend&duration_minutes=8&summary=Oma%20geht%20es%20gut..."
  ```
- **Cronjob schedules:**
  - Morning: `0 11 * * *` (deliver to origin/Telegram)
  - Evening: `0 21 * * *` (deliver to origin/Telegram)

**5. Anything unresolved or notable**
- A prior "CallKeep Daily Reminder" cronjob at 09:00 (job_id `bebe58017f95`) was superseded/reused for the 11:00 slot; the transcript shows the job ID remained the same after an update.
- The user paused an unrelated cronjob ("Lernziel 150min — Kopfhörer") during this session, but this is not part of the CallKeep scope.
- No further rebuilds or manual interventions are expected; the assistant recorded the compose workflow in memory for future autonomous use.

Summary:
**Factual Recap — May 23, 2026 at 09:18 AM (Telegram)**

**1. User’s goals**
The user asked to build **CallKeep**, a relationship-tracking web app to log phone calls with friends (who was called, when, duration, topics, mood, follow-ups) and receive automated reminders for pending calls. He also wanted a separate, immediate cronjob to track his daily learning goal: **150 minutes of study time** to unlock buying headphones, with hourly progress checks against the **Zeitgeist** learning backend.

**2. Actions taken and outcomes**
- **Zeitgeist learning check.** The assistant queried the Zeitgeist API (`http://localhost:8765/api/data`) and local DailyDose data. Results: 22.05.2026 showed **114 minutes (1.9 h)** across 5 slots; 23.05.2026 showed **0 minutes** tracked so far.
- **Learning-goal cronjob created.** A Hermes cronjob was deployed to remind the user hourly:
  - `job_id`: `802d68c923d8`
  - `name`: `"Lernziel 150min — Kopfhörer"`
  - `schedule`: `0 * * * *` (top of every hour)
  - `repeat`: `16 times`
  - `deliver`: `origin` (Telegram)
  - `enabled_toolsets`: `["terminal"]`
  - `next_run_at`: `2026-05-23T10:00:00+02:00`
  - The job queries Zeitgeist via `curl -s http://localhost:8765/api/data` and reports minutes completed vs. remaining until the 150-minute threshold is reached.
- **CallKeep concept & design.** Before building, the assistant sketched a FastAPI+SQLite architecture with a vanilla JS SPA frontend, bottom-sheet modals, blue glass-morphism / system-aware theme, and a CasaOS dashboard tile. Planned data model: contacts (name, nickname, relationship tier, desired call frequency), calls (datetime, duration, topics/tags, mood, follow-up flag), and a dashboard showing overdue calls, streaks, and stats.
- **CallKeep implementation started.** Using the `zimaos-web-app` skill, the assistant:
  - Created project structure at `/media/HDD_1TB/CallKeep/`
  - Confirmed port **3001** was free
  - Wrote `main.py` (FastAPI backend with SQLite schema, 13,980 bytes)
  - Wrote `Dockerfile`
  - Began writing `frontend/index.html` (full SPA UI with standardized inputs for names and frequencies)
  - Generated a todo list with 8 items (structure ✅, backend ✅, frontend in progress, Docker build pending, CasaOS deployment pending).

**3. Key decisions and solutions found**
- **Zeitgeist integration:** DailyDose auto-syncs learning minutes from the Zeitgeist backend; the cronjob leverages the same `:8765/api/data` endpoint rather than parsing DailyDose localStorage directly.
- **CallKeep deployment pattern:** Chose the ZimaOS-native pattern (source on HDD at `/media/HDD_1TB/CallKeep/`, Docker container with CasaOS `casaos.*` labels or `x-casaos` compose block) for dashboard integration and VPN compatibility. The skill mandates `hostname=""` (empty string) for universal access and an SVG icon served locally.
- **Standardized inputs:** The user explicitly requested that name and frequency fields in CallKeep be standardized/dropdown-driven rather than freeform text.

**4. Important technical details preserved**
- **Learning cronjob:** `802d68c923d8`, schedule `0 * * * *`, 16 repeats, origin delivery, terminal-only toolset.
- **Zeitgeist API:** `localhost:8765/api/data`; data keys include `zeitgeist-v2` (daily minute arrays), `zeitgeist-v2-notes` (topic labels), and `zeitgeist-anki-v2` (flashcard decks).
- **CallKeep paths:** project root `/media/HDD_1TB/CallKeep/`, planned port **3001**, planned icon route `/icon.svg`.
- **Backend stack:** Python 3.11-slim Docker image, FastAPI, uvicorn, SQLite file stored inside the container or mounted volume.
- **Frontend style:** Blue glass-morphism with `@media (prefers-color-scheme: dark)` system-aware theming, mobile-first, bottom-sheet modals, 44 px tap targets.
- **CasaOS quirks noted:** `network_mode: bridge` required; `zimaos-app-management` must be restarted after deployment; old `v2app` entries must be cleaned from `/etc/casaos/app-management.json` while the service is stopped to avoid “Derzeit nicht unterstützt” errors.

**5. Anything left unresolved**
- The **CallKeep app was not finished** when the transcript ends. The frontend HTML was still being written; Docker build, container deployment, CasaOS registration, and the actual **CallKeep reminder cronjobs** were pending.
- The **learning cronjob** (`802d68c923d8`) was successfully scheduled but had not yet executed (first run set for 10:00 AM); no execution results appear in the transcript.
- The user’s earlier request for standardized name/frequency inputs in CallKeep was acknowledged but not yet fully wired into the backend/frontend code before truncation.

