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Clawkeeper

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SafeAI-Lab-X
clawkeeper

Install, configure, verify, and debug the Clawkeeper watcher stack in this workspace. Use when a user asks to set up `clawkeeper`, initialize `remote` or `local` mode, enable `clawkeeper-watcher`, wire `clawkeeper-bands`, diagnose `context-judge` routing, inspect watcher logs, fix mode/config mismatches, or troubleshoot startup, audit, hardening, rollback, drift monitoring, or bridge notification issues.

Overview

PublisherSafeAI-Lab-X
RepositoryClawKeeper
Skill nameclawkeeper
Stars
1K
Forks
57
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by SafeAI-Lab-X on GitHub. Read the source before you install it.

Installation

Install the Clawkeeper AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/SafeAI-Lab-X/ClawKeeper/tree/main/legacy/clawkeeper-watcher/skills/clawkeeper
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/SafeAI-Lab-X/ClawKeeper.git /tmp/ClawKeeper
mkdir -p .claude/skills
cp -r /tmp/ClawKeeper/legacy/clawkeeper-watcher/skills/clawkeeper .claude/skills/clawkeeper
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Clawkeeper in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Clawkeeper on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Clawkeeper is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Clawkeeper

Use this skill only for the Clawkeeper workspace. Treat clawkeeper-watcher as the product center and clawkeeper as the launcher that prepares mode-specific runtime state.

Core mental model

  • plugins/clawkeeper-watcher/ is the watcher plugin and governance engine.
  • clawkeeper/ is the launcher that prepares isolated remote and local mode roots, then delegates to OpenClaw.
  • plugins/clawkeeper-bands/ is the user-side bridge for notifications and approvals.
  • remote is read-only judgment and historical intelligence.
  • local is trusted audit, hardening, rollback, drift monitoring, and skill guard.
  • Both watcher modes expose POST /plugins/clawkeeper-watcher/context-judge.

Read these files when needed:

  • README.md
  • plugins/clawkeeper-watcher/README.md
  • plugins/clawkeeper-bands/README.md
  • clawkeeper/src/cli.ts

Preferred workflow

Follow this order unless the user explicitly narrows the task:

  1. Identify whether the user wants install, config, validation, or debugging.
  2. Check whether the issue is about the launcher, the watcher plugin, or the bands bridge.
  3. Verify the exact mode in play: remote, local, or both.
  4. Run the smallest direct validation command first.
  5. Only after validation fails, inspect config, logs, bridge wiring, and code paths.

Do not jump straight to speculative fixes.

Install and initialize

For source checkout setup in this repo, use:

bash
pnpm install
cd clawkeeper
npm install
npm run build
npm link
cd ..

Initialize modes with:

bash
clawkeeper init remote
clawkeeper init local
clawkeeper local config set gateway.mode local
clawkeeper status

Important:

  • local mode expects gateway.mode=local.
  • The launcher stores mode state under ~/.clawkeeper/ by default unless --root overrides it.
  • If the problem is only inside the watcher plugin, do not blame launcher setup until clawkeeper status or mode launch actually fails.

Validation commands

Use the most direct command for the claimed problem.

Launcher validation

bash
clawkeeper --help
clawkeeper status
clawkeeper init remote
clawkeeper init local

Mode launch validation

bash
clawkeeper remote gateway run
clawkeeper local gateway run

Watcher validation

bash
clawkeeper remote clawkeeper-watcher status
clawkeeper remote clawkeeper-watcher logs
clawkeeper remote clawkeeper-watcher fingerprints
clawkeeper remote clawkeeper-watcher profiles

clawkeeper local clawkeeper-watcher status
clawkeeper local clawkeeper-watcher logs
clawkeeper local clawkeeper-watcher audit
clawkeeper local clawkeeper-watcher harden
clawkeeper local clawkeeper-watcher monitor
clawkeeper local clawkeeper-watcher rollback
clawkeeper local clawkeeper-watcher scan-skill <name-or-path>

