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

Click on an element identified by its ref ID from the snapshot (e.g., '@e5'). The ref IDs are shown in square brackets in the snapshot output. Requires browser_navigate and browser_snapshot to be called first.

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

Get browser console output and JavaScript errors from the current page. Returns console.log/warn/error/info messages and uncaught JS exceptions. Use this to detect silent JavaScript errors, failed API calls, and application warnings. Requires browser_navigate to be called first. When 'expression' is provided, evaluates JavaScript in the page context and returns the result — use this for DOM inspection, reading page state, or extracting data programmatically.

If true, clear the message buffers after reading

JavaScript expression to evaluate in the page context. Runs in the browser like DevTools console — full access to DOM, window, document. Return values are serialized to JSON. Example: 'document.title' or 'document.querySelectorAll("a").length'

Get a list of all images on the current page with their URLs and alt text. Useful for finding images to analyze with the vision tool. Requires browser_navigate to be called first.

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

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

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

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

Scroll the page in a direction. Use this to reveal more content that may be below or above the current viewport. Requires browser_navigate to be called first.

Direction to scroll

Get a text-based snapshot of the current page's accessibility tree. Returns interactive elements with ref IDs (like @e1, @e2) for browser_click and browser_type. full=false (default): compact view with interactive elements. full=true: complete page content. Snapshots over 8000 chars are truncated or LLM-summarized. Requires browser_navigate first. Note: browser_navigate already returns a compact snapshot — use this to refresh after interactions that change the page, or with full=true for complete content.

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

Type text into an input field identified by its ref ID. Clears the field first, then types the new text. Requires browser_navigate and browser_snapshot to be called first.

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

The text to type into the field

Take a screenshot of the current page and analyze it with vision AI. Use this when you need to visually understand what's on the page - especially useful for CAPTCHAs, visual verification challenges, complex layouts, or when the text snapshot doesn't capture important visual information. Returns both the AI analysis and a screenshot_path that you can share with the user by including MEDIA:<screenshot_path> in your response. Requires browser_navigate to be called first.

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

If true, overlay numbered [N] labels on interactive elements. Each [N] maps to ref @eN for subsequent browser commands. Useful for QA and spatial reasoning about page layout.

clarify

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

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

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

Do NOT use this tool for simple yes/no confirmation of dangerous commands (the terminal tool handles that). Prefer making a reasonable default choice yourself when the decision is low-stakes.

The question to present to the user.

Choices:
Up to 4 answer choices. Omit this parameter entirely to ask an open-ended question. When provided, the UI automatically appends an 'Other (type your answer)' option.

cronjob

Manage scheduled cron jobs with a single compressed tool.

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

To stop a job the user no longer wants: first action='list' to find the job_id, then action='remove' with that job_id. Never guess job IDs — always list first.

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

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

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

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

Required for update/pause/resume/remove/run

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

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

Optional human-friendly name

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

Omit this parameter to auto-deliver back to the current chat and topic (recommended). Auto-detection preserves thread/topic context. Only set explicitly when the user asks to deliver somewhere OTHER than the current conversation. Values: 'origin' (same as omitting), 'local' (no delivery, save only), 'all' (fan out to every connected home channel), or platform:chat_id:thread_id for a specific destination. Combine with comma: 'origin,all' delivers to the origin plus every other connected channel. Examples: 'telegram:-1001234567890:17585', 'discord:#engineering', 'sms:+15551234567', 'all'. WARNING: 'platform:chat_id' without :thread_id loses topic targeting. 'all' resolves at fire time, so a job created before a channel was wired up will pick it up automatically once connected.

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

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

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

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

Optional path to a script that runs each tick. In the default mode its stdout is injected into the agent's prompt as context (data-collection / change-detection pattern). With no_agent=True, the script IS the job and its stdout is delivered verbatim (classic watchdog pattern). Relative paths resolve under ~/.hermes/scripts/. ``.sh``/``.bash`` extensions run via bash, everything else via Python. On update, pass empty string to clear.

Default: False (LLM-driven job — the agent runs the prompt each tick). Set True to skip the LLM entirely: the scheduler just runs ``script`` on schedule and delivers its stdout verbatim. No tokens, no agent loop, no model override honoured.

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

DELIVERY SEMANTICS when True: (a) non-empty stdout is sent verbatim as the message; (b) EMPTY stdout means SILENT — nothing is sent to the user and they won't see anything happened, so design your script to stay quiet when there's nothing to report (the watchdog pattern); (c) non-zero exit / timeout sends an error alert so a broken watchdog can't fail silently.

WHEN TO USE True: recurring script-only pings where the script itself produces the exact message text (memory/disk/GPU watchdogs, threshold alerts, heartbeats, CI notifications, API pollers with a fixed output shape). WHEN TO USE False (default): anything that needs reasoning — summarize a feed, draft a daily briefing, pick interesting items, rephrase data for a human, follow conditional logic based on content.

Optional job ID or list of job IDs whose most recent completed output is injected into the prompt as context before each run. Use this to chain cron jobs: job A collects data, job B processes it. Each entry must be a valid job ID (from cronjob action='list'). Note: injects the most recent completed output — does not wait for upstream jobs running in the same tick. On update, pass an empty array to clear.

Optional list of toolset names to restrict the job's agent to (e.g. ["web", "terminal", "file", "delegation"]). When set, only tools from these toolsets are loaded, significantly reducing input token overhead. When omitted, all default tools are loaded. Infer from the job's prompt — e.g. use "web" if it calls web_search, "terminal" if it runs scripts, "file" if it reads files, "delegation" if it calls delegate_task. On update, pass an empty array to clear.

Optional absolute path to run the job from. When set, AGENTS.md / CLAUDE.md / .cursorrules from that directory are injected into the system prompt, and the terminal/file/code_exec tools use it as their working directory — useful for running a job inside a specific project repo. Must be an absolute path that exists. When unset (default), preserves the original behaviour: no project context files, tools use the scheduler's cwd. On update, pass an empty string to clear. Jobs with workdir run sequentially (not parallel) to keep per-job directories isolated.

Spawn one or more subagents to work on tasks in isolated contexts. Each subagent gets its own conversation, terminal session, and toolset. Only the final summary is returned -- intermediate tool results never enter your context window.

TWO MODES (one of 'goal' or 'tasks' is required):
1. Single task: provide 'goal' (+ optional context, toolsets)
2. Batch (parallel): provide 'tasks' array with up to 3 items concurrently for this user (configured via delegation.max_concurrent_children in config.yaml). All run in parallel and results are returned together. Nested delegation is OFF for this user (max_spawn_depth=1): every child is a leaf and cannot delegate further. Raise delegation.max_spawn_depth in config.yaml to enable nesting.