Summary:
**Recap: Morning Briefing & CallKeep Cronjob (May 31, 2026)**

**1. User’s initial request**
The user criticized the morning briefing for lacking effort and asked three things:
- *“Who do we have to call today?”*
- Reminder to fill out **Daily Dose**.
- Correction that today was **Sunday**, not Monday.

**2. Actions taken & outcomes**

- **Skills loaded:** `daily-dose`, `google-workspace`, `cronjob`.
- **Google auth verified:** `AUTHENTICATED: Token valid at /DATA/.hermes/google_token.json`.
- **Active cronjobs inspected.** Two recurring Telegram-delivered jobs were running:
  - `c11fbac168bd` — **“Morgenbriefing 9:30”**, schedule `30 9 * * *`, skills `google-workspace` + `daily-dose`. Last run: `2026-05-31T09:31:26+02:00`. Next run: `2026-06-01T09:30:00+02:00`.
  - `0968c1c5dec3` — **“Abend-Check 20:00”**, schedule `0 20 * * *`, skill `daily-dose`. Last run: `2026-05-30T20:00:44+02:00`. Next run: `2026-05-31T20:00:00+02:00`. Its prompt explicitly included a **CallKeep** step: *“1. **CallKeep Telefonate prüfen:** Ru…”*

- **CallKeep data queried via terminal** to answer “who to call today”:
  - One query returned `[]` — **no pending follow-up calls due today**.
  - A second query returned the full call log (JSON). Most recent calls were from **May 28, 2026** (Bayram calls to Orhan Ocakdan, Josef Garf, Fatih Yilmaz, Abdullah Oberascher). Earlier calls included Anneanne, Dede, Omar Elsayed, etc.
  - A third query listed contacts with IDs (e.g., `14: Abdullah Oberascher`, `9: Anneanne`, `8: Orhan Ocakdan`, etc.).

- **Daily Dose status:** Not yet filled for today. Yesterday (`dailydose_2026-05-30`) had: Islam 0.25h, Körperpflege 0.5h, Schlaf 8h.
- **Weather:** `Sunny +17°C 79% ↘8km/h`.

**3. Key decisions & conclusions**

- **Morning briefing delivered:** Sunday, May 31 — no calendar appointments, no calls due today, Daily Dose open, sunny 17°C in Vienna. The assistant noted that the previous prompt was too generic and **planned to patch the “Morgenbriefing” prompt** to be more specific and useful.
- The **Abend-Check 20:00 cronjob** was already the correct vehicle for CallKeep follow-ups; it just runs in the evening.

**4. Technical details preserved**

- Cron schedules: `30 9 * * *` (morning) and `0 20 * * *` (evening).
- Delivery method: `deliver: origin` (Telegram).
- CallKeep due-check returned `[]` (empty array).
- Daily Dose API endpoint referenced: `http://localhost:8765/api/data`.
- Daily Dose path: `/media/HDD_1TB/DailyDose/`.

**5. Unresolved / notable**

- The assistant **stated it would patch the morning briefing prompt** but the transcript does not show the actual edit being made.
- The rest of the long session shifted to an **unrelated Austrian legal research thread** (sale/burden of co-ownership shares under ABGB/WEG 2002, inheritance, compulsory portion calculations). A 17 KB legal opinion was produced and saved to `/tmp/oesterreich_miteigentum_wohnung_gutachten.md`. A final subagent call on compulsory portion gifting timed out after 600 s.


Explanation:
The user wants me to update the Cronjob prompt to make CallKeep updates shorter and more concise — only telling them who to call today, nothing else.

Looking at the cronjobs:
1. **Morgenbriefing 9:30** (`c11fbac168bd`) — morning briefing with calendar, weather, etc.
2. **Abend-Check 20:00** (`0968c1c5dec3`) — evening check with CallKeep step

The user is saying "halte callkeep kürzer und sage mir wirklich nur wen ich heute anrufen muss, sonst nichts."

I need to read both cronjob prompts to see which one has the CallKeep content. Based on the session_search, the Abend-Check has a CallKeep step ("CallKeep Telefonate prüfen"). But the user might also want the morning briefing to include CallKeep.

Let me read both prompts first, then update the one(s) that include CallKeep to be shorter.

Wait — I should load the cronjob details to see the full prompts. The list output only shows previews. Let me check what I can read. Actually, I can see the previews:
- Morgenbriefing: "Morgenbriefing für den Chef (Zeyd). Führe folgende Schritte aus:\n\n1. **Kalender:** Rufe den Google K..."
- Abend-Check: "Abend-Check für den Chef (Zeyd). Führe folgende Schritte aus:\n\n1. **CallKeep Telefonate prüfen:** Ru..."

I need the full prompt text. The list output doesn't give full prompts. Let me read the cronjob storage/config to find the full prompts. Or maybe I can use the cronjob tool to view full details?

Actually, I don't have a "view" action on cronjob — only create, list, update, pause, resume, remove, run. But I can use `update` to update the prompt. I need to know the full prompt first though.

Let me look at where cronjobs are stored. From the hermes-agent skill, I might find the path. Let me check the config/storage locations.

Actually, let me just search for the cronjob storage location or read the config file.


hermes-agent

---
name: hermes-agent
description: "Configure, extend, or contribute to Hermes Agent."
version: 2.1.0
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 10+ 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 (ID can be a hub identifier OR a direct https://…/SKILL.md URL; pass --name to override when frontmatter has no name)
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
```

### 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, BlueBubbles (iMessage), Weixin (WeChat), API Server, Webhooks. Open WebUI connects via the API Server adapter.

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

```
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
```

### 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 (requires honcho plugin)
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. New commands land fairly
often; if something below looks stale, run `/help` in-session for the
authoritative list or see the [live slash commands reference](https://hermes-agent.nousresearch.com/docs/reference/slash-commands).
The registry of record is `hermes_cli/commands.py` — every consumer
(autocomplete, Telegram menu, Slack mapping, `/help`) derives from it.

### 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
/snapshot [sub]      Create or restore state snapshots of Hermes config/state (CLI)
/background <prompt> Run prompt in background
/queue <prompt>      Queue for next turn
/steer <prompt>      Inject a message after the next tool call without interrupting
/agents (/tasks)     Show active agents and running tasks
/resume [name]       Resume a named session
/goal [text|sub]     Set a standing goal Hermes works on across turns until achieved
                     (subcommands: status, pause, resume, clear)
/redraw              Force a full UI repaint (CLI)
```

### Configuration
```
/config              Show config (CLI)
/model [name]        Show or change model
/personality [name]  Set personality
/reasoning [level]   Set reasoning (none|minimal|low|medium|high|xhigh|show|hide)
/verbose             Cycle: off → new → all → verbose
/voice [on|off|tts]  Voice mode
/yolo                Toggle approval bypass
/busy [sub]          Control what Enter does while Hermes is working (CLI)
                     (subcommands: queue, steer, interrupt, status)
/indicator [style]   Pick the TUI busy-indicator style (CLI)
                     (styles: kaomoji, emoji, unicode, ascii)
/footer [on|off]     Toggle gateway runtime-metadata footer on final replies
/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
/reload-skills       Re-scan ~/.hermes/skills/ for added/removed skills
/reload              Reload .env variables into the running session (CLI)
/reload-mcp          Reload MCP servers
/cron                Manage cron jobs (CLI)
/curator [sub]       Background skill maintenance (status, run, pin, archive, …)
/kanban [sub]        Multi-profile collaboration board (tasks, links, comments)
/plugins             List plugins (CLI)
```

### Gateway
```
/approve             Approve a pending command (gateway)
/deny                Deny a pending command (gateway)
/restart             Restart gateway (gateway)
/sethome             Set current chat as home channel (gateway)
/update              Update Hermes to latest (gateway)
/topic [sub]         Enable or inspect Telegram DM topic sessions (gateway)
/platforms (/gateway) Show platform connection status (gateway)
```

### Utility
```
/branch (/fork)      Branch the current session
/fast                Toggle priority/fast processing
/browser             Open CDP browser connection
/history             Show conversation history (CLI)
/save                Save conversation to file (CLI)
/copy [N]            Copy the last assistant response to clipboard (CLI)
/paste               Attach clipboard image (CLI)
/image               Attach local image file (CLI)
```

### Info
```
/help                Show commands
/commands [page]     Browse all commands (gateway)
/usage               Token usage
/insights [days]     Usage analytics
/gquota              Show Google Gemini Code Assist quota usage (CLI)
/status              Session info (gateway)
/profile             Active profile info
/debug               Upload debug report (system info + logs) and get shareable links
```

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

---

## Key Paths & Config