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

WHEN NOT TO USE (use these instead):
- Mechanical multi-step work with no reasoning needed -> use execute_code
- Single tool call -> just call the tool directly
- Tasks needing user interaction -> subagents cannot use clarify
- Durable long-running work that must outlive the current turn -> use cronjob (action='create') or terminal(background=True, notify_on_complete=True) instead. delegate_task runs SYNCHRONOUSLY inside the parent turn: if the parent is interrupted (user sends a new message, /stop, /new) the child is cancelled with status='interrupted' and its work is discarded. Children cannot continue in the background.

IMPORTANT:
- Subagents have NO memory of your conversation. Pass all relevant info (file paths, error messages, constraints) via the 'context' field.
- If the user is writing in a non-English language, or asked for output in a specific language / tone / style, say so in 'context' (e.g. "respond in Chinese", "return output in Japanese"). Otherwise subagents default to English and their summaries will contaminate your final reply with the wrong language.
- Subagent summaries are SELF-REPORTS, not verified facts. A subagent that claims "uploaded successfully" or "file written" may be wrong. For operations with external side-effects (HTTP POST/PUT, remote writes, file creation at shared paths, publishing), require the subagent to return a verifiable handle (URL, ID, absolute path, HTTP status) and verify it yourself — fetch the URL, stat the file, read back the content — before telling the user the operation succeeded.
- Leaf subagents (role='leaf', the default) CANNOT call: delegate_task, clarify, memory, send_message, execute_code.
- Orchestrator subagents (role='orchestrator') retain delegate_task so they can spawn their own workers, but still cannot use clarify, memory, send_message, or execute_code. Orchestrators are bounded by max_spawn_depth=1 for this user and can be disabled globally via delegation.orchestrator_enabled=false.
- Each subagent gets its own terminal session (separate working directory and state).
- Results are always returned as an array, one entry per task.

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

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

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

Task goal

Task-specific context

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

Per-task ACP command override (e.g. 'copilot'). Overrides the top-level acp_command for this task only. Do NOT set unless the user explicitly told you an ACP CLI is installed.

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

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

Batch mode: tasks to run in parallel (up to 3 for this user, set via delegation.max_concurrent_children). Each gets its own subagent with isolated context and terminal session. When provided, top-level goal/context/toolsets are ignored.

Role of the child agent. 'leaf' (default) = focused worker, cannot delegate further. 'orchestrator' = can use delegate_task to spawn its own workers. Nesting is OFF for this user (max_spawn_depth=1); 'orchestrator' is silently forced to 'leaf'. Raise delegation.max_spawn_depth in config.yaml to enable.

Override ACP command for child agents (e.g. 'copilot'). When set, children use ACP subprocess transport instead of inheriting the parent's transport. Requires an ACP-compatible CLI (currently GitHub Copilot CLI via 'copilot --acp --stdio'). See agent/copilot_acp_client.py for the implementation. IMPORTANT: Do NOT set this unless the user has explicitly told you a specific ACP-compatible CLI is installed and configured. Leave empty to use the parent's default transport (Hermes subagents).

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

Run a Python script that can call Hermes tools programmatically. Use this when you need 3+ tool calls with processing logic between them, need to filter/reduce large tool outputs before they enter your context, need conditional branching (if X then Y else Z), or need to loop (fetch N pages, process N files, retry on failure).

Use normal tool calls instead when: single tool call with no processing, you need to see the full result and apply complex reasoning, or the task requires interactive user input.

Available via `from hermes_tools import ...`:

  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.

Generate high-quality images from text prompts. The underlying backend (FAL, OpenAI, etc.) and model are user-configured and not selectable by the agent. Returns either a URL or an absolute file path in the `image` field; display it with markdown ![description](url-or-path) and the gateway will deliver it.

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

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

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

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

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

REQUIRED when mode='replace'. Exact text to find and replace. Must be unique in the file unless replace_all=true. Include surrounding context lines to ensure uniqueness.

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

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

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

process

Manage background processes started with terminal(background=true). Actions: 'list' (show all), 'poll' (check status + new output), 'log' (full output with pagination), 'wait' (block until done or timeout), 'kill' (terminate), 'write' (send raw stdin data without newline), 'submit' (send data + Enter, for answering prompts), 'close' (close stdin/send EOF).

list poll log wait kill write submit close

Action to perform on background processes

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

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

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

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

Max lines to return for 'log' action

Read a text file with line numbers and pagination. Use this instead of cat/head/tail in terminal. Output format: 'LINE_NUM|CONTENT'. Suggests similar filenames if not found. Use offset and limit for large files. Reads exceeding ~100K characters are rejected; use offset and limit to read specific sections of large files. NOTE: Cannot read images or binary files — use vision_analyze for images.

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

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

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

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

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

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

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

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

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

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

Maximum number of results to return (default: 50)

Skip first N results for pagination (default: 0)

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

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

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.

Load an image into the conversation so you can see it. Accepts a URL, local file path, or data URL. When your active model has native vision, the image is attached to your context directly and you read the pixels yourself on the next turn — call this any time the user references an image (filepath in their message, URL in tool output, screenshot from the browser, etc.). For non-vision models, falls back to an auxiliary vision model that returns a text description.

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

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

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


[M G] ich habe den API key für Openfigi. wo soll ich dir diesen ablegen? gib mir die befehle fürs Terminal.


Explanation:
**Setting up the OpenFIGI key**

I see that we need the answer in German. It’s important to set up the OpenFIGI key properly, but I'm wondering if this is more about configuration rather than Hermes itself, which could be a finance-related aspect. The user seems to be asking where to place the API key, so I might want to focus on the relevant finance skill or even the finance system architecture. Let’s load the finance-system architecture for clarity!


finance-system-architecture

---
name: finance-system-architecture
description: "Design/implement the user's JARVIS Finance System: CHF ledger, portfolio accounting, dashboard, imports, reports, secrecy."
version: 1.0.0
author: Hermes Agent
license: MIT
metadata:
  hermes:
    tags: [finance, portfolio, accounting, dashboard, csv, fx, tax, privacy]
---

# Finance System Architecture

## When to use

Use this skill whenever the user asks about the **Finance System – Architektur & Scripts** topic or work involving the user's personal finance-management system: portfolio imports, transaction accounting, Bank/Broker/CSV processing, dashboards, reports, tax/income views, FX logic, market data jobs, alerts, or later implementation.

Do **not** use it for pure investment-strategy discussion; those belong in the separate finance strategy topic unless the user explicitly asks for technical implementation.