```
~/.hermes/config.yaml       Main configuration
~/.hermes/.env              API keys and secrets
$HERMES_HOME/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), `protect_last_n` (20), `hygiene_hard_message_limit` (400) |
| `display` | `skin`, `tool_progress`, `show_reasoning`, `show_cost` |
| `stt` | `enabled`, `provider` (local/groq/openai/mistral) |
| `tts` | `provider` (edge/elevenlabs/openai/minimax/mistral/neutts) |
| `memory` | `memory_enabled`, `user_profile_enabled`, `provider` |
| `security` | `tirith_enabled`, `website_blocklist` |
| `delegation` | `model`, `provider`, `base_url`, `api_key`, `max_iterations` (50), `reasoning_effort` |
| `checkpoints` | `enabled`, `max_snapshots` (50) |

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

### Providers

20+ providers supported. Set via `hermes model` or `hermes setup`.

| Provider | Auth | Key env var |
|----------|------|-------------|
| OpenRouter | API key | `OPENROUTER_API_KEY` |
| Anthropic | API key | `ANTHROPIC_API_KEY` |
| Nous Portal | OAuth | `hermes auth` |
| OpenAI Codex | OAuth | `hermes auth` |
| GitHub Copilot | Token | `COPILOT_GITHUB_TOKEN` |
| Google Gemini | API key | `GOOGLE_API_KEY` or `GEMINI_API_KEY` |
| DeepSeek | API key | `DEEPSEEK_API_KEY` |
| xAI / Grok | API key | `XAI_API_KEY` |
| Hugging Face | Token | `HF_TOKEN` |
| Z.AI / GLM | API key | `GLM_API_KEY` |
| MiniMax | API key | `MINIMAX_API_KEY` |
| MiniMax CN | API key | `MINIMAX_CN_API_KEY` |
| Kimi / Moonshot | API key | `KIMI_API_KEY` |
| Alibaba / DashScope | API key | `DASHSCOPE_API_KEY` |
| Xiaomi MiMo | API key | `XIAOMI_API_KEY` |
| Kilo Code | API key | `KILOCODE_API_KEY` |
| AI Gateway (Vercel) | API key | `AI_GATEWAY_API_KEY` |
| OpenCode Zen | API key | `OPENCODE_ZEN_API_KEY` |
| OpenCode Go | API key | `OPENCODE_GO_API_KEY` |
| Qwen OAuth | OAuth | `hermes login --provider qwen-oauth` |
| Custom endpoint | Config | `model.base_url` + `model.api_key` in config.yaml |
| GitHub Copilot ACP | External | `COPILOT_CLI_PATH` or Copilot CLI |

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

**Ollama Cloud Pro as custom provider:** See `references/ollama-cloud-pro-custom-provider.md` — base URL `https://ollama.com/v1` with `provider: custom`, 3-model concurrency limit, CCR proxy pitfalls, and direct config template.

### Toolsets

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

| Toolset | What it provides |
|---------|-----------------|
| `web` | Web search and content extraction |
| `search` | Web search only (subset of `web`) |
| `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 |
| `video` | Video analysis and 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 |
| `messaging` | Cross-platform message sending |
| `todo` | In-session task planning and tracking |
| `kanban` | Multi-agent work-queue tools (gated to workers) |
| `debugging` | Extra introspection/debug tools (off by default) |
| `safe` | Minimal, low-risk toolset for locked-down sessions |
| `spotify` | Spotify playback and playlist control |
| `homeassistant` | Smart home control (off by default) |
| `discord` | Discord integration tools |
| `discord_admin` | Discord admin/moderation tools |
| `feishu_doc` | Feishu (Lark) document tools |
| `feishu_drive` | Feishu (Lark) drive tools |
| `yuanbao` | Yuanbao integration tools |
| `rl` | Reinforcement learning tools (off by default) |
| `moa` | Mixture of Agents (off by default) |

Full enumeration lives in `toolsets.py` as the `TOOLSETS` dict; `_HERMES_CORE_TOOLS` is the default bundle most platforms inherit from.

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

---

## Security & Privacy Toggles

Common "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.

### Secret redaction in tool output

Secret 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:

```bash
hermes config set security.redact_secrets true       # enable globally
```

**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.

Disable again with:
```bash
hermes config set security.redact_secrets false
```

### PII redaction in gateway messages

Separate from secret redaction. When enabled, the gateway hashes user IDs and strips phone numbers from the session context before it reaches the model:

```bash
hermes config set privacy.redact_pii true    # enable
hermes config set privacy.redact_pii false   # disable (default)
```

### Command approval prompts

By default (`approvals.mode: manual`), Hermes prompts the user before running shell commands flagged as destructive (`rm -rf`, `git reset --hard`, etc.). The modes are:

- `manual` — always prompt (default)
- `smart` — use an auxiliary LLM to auto-approve low-risk commands, prompt on high-risk
- `off` — skip all approval prompts (equivalent to `--yolo`)

```bash
hermes config set approvals.mode smart       # recommended middle ground
hermes config set approvals.mode off         # bypass everything (not recommended)
```

Per-invocation bypass without changing config:
- `hermes --yolo …`
- `export HERMES_YOLO_MODE=1`

Note: YOLO / `approvals.mode: off` does NOT turn off secret redaction. They are independent.

### Shell hooks allowlist

Some 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.

### Disabling the web/browser/image-gen tools

To 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.