## Core principles

1. **No automated trading.** The system may prepare orders and recommendations, but never executes orders or connects to broker trading APIs for execution.
2. **Accounting first, opinions later.** MVP must prioritize correct transaction ledger, cash ledger, FX handling, income/tax data, and dashboard before complex scores, news, analyst ratings, or LLM analysis.
3. **Rule-based first.** Calculations, scores, alerts, rebalancing and reports must be deterministic and auditable. LLMs may only summarize/explain text or assist extraction with human review.
4. **CHF as base currency.** Store every transaction in original currency and CHF using historical FX at transaction/payment date; current valuations use current FX.
5. **Financial data secrecy.** Never expose real financial values, portfolio files, raw exports, reports with real numbers, DBs, API keys, or credentials in chat, GitHub, logs, or shared docs unless the user explicitly approves scope.
6. **Data ownership.** All data must be exportable: CSV, JSON, Parquet, SQLite/Postgres dump, Markdown/HTML/PDF reports.

## Current v0.3 decisions

See `references/spec-v0.2-decisions.md` for the baseline, `references/spec-v0.3-decisions.md` for the priority update, `references/spec-v0.4-implementation-blueprint.md` for the MVP 1 technical implementation blueprint, `references/spec-v0.4.1-corrections.md` for accepted corrections, `references/spec-v0.5-repo-blueprint.md` for the concrete repo/implementation plan, `references/mvp-safety-gate-implementation.md` for the implementation safety-gate sequence and verification commands, `references/mvp-import-pipeline-tasks-9-13.md` for the synthetic CSV import/FX/transaction pipeline pattern, `references/mvp-ledger-cash-wac-positions.md` for cash/WAC/position ledger calculation rules and tests, `references/mvp-crypto-wallet-ledger.md` for crypto wallet/assets/holdings/transfers/buy-sell/fee MVP rules, `references/crypto-xlsx-initial-snapshot-dry-run.md` for the controlled real-file XLSX crypto initial-snapshot dry-run pattern and mapping decisions, `references/crypto-xlsx-initial-snapshot-production-import.md` for productive safe-subset XLSX import operations, compatibility/partial-write recovery, and dashboard correction follow-up, `references/crypto-single-coin-runtime-test.md` for controlled one-coin productive runtime tests and the coin-vs-holding ambiguity guard, `references/multi-wallet-crypto-and-equity-manage-ui.md` for approved multi-wallet single-coin snapshots, SQLite Decimal/TEXT affinity pitfalls, and synthetic-first Equity/ETF Manage UI patterns, `references/crypto-price-refresh-and-idempotent-btc-runtime.md` for robust batch price refresh and re-run-safe BTC/single-coin runtime checks, `references/crypto-runtime-db-consistency-verification.md` for post-import runtime DB consistency checks, exact safe-set verification, dashboard no-live-API testing, and runtime-only report generation, `references/mvp-crypto-manual-management-ui.md` for audited dashboard add/correct/remove crypto holding workflows after an initial snapshot, `references/mvp-market-import-safety-hardening.md` for CoinGecko provider/backoff, CSV importer completion, alert lifecycle, Git-safety and crypto Decimal precision patterns, `references/git-safety-verification-coverage.md` for the verifier-warning workflow and minimum Git-safety test matrix, `references/mvp-streamlit-dashboard.md` for the safe local Streamlit dashboard shell/read-model/testing pattern, `references/mvp-crypto-report-export.md` for local-only crypto report context/export rules, `references/github-token-push-from-drive.md` for the safe Google-Drive-token push workflow when local FinanceManager commits are ahead of GitHub, `references/runtime-backup-and-broker-mapping.md` for runtime DB backup/restore hardening plus PostFinance/True Wealth/Raiffeisen structural mapping/dry-run rules, `references/import-wizard-mapping-layer.md` for the Phase B1 import wizard, instrument/account mapping, review queue, data-quality and read-only safety pattern, `references/broker-parser-dry-run-pipeline.md` for the Phase B2 synthetic broker parser, dry-run, runtime review-item and UI quality-flag pipeline, `references/controlled-real-broker-dry-run.md` for the Phase B3 controlled real-file dry-run pattern with backup, aggregate-only reporting, runtime-only review items, and no productive position writes, and `references/broker-review-queue-hardening.md` for Phase B4 manual review queue filters, auditable mapping actions, import-readiness gating, dry-run session management, and Data Quality Center hardening without productive portfolio writes, and `references/guided-manual-review-pilot.md` for Phase B5 small-scope runtime metadata pilots that move selected review items to `ready_for_import` without productive imports, `references/broker-import-execution-plan-mini-import.md` for Phase B6 final dry-run execution plans plus exactly-one productive broker mini-import, `references/broker-mini-import-regression-and-corrections.md` for post-mini-import regression, void/correction workflows, backup/restore checks, and one-at-a-time follow-up imports, and `references/broker-mini-import-completion-and-dq-consolidation.md` for completing the last ready True-Wealth mini-import plus active-vs-resolved Data Quality alert consolidation, `references/equity-fx-market-data-phase-c.md` for the local FX/market-data foundation after broker mini-imports and before broader Equity/ETF valuation/imports, and `references/true-wealth-valuation-pilot-c2.md` for the True-Wealth valuation pilot safeguards around hedge metadata, provider mappings, historical FX failures, timestamp alignment, corporate-action flags, and aggregate-only runtime reporting, `references/true-wealth-mapping-candidate-review-c3.md` for the controlled mapping-candidate review pattern before any productive Equity/ETF price or FX valuation, `references/instrument-catalog-manual-add-workflow.md` for the general Instrument Catalog + dashboard manual-add workflow that must underpin future Equity/ETF/Crypto adds, and `references/public-instrument-lookup-candidate-generator.md` for runtime-only public metadata lookups, candidate review packs, alert dedupe, and no-auto-selection rules, and `references/mapping-candidate-ranking-decision-pack.md` for ranking raw candidates into a manual-review decision aid, Data Quality alerts, confirmation workflow, and migration pitfalls, and `references/dashboard-user-mode-ux-and-runtime-review.md` for User/Admin dashboard navigation, crypto wallet drilldowns, audited Crypto Manage actions, and runtime-only mapping demotion patterns, and `references/dashboard-functional-ux-stabilization.md` for removing duplicate Streamlit navigation, hiding unfinished User Mode pages, enforcing Read-only/Edit Mode button behavior, and testing explicit-click price/report actions, and `references/dashboard-usability-simplification.md` for the stricter MVP User Mode reduction, calm Command Center, compact Crypto/Wallet pages, direct inline action forms, and disabled-not-fake button rule, and `references/crypto-adjusted-xlsx-and-equity-docx-dryrun.md` for adjusted real crypto XLSX completion using CoinGecko IDs plus aggregate-only True Wealth/PostFinance DOCX Equity/ETF dry-run preparation, and `references/equity-docx-instrument-resolver-review-workflow.md` for the controlled Equity/ETF DOCX staging, resolver, review queue, local-Qwen-as-parser-only, and confirmed-only initial-snapshot workflow, `references/manual-equity-etf-entry-wizard.md` for the preferred manual Equity/ETF search/add-position wizard when DOCX imports are too unsafe or not approved, and `references/manual-position-entry-provider-ux.md` for User Mode placement, explicit-click OpenFIGI/Finnhub/FMP provider lookup, runtime-secret loading, caching, and final verification/push discipline. Key decisions:

- Platform/account views: Raiffeisen, PostFinance, True Wealth, Crypto-Coins, plus Gesamtansicht.
- Existing Google Drive files under `Finanzen/01 Aktueller Stand Portfolios` are **initial-snapshot reality checks**, not full ledgers.
- MVP means the smallest useful first version: correct data foundation, ledger, CHF/FX logic, platform views, crypto inventory, watchlist, reports, workflows and audit log.
- Stock/ETF tax documents are downgraded: optional reference/control module and dividend/distribution transparency, not MVP 1 and not a complete tax dossier replacement.
- Crypto inventory is promoted to MVP 1: wallet/platform-level holdings, Crypto PDF, CoinGecko valuation, stale-price warnings and manual verification.
- Crypto snapshot values are stale; use quantities only and recalculate current values via CoinGecko later.
- MVP dashboard recommendation: Streamlit + SQLite + SQLAlchemy/Pandas/Plotly; later migrateable to FastAPI + React/PostgreSQL.
- MVP inputs: manual dashboard entry, standard CSV import/export, later broker/bank export import. No direct broker integrations initially.
- Telegram crypto buys/sells/transfers should be parsed as pending transactions and only saved after explicit confirmation.
- Every portfolio or crypto change must create a History/Audit entry.

## Required data model areas

At minimum design for:

- `platforms`, `accounts`, `instruments`
- `transactions` with original currency and CHF fields
- `cash_ledger`
- derived `positions_current`
- `dividends_distributions`
- `market_prices`, `fx_rates`
- `watchlist_items`
- `alerts`
- `decision_journal`
- `reports`
- `data_quality_issues`

## CSV/import rules

- For broker/bank imports (PostFinance, True Wealth, Raiffeisen), build the safe review layer before productive imports: Import Wizard, instrument mappings, platform/account mappings, dry-run summaries, Manual Review Queue, Data Quality Center and visible read-only/write-enabled state. Follow `references/import-wizard-mapping-layer.md`. When wiring parser output into the wizard, use the synthetic-first parser/dry-run/review-item pipeline in `references/broker-parser-dry-run-pipeline.md`. After explicit approval for real-file dry-runs, follow `references/controlled-real-broker-dry-run.md`: preflight, verified runtime backup, temp-only file handling, aggregate-only reporting, runtime-only review items, and verification that productive positions/ledger rows stayed unchanged. For DOCX portfolio extracts from True Wealth/PostFinance, follow `references/crypto-adjusted-xlsx-and-equity-docx-dryrun.md`: use structural/masked parsing only, count field coverage and mapping status, treat ticker-without-exchange as review-needed, and stop before productive import. If the DOCX dry run shows low ISIN coverage/no cost basis/no transaction history or the user withholds final import approval, switch to `references/equity-docx-instrument-resolver-review-workflow.md`: create `instrument_import_candidates`-style staging, use local Qwen only as an assistive parser if available, classify ticker-only rows as `needs_manual_review`, expose a Mapping Review Queue, and import only later from `confirmed` candidates after explicit approval. If the user rejects productive DOCX import or wants direct manual control, follow `references/manual-equity-etf-entry-wizard.md`: make the main path an audited portfolio-app-style search/add-position wizard with explicit candidate selection, no live API on render, no ticker-only auto-selection, hidden technical IDs in User Mode, cost-basis/FX quality alerts, and audit-log writes. When the user asks to make real dry-run results manually editable, follow `references/broker-review-queue-hardening.md`: add filters/detail views, auditable review-metadata actions, per-item/session import-readiness status, dry-run session management, and Data Quality Center counts while keeping productive portfolio writes disabled. For a guided manual-review pilot on real runtime items, follow `references/guided-manual-review-pilot.md`: select 1–3 clear ETF/equity items (prefer True Wealth), write only audited review metadata, correct only presence booleans if needed, derive `ready_for_import` via readiness logic, and verify productive tables remain unchanged. Before the first productive broker position import, follow `references/broker-import-execution-plan-mini-import.md`: create runtime-only execution plans from the ready review items, validate exact Decimal-text payloads from the runtime source, preserve missing FX/cost-basis quality flags, then import exactly one ledger `initial_position_snapshot` after a verified backup; do not write `positions_snapshot` as the source of truth. After the first mini-import and before broader imports, follow `references/broker-mini-import-regression-and-corrections.md`: verify import links/audit/Decimal handling/re-import blocking, add or test safe void/correction flows, run backup/restore-to-test-DB regression, and only then optionally import one more ready plan. When the user approves finishing a remaining small set, follow `references/broker-mini-import-completion-and-dq-consolidation.md`: first disambiguate active vs resolved stale crypto alerts with `check-data-quality --scope crypto --resolve-fixed`, then import exactly one remaining ready execution plan after backup/verify, and consolidate Review Queue/Data Quality counts without exposing values.
- Do not pivot into later analytics modules while the user has asked for import/mapping hardening. Monte Carlo, backtesting, rebalancing, scores, heatmaps and projections are later phases unless explicitly re-authorized.
- Use a canonical CSV format before broker-specific importers.
- Imports must be idempotent via external transaction ID or row hash.
- Importers must separate dry-run and commit modes, collect validation errors explicitly, and always create an `import_sessions` record even for dry runs or failed imports.
- Import results should classify rows as new, existing, duplicate, or failed; do not rely on `INSERT OR IGNORE` as the only duplicate-detection mechanism.
- Row hashes must be stable and deterministic: normalize key order, whitespace, and `None` versus empty strings while leaving domain-specific canonicalization to the importer.
- If a source file has only current holdings and no full history, import it as `initial_position_snapshot` / `initial_cash_snapshot`, not fake historical buys.
- Missing historic FX, fees, taxes, dates, investment case, target weights, or dividend details must be flagged as data-quality gaps.