---

## 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`
4. **Mistral Voxtral** — set `MISTRAL_API_KEY`

Config:
```yaml
stt:
  enabled: true
  provider: local        # local, groq, openai, mistral
  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 |
| MiniMax | `MINIMAX_API_KEY` | Paid |
| Mistral (Voxtral) | `MISTRAL_API_KEY` | Paid |
| NeuTTS (local) | None (`pip install neutts[all]` + `espeak-ng`) | Free |

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

---

## Durable & Background Systems

Four systems run alongside the main conversation loop. Quick reference
here; full developer notes live in `AGENTS.md`, user-facing docs under
`website/docs/user-guide/features/`.

### Delegation (`delegate_task`)

Synchronous subagent spawn — the parent waits for the child's summary
before continuing its own loop. Isolated context + terminal session.

- **Single:** `delegate_task(goal, context, toolsets)`.
- **Batch:** `delegate_task(tasks=[{goal, ...}, ...])` runs children in
  parallel, capped by `delegation.max_concurrent_children` (default 3).
- **Roles:** `leaf` (default; cannot re-delegate) vs `orchestrator`
  (can spawn its own workers, bounded by `delegation.max_spawn_depth`).
- **Not durable.** If the parent is interrupted, the child is
  cancelled. For work that must outlive the turn, use `cronjob` or
  `terminal(background=True, notify_on_complete=True)`.

Config: `delegation.*` in `config.yaml`.

### Cron (scheduled jobs)

Durable scheduler — `cron/jobs.py` + `cron/scheduler.py`. Drive it via
the `cronjob` tool, the `hermes cron` CLI (`list`, `add`, `edit`,
`pause`, `resume`, `run`, `remove`), or the `/cron` slash command.

- **Schedules:** duration (`"30m"`, `"2h"`), "every" phrase
  (`"every monday 9am"`), 5-field cron (`"0 9 * * *"`), or ISO timestamp.
- **Per-job knobs:** `skills`, `model`/`provider` override, `script`
  (pre-run data collection; `no_agent=True` makes the script the whole
  job), `context_from` (chain job A's output into job B), `workdir`
  (run in a specific dir with its `AGENTS.md` / `CLAUDE.md` loaded),
  multi-platform delivery.
- **Invariants:** 3-minute hard interrupt per run, `.tick.lock` file
  prevents duplicate ticks across processes, cron sessions pass
  `skip_memory=True` by default, and cron deliveries are framed with a
  header/footer instead of being mirrored into the target gateway
  session (keeps role alternation intact).

User docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/cron

### Curator (skill lifecycle)

Background maintenance for agent-created skills. Tracks usage, marks
idle skills stale, archives stale ones, keeps a pre-run tar.gz backup
so nothing is lost.

- **CLI:** `hermes curator <verb>` — `status`, `run`, `pause`, `resume`,
  `pin`, `unpin`, `archive`, `restore`, `prune`, `backup`, `rollback`.
- **Slash:** `/curator <subcommand>` mirrors the CLI.
- **Scope:** only touches skills with `created_by: "agent"` provenance.
  Bundled + hub-installed skills are off-limits. **Never deletes** —
  max destructive action is archive. Pinned skills are exempt from
  every auto-transition and every LLM review pass.
- **Telemetry:** sidecar at `~/.hermes/skills/.usage.json` holds
  per-skill `use_count`, `view_count`, `patch_count`,
  `last_activity_at`, `state`, `pinned`.

Config: `curator.*` (`enabled`, `interval_hours`, `min_idle_hours`,
`stale_after_days`, `archive_after_days`, `backup.*`).
User docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/curator

### Kanban (multi-agent work queue)

Durable SQLite board for multi-profile / multi-worker collaboration.
Users drive it via `hermes kanban <verb>`; dispatcher-spawned workers
see a focused `kanban_*` toolset gated by `HERMES_KANBAN_TASK` so the
schema footprint is zero outside worker processes.

- **CLI verbs (common):** `init`, `create`, `list` (alias `ls`),
  `show`, `assign`, `link`, `unlink`, `comment`, `complete`, `block`,
  `unblock`, `archive`, `tail`. Less common: `watch`, `stats`, `runs`,
  `log`, `dispatch`, `daemon`, `gc`.
- **Worker toolset:** `kanban_show`, `kanban_complete`, `kanban_block`,
  `kanban_heartbeat`, `kanban_comment`, `kanban_create`, `kanban_link`.
- **Dispatcher** runs inside the gateway by default
  (`kanban.dispatch_in_gateway: true`) — reclaims stale claims,
  promotes ready tasks, atomically claims, spawns assigned profiles.
  Auto-blocks a task after ~5 consecutive spawn failures.
- **Isolation:** board is the hard boundary (workers get
  `HERMES_KANBAN_BOARD` pinned in env); tenant is a soft namespace
  within a board for workspace-path + memory-key isolation.

User docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/kanban

---

## Troubleshooting

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

### 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
4. **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.

### Credential management (`.env` writing)

When `hermes` CLI is unavailable and `write_file` is blocked on credential files, writing secrets to `.env` requires terminal-based approaches. Full guide: `references/credential-management.md` — covers safe append vs. dangerous overwrite, sandbox limitations, and 401 troubleshooting.

### Changes not taking effect
- **Tools/skills:** `/reset` starts a new session with updated toolset
- **Config changes:** In gateway: `/restart`. In CLI: exit and relaunch.
- **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`

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

**Gateway completely dead / won't start?** See `references/gateway-outage-recovery.md` — 4-item checklist covering .env vars, config.yaml gateway section, and stale PID/lock cleanup.

Common gateway problems:
- **Gateway dies on SSH logout**: Enable linger: `sudo loginctl enable-linger $USER`