## FX and return rules

For foreign currency assets, always distinguish:

- price/security performance in original currency
- FX effect to CHF
- realized P&L
- unrealized P&L
- dividends/distributions/income
- fees and taxes
- Total Return in CHF

Every transaction/income event needs:

- original amount and currency
- historical FX rate to CHF, or explicit `fx_status=missing` with a critical data-quality alert
- FX source and timestamp
- CHF equivalent at event date when FX is known

Manual FX overrides require a non-empty note and an audit-log entry.

## Ledger calculation rules

- Cash after system start must be calculated from `transactions`; `cash_balances` is only a snapshot/cache/control view.
- `initial_cash_snapshot` and `initial_position_snapshot` are explicit starting truths, not fabricated historical trades.
- Implement Weighted Average Cost as the MVP internal performance method: buy fees increase cost basis, partial sells remove proportional cost basis, realized P&L is calculated against average cost, full sells zero remaining quantity/cost basis, and dividends do not alter quantity or cost basis.
- WAC is not tax-complete; do not add FIFO/LIFO/tax-lot logic in MVP 1, but keep transaction granularity so it can be added later.
- Position calculations must keep zero-quantity historical positions visible when sale history exists.
- Missing market price or FX must degrade data quality and suppress precise Total Return CHF rather than inventing a value.
- Before productive dashboard use, add alert deduplication per rule/entity/date.
- Market-FX for non-CHF market prices belongs to the later Market/FX provider block.

## Crypto MVP rules

- Crypto inventory is MVP-critical but must remain dummy-first until mapper/dry-run layers are ready; do not touch real coin/wallet files during core implementation. After explicit user approval, real files may be read only from temp/runtime for controlled dry runs using `references/crypto-xlsx-initial-snapshot-dry-run.md`; report only aggregate counts/labels and never quantities or values. Productive safe-subset imports require a second explicit approval and must follow `references/crypto-xlsx-initial-snapshot-production-import.md`: external runtime DB only, no real CSV/XLSX/reports/DBs in Git, Git-safety before/after, import-session + audit-log creation, and aggregate-only reporting. When the user supplies an adjusted real crypto workbook with CoinGecko IDs for missing/previously skipped assets, follow `references/crypto-adjusted-xlsx-and-equity-docx-dryrun.md`: detect the actual structure first, validate IDs against CoinGecko metadata, import only clear missing asset/holding subsets after verified backup, preserve Decimal/Text quantities, ignore legacy CHF values, and delete temporary source files.
- Wallet names must be unique; wallet addresses are optional and must not appear in tests/fixtures.
- Validate wallet type against: Hardware Wallet, Software Wallet, Exchange, Bank/Broker, DeFi, Sonstiges.
- CoinGecko ID is strongly recommended but not hard-required; missing ID creates a data-quality warning and blocks reliable valuation.
- Crypto symbols are not globally unique; symbol conflicts require warning/manual selection, never silent merging.
- Initial crypto holdings are confirmed snapshots by wallet+asset. Store legacy values for provenance/control only, never current valuation.
- Crypto holdings should be calculated/controlled from initial snapshots plus crypto transactions, not silently overwritten.
- Crypto transfers require different source/target wallets, quantity > 0, and same asset; coin fees reduce source-wallet balance.
- Negative wallet balances should be blocked in MVP and produce a critical alert unless a future explicit correction workflow is implemented.
- Crypto buys/sells with fiat impact must create/reference general ledger transactions via `source_type='crypto'`/`source_id` so cash remains ledger-consistent.
- Fiat fees should be ledger fees when unambiguous; avoid double counting when a fee is already embedded in sell net proceeds.
- Unknown fee currency creates a data-quality warning instead of invented accounting.
- Crypto Cost Basis/WAC is not required for MVP 1; MVP 1 prioritizes crypto holdings, wallet structure, current valuation, reports and audit.
- Crypto report context/export must be renderer-neutral and local-only: build from SQLite, aggregate by coin and wallet, use local cached prices only, preserve Decimal/Text values, ignore legacy snapshot values for current valuation, include data-quality warnings, and write generated files only to the external runtime reports directory.
- Crypto PDF export should be optional-dependency tolerant: prefer PDF when a renderer is available, otherwise fall back to HTML/Markdown with a clear warning while still recording report metadata and audit.
- After productive real-data crypto imports, run the post-import runtime verification in `references/crypto-runtime-db-consistency-verification.md`: exact safe-set membership checks, aggregate-only counts, audit/import-session traceability, dashboard render with no live API, runtime-only report generation, and Git-safety before/after.
- Manual dashboard additions/corrections/removals after an initial snapshot must follow `references/mvp-crypto-manual-management-ui.md`: no silent `crypto_holdings` mutation, explicit confirmation, mandatory notes for adjustments/removals, audit-log entries with old/new values, Decimal/TEXT quantity handling, no negative holdings, and no live API lookup during render. For dashboard UX/read-model work, also follow `references/dashboard-user-mode-ux-and-runtime-review.md`: split User Mode from Admin/Review/Debug, aggregate coins across wallets, hide technical IDs in normal views, keep cached-price semantics explicit, and make Crypto Manage actions audited workflows rather than raw table edits.
- Crypto tax logic, tax lots, FIFO/LIFO and detailed cost basis are later modules.
- Keep crypto assets separate from `instruments` for MVP 1, but later evaluate a shared Asset Master if it improves reporting, performance views or watchlists.

## Income/tax rules

For dividends and ETF distributions, separately store:

- gross dividend/distribution
- Swiss withholding tax 35%
- foreign withholding tax
- other tax/withholding if present
- net amount
- original currency
- historic FX to CHF
- gross/net CHF equivalents
- platform/account
- ISIN/ticker
- payment date
- ex-dividend date if available

Plan later ESTV/ICTax support for Swiss year-end values and tax reports, but label outputs as technical reports, not tax advice.