- **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).
- **Gateway crash loop**: Reset the failed state: `systemctl --user reset-failed hermes-gateway`
- **ModuleNotFoundError after file deletions**: NEVER delete `.py` files from the hermes-agent source directory unless the corresponding imports are also removed. `hermes_cli/models.py` imports `codex_models.py` at startup — deleting that file without editing `models.py` causes `ModuleNotFoundError: No module named 'hermes_cli.codex_models'` at gateway start, producing a restart loop. Recovery: `sudo git -C /path/to/hermes-agent -c safe.directory=/path/to/hermes-agent restore .`. If you want to disable providers, modify the import chain — never just delete files.

### Session Recovery After Gateway Restart
If the gateway restarts and `session_search` returns no results, **session data is NOT lost** — the in-memory index was cleared but the on-disk files remain.

**Where to look:**
- `~/.hermes/sessions/*.jsonl` — raw session transcripts (one file per session)
- `~/.hermes/memories/USER.md` and `MEMORY.md` — persisted user profile and environment facts
- `~/.hermes/AGENTS.md` — custom operating rules
- `~/.hermes/work/` — any files the agent produced
- `~/.hermes/config.yaml` and `~/.hermes/.env` — configuration and secrets

**Recovery steps:**
1. Read the memories: `~/.hermes/memories/USER.md` and `MEMORY.md`
2. List recent session files: `ls -lt ~/.hermes/sessions/*.jsonl | head -20`
3. Read key session transcripts directly (JSONL format, one message per line)
4. Check `~/.hermes/work/` for any deliverables from past sessions

**Important:** The gateway restart itself does NOT delete anything. The `sessions.json` index may take a moment to rebuild, but the `.jsonl` files are present immediately. If `session_search` is empty, always fall back to direct filesystem inspection.

**Critical pitfall — session_search default limit:**
`session_search` without arguments may return only 1 result. After a gateway restart the index is empty, so even recent sessions appear lost. Always pass `limit=5` (or higher) and use `query="*"` to force a broad scan when recovering. Example:
```python
session_search(limit=5, query="*")
```
If this still returns nothing, bypass the index entirely and read the `.jsonl` files directly from disk.

### Honcho Memory Plugin — Reality Check
Honcho is listed as an installed plugin but the CLI subcommand `hermes honcho` does **not exist** in all Hermes builds. The Python library (`honcho`) may be present in the venv while the CLI integration is missing.

**What actually works:**
1. Set provider: `hermes config set memory.provider honcho`
2. Verify with `hermes memory status` — look for `Provider: honcho`
3. The plugin status line will say `Status: not available` if the Honcho server (cloud or local Docker) is not reachable.

**Local (no API key) is NOT automatic:**
Honcho requires either a cloud API key (`HONCHO_API_KEY`) or a self-hosted Docker/Postgres instance. There is no "just use SQLite locally" zero-setup mode. If the user wants 100 % offline memory without cloud accounts, the built-in memory system is the practical choice.

**Do not promise Honcho setup works without verifying the CLI subcommand exists first.** Check with `hermes honcho status` — if the command is not found, the integration is incomplete and needs manual Python-level setup or a plugin update.

### Honcho Self-Hosting — ZimaOS Pitfalls

Self-hosting Honcho on ZimaOS has specific gotchas:

1. **Docker Compose v5 + buildx incompatibility:** ZimaOS ships an older buildx. Docker Compose v5 refuses with `compose build requires buildx 0.17.0 or later`. Workaround: use `docker build` manually, then start containers with `docker run` (or install an older docker-compose v2 binary).

2. **Read-only root filesystem:** `/root/.docker` is on a read-only FS — `sudo docker` fails with `mkdir /root/.docker: read-only file system`. Set `DOCKER_CONFIG=/tmp/docker-config` (or `/DATA/.docker-config`) before invoking docker commands.

3. **Docker group access:** After `usermod -aG docker`, the group membership doesn't take effect until next login. Use `sg docker -c "..."` in the same session. Combine with (2): `sg docker -c "DOCKER_CONFIG=/tmp/docker-config docker ps"`.

4. **Honcho needs its own LLM key:** Even self-hosted, Honcho requires an LLM provider API key for internal memory operations (deriver, dialectic, dreamer). You can point it at the same Ollama Cloud Pro endpoint Hermes uses — set `LLM_OPENAI_API_KEY` plus per-module `*_MODEL_CONFIG__OVERRIDES__BASE_URL` to `https://ollama.com/v1` in Honcho's `.env`. Every module (deriver, dialectic levels, summary, dream) needs its own base URL override — the global `LLM_BASE_URL` may not propagate to all submodules.

5. **Embeddings still go to OpenAI:** Honcho defaults to `text-embedding-3-small` via OpenAI transport. If your LLM proxy doesn't support embeddings, Honcho's deriver will fail. Check with `docker logs honcho-api`.

6. **Container naming:** When using `docker run` instead of compose, name the network explicitly so api/deriver/database/redis can resolve each other's hostnames: `docker network create honcho-net`, then `--network honcho-net` on all containers.

**Complete self-hosting guide:** `references/honcho-self-hosting.md` — covers Docker Compose setup (including ZimaOS quirks), `.env` template for OpenAI-compatible providers (Ollama, OpenRouter), embedding configuration, and common pitfalls.

### Platform-specific issues
- **Discord bot silent**: Must enable **Message Content Intent** in Bot → Privileged Gateway Intents.
- **Slack bot only works in DMs**: Must subscribe to `message.channels` event. Without it, the bot ignores public channels.