## Market-data rules

- Dashboard reads primarily from local DB, not directly from APIs on page load.
- For Equity/ETF FX and market-data hardening after broker mini-imports, follow `references/equity-fx-market-data-phase-c.md`: validate active `missing_fx` alerts by original transaction currency first, correct only CHF false positives with audit, keep foreign-currency missing-FX alerts active until local historical rates exist, use ISIN as instrument identity and provider symbols only as market-data mappings, and run market-price providers only from explicit CLI/scheduled jobs.
- For the True-Wealth valuation pilot, follow `references/true-wealth-valuation-pilot-c2.md`: do not import more positions, do not guess provider symbols or hedge status, extend instrument metadata for currency hedging/status/valuation policy/corporate-action state, handle historical-FX paywalls as `manual_override_required` without crashing, align price/FX timestamps before claiming valuation precision, and report only aggregate runtime counts.
- For True-Wealth mapping-candidate review after the valuation pilot, follow `references/true-wealth-mapping-candidate-review-c3.md`: create runtime-only provider-symbol candidates keyed by ISIN/instrument, keep name-only or ticker-without-exchange candidates review-required, mark multiple candidates `needs_manual_review`, do not auto-select final mappings on ambiguity, keep hedge/instrument status unknown until confirmed, and ensure market-price dry runs call no provider when there are zero confirmed mappings. For public metadata lookup implementation details, provider result caps, OpenFIGI/Yahoo evidence handling, alert dedupe, runtime-only review templates, and UI/test requirements, use `references/public-instrument-lookup-candidate-generator.md`. For ranking/scoring candidates, generating a runtime-only user decision pack, surfacing `candidate_review_required` and same-ISIN multiple-listing risks, and confirming/rejecting candidates with audit logs, use `references/mapping-candidate-ranking-decision-pack.md`.
- For the broader Instrument Catalog + manual-add workflow, follow `references/instrument-catalog-manual-add-workflow.md`: documents/import files are initial-population aids, but the dashboard must allow audited manual add of equities/ETFs and later coins via search, candidate selection, account/wallet selection, Decimal/Text quantity, date, cost-basis/snapshot info and notes. ISIN is primary for equities/ETFs but can have multiple listings; ticker/symbol alone is never unique; provider symbols are market-data mappings only; CoinGecko ID is primary for crypto provider identity. External lookups may use only non-confidential instrument metadata and must never send quantities, balances, account/wallet IDs, cost basis, private notes or source documents. If DOCX/Broker import is not approved or structurally weak, use `references/manual-equity-etf-entry-wizard.md` as the preferred user path: search on explicit click, show candidates, require conscious selection, allow warned manual creation, then review/confirm an audited initial snapshot or transaction. For the concrete Dashboard/User-Mode implementation pattern, provider order (local/OpenFIGI/Finnhub/FMP/manual), runtime `.env` secret lookup, provider-result caching, and final compile/test/Git-safety/commit/push discipline, also follow `references/manual-position-entry-provider-ux.md`.
- First Streamlit MVP should be a safe, local, read-first shell over SQLite with explicit synthetic demo DB creation only; page render functions must not call CoinGecko/market APIs, and tests should prove that by monkeypatching provider methods to fail.
- Functional UX stabilization work must prioritize making the existing dashboard genuinely usable before adding more pages. Follow `references/dashboard-functional-ux-stabilization.md`: use one navigation system, move executable page modules out of Streamlit `pages/` when using a custom router, hide unfinished pages from User Mode, replace text-link/fake actions with real buttons or disabled controls, enforce session-based Edit Mode for writes, keep IDs/debug notes out of User Mode, and test price/report provider calls happen only on explicit clicks. If the user says the dashboard is still too busy or prototype-like, follow `references/dashboard-usability-simplification.md`: reduce User Mode to only currently useful pages, keep the Command Center calm, avoid misleading `CHF 0.00` Equity/ETF displays when valuation is incomplete, make Crypto the primary MVP surface, and ensure every visible button either works immediately, opens an inline form, or is disabled with a reason.
- Use scheduled jobs to update prices/FX/news.
- Store provider, timestamp, quality status and freshness for every price/FX point.
- Implement caching, local historical storage, batch requests where possible, provider rate-limit queues, and backoff on HTTP 429.
- CoinGecko integrations must be mockable and unit-tested without real API calls; treat HTTP 429 as non-fatal and return a non-fresh data-quality status plus alert after configured retries.
- Crypto price refresh belongs in CLI/scheduled-job commands, not dashboard/report rendering. Prefer CoinGecko batch requests over per-coin requests; expose conservative controls (`--sleep-seconds`, `--max-retries`, `--initial-backoff`, `--max-backoff`, `--only-missing`, `--only-stale`, `--only-symbol`, `--limit`, `--dry-run`, `--currency`). Commands should use aggregate-only output (`total_assets/updated/cached/skipped/stale/warnings/errors/assets_still_missing_local_price`), cache by configurable `max_age_seconds`, store exact Decimal prices as TEXT in `crypto_prices`, and verify dashboard/report contexts read local prices with `live_api_calls=False`. For details and tests see `references/crypto-price-refresh-and-idempotent-btc-runtime.md`.
- Candidate providers: Finnhub, Financial Modeling Prep, Twelve Data, Stooq, Alpha Vantage selectively, Yahoo Finance fallback only; CoinGecko for crypto; later DefiLlama; ESTV/ICTax for Swiss tax values.

## Crypto Decimal precision rules

SQLite has no exact native DECIMAL. In the crypto context, store quantities, prices, crypto fees and valuation-relevant amounts as exact Decimal strings (`TEXT`) and compute with Python `Decimal`. Never convert crypto quantity/price/fee/valuation through float/REAL. Format Decimal writes with `format(value, "f")` so small quantities such as `0.00000001` do not become scientific notation. CSV importers must validate Decimal strings, and tests should assert high-precision preservation plus SQLite text storage. For multi-wallet real-data snapshots and Equity/ETF ledger fields, also see `references/multi-wallet-crypto-and-equity-manage-ui.md`; SQLite `NUMERIC` affinity can coerce Decimal-looking text to `real`, so schema/migrations should use `TEXT` for exact quantities, FX rates, original amounts and CHF equivalents where precision matters.

## Alert lifecycle rules

Alerts must be deduplicated and lifecycle-aware before dashboards run repeated calculations. Use a dedup key from `rule_id`, `entity_type`, `entity_id`, `priority` and an error fingerprint. Alerts should carry `status` (`active`, `resolved`, `muted`), `resolved_at`, optional `muted_until`, `last_seen_at`, `occurrence_count`, `fingerprint` and `dedup_key`. Re-seeing an identical active/resolved/muted alert should update `last_seen_at`/`occurrence_count` rather than create a new active row; changed fingerprints may create a new alert.

## Git/GitHub safety

Code/scripts/docs may be stored in a private Git repo, but never commit financial data. Use the `github-repo-management` skill and its `references/sensitive-code-backup.md` guidance.

Minimum `.gitignore` for finance repos must block `data/`, `reports/`, `exports/`, `backups/`, DB files, spreadsheets, PDFs, DOCX, raw CSV/JSON, `.env`, tokens, credentials and client secrets. Only synthetic examples under `examples/` are acceptable.

## MVP implementation safety gate

Before any real broker/bank/portfolio/crypto data is imported, build and verify the safety foundation described in `references/mvp-safety-gate-implementation.md`: repo skeleton, `.gitignore`, `.env.example`, runtime outside repo, settings validation, SQLite schema, synthetic fixtures, audit log, CSV dry-run, duplicate protection, and Git-safety scan. Run the safety scan before staging, committing, or pushing. If GitHub credentials are needed from Drive, use them only in a temporary location and never echo token values.