- **Windows HTTP 400 "No models provided"**: Config file encoding issue (BOM). Ensure `config.yaml` is saved as UTF-8 without BOM.

### Auxiliary models not working
If `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:
```bash
hermes config set auxiliary.vision.provider <your_provider>
hermes config set auxiliary.vision.model <model_name>
```

Full step-by-step setup for dedicated auxiliary models (recommended for custom providers like Ollama): see `references/auxiliary-model-setup.md` — covers model selection, required context windows, and the exact YAML block to paste.

Context compression tuning (threshold, target_ratio, local vs cloud models): see `references/compression-tuning.md`.

---

## 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, context compression, memory, model routing, credential pooling, skill dispatch
├── 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 to `toolsets.py`** → `_HERMES_CORE_TOOLS` list.

Auto-discovery: any `tools/*.py` file with a top-level `registry.register()` call is imported automatically — no manual list needed.

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
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:
The user wants me to update the "Abend-Check 20:00" cronjob (job_id: 0968c1c5dec3) to make the CallKeep part shorter — he only wants to know WHO he needs to call today, nothing else.

Let me look at the current prompt for that cronjob. From the session search, the prompt includes "1. **CallKeep Telefonate prüfen:** Ru…". I need to see the full prompt to know exactly what to change.

Let me get the full details of this cronjob. The `cronjob` tool with `action='list'` only gives a preview. Let me see if I can get the full prompt somehow.

Actually, the `hermes cron edit` CLI command would let me see and edit it. Let me use terminal to run `hermes cron` or just look at the stored cronjob data.

Actually, let me think about this differently. The user wants the Abend-Check to be shorter — specifically for the CallKeep part, only say WHO to call, nothing else.

Let me first look at the actual cron jobs in more detail. I can try reading the cron storage to see the full prompt.

from hermes_tools import terminal

# Get full cronjob details
result = terminal("hermes cron list 2>&1", timeout=10)
print(result["output"])


Output: /usr/bin/bash: line 3: hermes: command not found


Explanation:
The user wants to know which CallKeep cronjob they're referring to. Looking at the cronjob list, there are two jobs:

1. `c11fbac168bd` - "Morgenbriefing 9:30" - runs at 9:30 daily, uses google-workspace + daily-dose
2. `0968c1c5dec3` - "Abend-Check 20:00" - runs at 20:00 daily, uses daily-dose

The Abend-Check has CallKeep in its prompt. Let me look at the session search results - it says the Abend-Check prompt includes "**CallKeep Telefonate prüfen:** Ru…"

The user says "bitte halte callkeep kürzer und sage mir wirklich nur wen ich heute anrufen muss, sonst nichts" - they want the CallKeep section to be shorter and only tell them who to call today, nothing else.

The user didn't specify which cronjob - but the "Morgenbriefing" at 9:30 seems most likely since that's when they'd want to know who to call today. But actually, looking at the Abend-Check (20:00) - it also has CallKeep. Let me look more carefully.

The user said "Zu dem cronjob" - "regarding the cronjob". But which one? The user might be referring to the one that just ran (Morgenbriefing at 9:30) since it's now 9:32 and the last run was 9:31.

Actually wait - I need to get the full prompt of both to understand what to change. Let me try with the proper cron tool.

Actually, let me re-read: the user is saying "Zu dem cronjob: bitte halte callkeep kürzer und sage mir wirklich nur wen ich heute anrufen muss, sonst nichts." - "Regarding the cronjob: please keep callkeep shorter and really only tell me who I have to call today, nothing else."

This is probably about the morning briefing. But I should clarify which one. Actually, since it's the morning and the user just got the morning briefing at 9:31, that's almost certainly what they're referring to. They want the CallKeep part of the morning briefing to be shorter.

But actually, looking more carefully - it could also be the Abend-Check which explicitly has CallKeep in its prompt. But the user says "heute" (today) - so it's probably the morning briefing telling them who to call today.

Let me look at the cron prompts more carefully. I need to see the actual prompt content. Let me just ask the user which cronjob they mean, or I can look at the prompt preview. It's the Morgenbriefing at 9:30 since it says "Kalender: Rufe den Google K..." and it would make sense to include CallKeep there.

Wait - looking at the session search result from May 31: "The assistant stated it would patch the morning briefing prompt but the transcript does not show the actual edit being made." So the morning briefing was supposed to be patched but wasn't.

The Abend-Check has CallKeep as step 1 in its prompt. The user probably wants me to update the Abend-Check's CallKeep section to be shorter. But they could also want the morning briefing to have a shorter CallKeep section.

Given that the user just received the morning briefing at 9:31 (it ran at 9:31:51), and they're responding now at 9:32, they're likely reacting to the morning briefing that just came in. They want the CallKeep part of it to be shorter.

But I need to see the actual prompt content. Let me try to get it.

Actually, I can use `hermes cron edit` or just look at the state. But `hermes` isn't available as a command. Let me try another approach.

Let me just look at the cron data directory.


Explanation: Let me read the cron jobs JSON file to see the full details of both jobs.