- Before broader productive imports, implement or verify the runtime backup loop in `references/runtime-backup-and-broker-mapping.md`: backup outside Git, SHA256 verification, restore requiring explicit confirmation, tests for backup/restore/checksum, and Git-safety coverage that blocks backup artifacts in the repo. For PostFinance/True Wealth/Raiffeisen, perform structural mapping and dry-runs only until the user approves import; report aggregate counts/field coverage/quality flags only, never real values or raw rows. If backup CLI output is too terse to evidence the backup path/checksum, call `jarvis_finance.runtime.backup.backup_runtime_db(...)` and `verify_backup(...)` directly and report only path-existence/outside-repo/checksum status, not DB contents.

## Common pitfalls

- Starting later analytics (Monte Carlo, backtesting, rebalancing, scoring, heatmaps, projections) while import/mapping/data-quality phases are still being hardened or while the user explicitly asked to postpone them.
- Treating a holdings snapshot as a real transaction history.
- Mixing price P&L and FX P&L.
- Letting dashboard refreshes hammer APIs.
- Committing realistic sample data to Git because the repo is private. Private GitHub is not a financial data vault.
- Showing real portfolio values back to the user unnecessarily in summaries.
- Designing Git-safety scans that block source package names like `src/.../imports` or `src/.../reports`; block top-level runtime/data directories instead.
- In broker/bank real-file dry-runs, aggregating Data Quality flags only for `review_status='open'`. Blocked review items are still actionable data-quality issues; include `open` and `blocked` so defensive Raiffeisen aggregate-only rows remain visible.
- Letting manual review actions blur into productive import actions. Review-metadata writes (ISIN/ticker/exchange/account/instrument confirmations, ignore/resolve, dry-run archive/current status) may be allowed with audit logs, but they must not write `positions_snapshot`, `transactions`, `cash_balances`, ledger rows, or cash snapshots. Name-only mapping must never become `mapped`/`ready_for_import`; ticker-only without exchange remains review-needed; `aggregate_only` remains blocked for instrument import. In guided pilots, do not force `ready_for_import` by direct status edits; let readiness logic derive it after audited metadata actions, and if parser presence flags were missed, correct only boolean presence metadata with an audit event, never actual quantities/values.
- Skipping the execution-plan layer between ready review items and productive broker imports. A final dry-run should materialize runtime-only execution plans with source row hash, target IDs, exact Decimal-text payload summary, quality flags and planned write status. Productive mini-imports should consume exactly one planned ready payload, write exactly one ledger `initial_position_snapshot`, mark that plan/review item imported, leave the other ready plans untouched, and verify zero direct `positions_snapshot`/cash writes. After the first productive mini-import, do not proceed straight to mass import: run regression checks, implement/test void and correction audit paths, verify backup/restore to a separate test DB, and import at most one additional ready plan. When later completing the final ready plan, first resolve Data Quality alert ambiguity by counting only active alerts (`status='active'`) and treating resolved rows as history; then import exactly one plan and consolidate counts. See `references/broker-import-execution-plan-mini-import.md`, `references/broker-mini-import-regression-and-corrections.md`, and `references/broker-mini-import-completion-and-dq-consolidation.md`.
- Running compile/tests before Git-safety and forgetting generated `__pycache__`; remove or ignore generated caches before safety scans. `pytest` may recreate `.pytest_cache`, so remove `__pycache__`/`.pytest_cache` again after test execution and before `git-safety-scan`.
- Treating every active `missing_fx` alert after a broker mini-import as a bug. First aggregate by original currency: CHF rows may be false positives (`fx=1`, `not_needed`, resolve with audit), but foreign-currency rows without local historical FX should remain active and block precise CHF valuation until rates are populated.
- Auto-mapping Equity/ETF market prices by instrument name or ticker alone. ISIN is the instrument identity, but one ISIN can have multiple listings across exchange/currency, so even ISIN matches may need candidate selection. Provider symbols are separate market-data mappings, ticker without exchange is review-needed, and missing provider symbols should create deduplicated Data Quality alerts rather than triggering provider guesses. For mapping-candidate phases, candidate creation is allowed in the runtime DB, but final selection must remain manual/audited unless the user explicitly approves and the match is unambiguous. Public lookup endpoints can return dozens of listings; cap result sets, dedupe active mapping alerts by rule/entity, and do not treat search-fallback results as ISIN-confirmed unless the provider response supplies ISIN evidence.
- Designing future portfolio entry as import-file-only. Imports/documents are for initial population and existing holdings; the system must also support dashboard manual add/search workflows with audited ledger writes, explicit candidate selection, Decimal/Text quantities, required notes where history is incomplete, and no silent overwrites. If the user says DOCX/Broker files are too unsafe or not approved, stop the productive import path and pivot to the manual Equity/ETF wizard in `references/manual-equity-etf-entry-wizard.md`; keep the review queue optional/admin-only, ensure manual-entry broker accounts exist, and do not expose technical IDs in User Mode. The manual entry path must be visible in normal User Mode (e.g. `Position hinzufügen`) with Command Center routing; provider lookup must be explicit-click only, cache results locally, load provider keys from runtime secrets, and degrade missing keys to warnings. See `references/instrument-catalog-manual-add-workflow.md` and `references/manual-position-entry-provider-ux.md`.
- Letting an Equity/ETF market-price dry run call providers when no confirmed mappings exist. The safe outcome is `total_mappings=0`, no provider calls, and aggregate reporting only.
- For valuation pilots on historical broker snapshots, treating a computable current market value as a clean performance result. `snapshot_only`, `cost_basis_uncertain`, missing hedge confirmation, missing historical FX, stale price/FX timestamp alignment, or suspected corporate actions must keep valuation `partially_valuable` or suppress precise Total Return until reviewed.
- Inferring CHF-hedged ETF behavior from the name alone. Hedge status is methodology-critical: unknown status should create a warning/review item; confirmed CHF hedging must prevent naive free FX-PnL attribution.
- Crashing or blocking on historical-FX provider paywalls. Persist `manual_override_required`, create deduplicated alerts, keep the flow moving, and require a noted audited manual override instead of guessing latest FX.
- Productive real-data imports can partially write before surfacing schema/importer compatibility issues. Do not rerun blindly or dump row-level data; inspect aggregate counts and unique identifiers needed for idempotency, patch/complete via missing-only inserts, then verify committed import session, audit log, Git clean and Git-safety OK.
- In controlled one-coin runtime tests from a real XLSX, distinguish **one coin/asset** from **one holding/wallet row**. A coin may be split across multiple wallet columns; if the user required an unambiguous target wallet or one holding, stop and ask rather than choosing a wallet silently. If the user explicitly approves multi-wallet import for that coin, import exactly one asset plus one audited holding per non-empty approved wallet cell; verify aggregate counts only. If re-running a BTC/single-coin test finds the exact approved asset and holdings already present, do not import duplicates; perform the aggregate-only idempotency checks and report that asset/holding counts did not increase because duplicate prevention succeeded. See `references/crypto-single-coin-runtime-test.md`, `references/multi-wallet-crypto-and-equity-manage-ui.md`, and `references/crypto-price-refresh-and-idempotent-btc-runtime.md`.
- After productive crypto imports, do a separate aggregate-only consistency pass before building new features: DB/runtime outside repo, exact safe-subset membership, no duplicate/negative/orphan holdings, correct snapshot date, null legacy-value fields when ignored, import sessions committed, holding-level audit traces present, dashboard local-read/no-live-API verified, and report generated only under runtime reports.
- Letting a dashboard correction UI mutate crypto holdings directly. Add/remove/edit operations must become audited transactions or `manual_adjustment` events with mandatory notes where appropriate; preserve history instead of silently overwriting balances.
- Letting normal dashboard pages become technical raw-table dumps. For this user's Finance dashboard, implement an Alltag/User Mode that hides internal IDs/provider internals and presents aggregate, actionable read models; keep raw identifiers, candidate details and audit/debug fields in Admin/Review/Data Quality views. See `references/dashboard-user-mode-ux-and-runtime-review.md`.
- Treating Streamlit dashboard UX stabilization as a chance to build more modules. When the user complains about prototype feel, first eliminate duplicate navigation, empty User Mode pages, fake/text buttons, unclear Read-only/Edit state, and raw technical IDs. Keep unfinished pages in Admin/Debug or hide them; every visible button must work, prefill a real workflow, or be disabled with a reason. See `references/dashboard-functional-ux-stabilization.md` and `references/dashboard-usability-simplification.md`.
- Leaving an accepted sprint half-finished because the next feature is tempting. If cleanup, final tests, Git-safety, commit, and push are still missing, finish those in order before starting new work. Remove `.pytest_cache`/`__pycache__` before and after tests, then run Git-safety, `git diff --check`, verify clean status, commit, push, and fetch/update `origin/main` to prove sync. See `references/dashboard-usability-simplification.md`.
- Running Git-safety immediately after pytest without cleaning generated caches. Pytest can recreate `.pytest_cache`; remove `.pytest_cache` and `__pycache__` after the final test run, then run Git-safety before staging/commit/push.
- Relying on the user's prose description of a spreadsheet layout instead of detecting the actual workbook structure. In adjusted crypto XLSX files, CoinGecko IDs may appear as an `API ID` column in the same row rather than a preceding row; use the detected structure, validate IDs, and report the difference aggregate-only.
- Treating formula/scientific-notation source cells as automatic import blockers. Count them, but block only when exact Decimal/Text conversion fails; never use float arithmetic for crypto quantities.
- Printing raw DOCX/table rows while analyzing real broker files. Use masked structural flags and aggregate counts only; real position names/values/quantities stay out of chat/log summaries.
- Counting ticker-like tokens from DOCX as confirmed Equity/ETF mappings. Without ISIN plus exchange/provider confirmation, mappings are `probable` or `needs_manual_review`, not productive-import ready.
- Treating low-confidence Equity/ETF DOCX extraction as enough for import. If most positions lack ISIN, cost basis or transaction history, build/operate a staging resolver and Mapping Review Queue first. Ticker-only rows stay `needs_manual_review`; local Qwen may help extract candidates but must not decide mappings or write ledger rows. See `references/equity-docx-instrument-resolver-review-workflow.md`.
- Treating verifier/file-mutation warnings as either automatically true or automatically false. Check the exact commit with `git show --name-status --patch <commit> -- <file>`, then separately verify whether the test matrix actually covers the promised cases.
- Adding broad Git-safety tests that only assert `len(findings) >= N`; prefer explicit assertions for token filename, PAT patterns, private keys, CSV/JSON path policy, runtime/data directories, allowed synthetic paths, `config.example/`, and normal `src/` false-positive protection.

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


Explanation:
**Inspecting repo paths**

I need to look at the repo paths since the user is asking for commands. I can safely provide mkdir and chmod commands. It’s likely that the finance runtime is located in /jarvis_runtime/finance-system/secrets. I want to remind the user not to send sensitive information in the chat, maybe using read -s for that. Also, the OpenFIGI environment variable is likely OPENFIGI_API_KEY, which could be in a .env file in the runtime rather than the repo. I'll check on existing file naming as well.


Mein Herr, bitte **nicht hier in Telegram posten**. Legen Sie den OpenFIGI-Key im Runtime-Secrets-Bereich ab — außerhalb von Git:

```bash
mkdir -p ~/jarvis_runtime/finance-system/secrets
chmod 700 ~/jarvis_runtime/finance-system/secrets
```

Dann den Key sicher eintragen, ohne ihn in die Shell-History zu schreiben:

```bash
read -rsp "OpenFIGI API key: " OPENFIGI_API_KEY; echo
cat > ~/jarvis_runtime/finance-system/secrets/openfigi.env <<EOF
OPENFIGI_API_KEY=$OPENFIGI_API_KEY
EOF
unset OPENFIGI_API_KEY
chmod 600 ~/jarvis_runtime/finance-system/secrets/openfigi.env
```

Kurzer Check, ohne den Key auszugeben:

```bash
test -s ~/jarvis_runtime/finance-system/secrets/openfigi.env \
  && grep -q '^OPENFIGI_API_KEY=' ~/jarvis_runtime/finance-system/secrets/openfigi.env \
  && echo "OpenFIGI key stored safely."
```

Wenn Sie ihn in einer Shell-Session nutzen wollen:

```bash
set -a
source ~/jarvis_runtime/finance-system/secrets/openfigi.env
set +a
```

Ablageort also:

```text
~/jarvis_runtime/finance-system/secrets/openfigi.env
```

Schön trocken, außerhalb des Repos, mit `600` Permissions — genau dort, wo ein API-Key hingehört und nicht in irgendein fröhlich commitbares `.env`.

Explanation:
**Planning secure storage**

I’m trying to figure out how to securely store commands without echoing keys in the history. Using `read -s` will help with that. I’m thinking of saving the commands in a `secrets/.env.marketdata` file and ensuring it has the right permissions with `chmod`. It might also be helpful to set up a symlink, especially if the app expects a `.env` file. Since there’s no current code, I’ll designate a canonical runtime secret file outside of Git.