Context-judge validation

Confirm that the route is the watcher route, not the bands route:

text
POST /plugins/clawkeeper-watcher/context-judge

Bridge validation

Install the receiving-side bridge plugin with:

bash
openclaw plugins install --link /path/to/clawkeeper/plugins/clawkeeper-bands

Then verify the local watcher bridge config:

bash
clawkeeper local config set plugins.entries.clawkeeper-watcher.config.notify.userBridge.enabled true
clawkeeper local config set plugins.entries.clawkeeper-watcher.config.notify.userBridge.url http://127.0.0.1:18889
clawkeeper local config set plugins.entries.clawkeeper-watcher.config.notify.userBridge.token <gateway-token>

Debugging order

When debugging, follow this sequence:

  1. Confirm the exact failing command.
  2. Confirm whether the command is running in remote or local.
  3. Confirm whether the command is launcher-level or watcher-level.
  4. Inspect current config relevant to that failure.
  5. Read watcher logs or gateway output.
  6. Check bridge endpoint path and token if notifications or approvals are involved.
  7. Only then inspect code.

Report the first verified failing boundary, not every possible theory.

Common failure patterns

Local command run in remote mode

Symptoms:

  • audit, harden, monitor, or rollback rejected
  • output says the command is only available in local mode

Fix:

  • rerun on the local instance
  • verify CLAWKEEPER_MODE or config mode if behavior is unexpected

gateway.mode mismatch

Symptoms:

  • local launch behaves like plain or wrong mode
  • local-only watcher behavior does not appear

Fix:

  • set clawkeeper local config set gateway.mode local
  • restart the local mode process

Wrong route when testing context judgment

Symptoms:

  • request sent to bands instead of watcher
  • remote judgment appears missing

Fix:

  • use POST /plugins/clawkeeper-watcher/context-judge for watcher judgment
  • use clawkeeper-bands only for the receiving-side bridge and approval surface

Bridge configured but notifications do not arrive

Symptoms:

  • startup audit or approval summary never reaches user-side gateway

Check:

  • bridge enabled
  • bridge url
  • bridge token
  • receiving gateway has clawkeeper-bands installed
  • user-side receiver path exists and gateway is reachable

Logs exist but the wrong file is inspected

Symptoms:

  • "no events" while watcher is active

Check:

  • today vs explicit --date
  • current mode and workspace
  • whether the command is reading watcher event logs or launcher stdout

Use:

bash
clawkeeper local clawkeeper-watcher log-path
clawkeeper local clawkeeper-watcher logs --all
clawkeeper local clawkeeper-watcher logs --date YYYY-MM-DD

Audit result interpreted as host hardening

Symptoms:

  • user expects firewall, SSH, or OS policy changes

Clarify:

  • Clawkeeper watcher audits and hardens OpenClaw-side runtime state
  • it does not automatically perform generic host OS hardening

Command accuracy guardrails

Do not invent flags or routes. Prefer commands already documented in:

  • README.md
  • plugins/clawkeeper-watcher/README.md
  • clawkeeper/src/cli.ts

Current launcher surface:

  • clawkeeper init <mode>
  • clawkeeper status
  • clawkeeper remote ...
  • clawkeeper local ...

Current watcher CLI surface includes:

  • audit
  • harden
  • monitor
  • rollback
  • status
  • logs
  • log-path
  • scan-skill
  • fingerprints
  • profiles

Response expectations

When using this skill:

  • State whether the issue is launcher, watcher, or bridge related.
  • State whether it is remote, local, or cross-mode.
  • Show the exact command you used to validate the issue.
  • Separate verified facts from inference.
  • Prefer the narrowest fix that matches the failing boundary.

Frequently asked questions

What does the Clawkeeper AI skill do?

Install, configure, verify, and debug the Clawkeeper watcher stack in this workspace. Use when a user asks to set up `clawkeeper`, initialize `remote` or `local` mode, enable `clawkeeper-watcher`, wire `clawkeeper-bands`, diagnose `context-judge` routing, inspect watcher logs, fix mode/config mismatches, or troubleshoot startup, audit, hardening, rollback, drift monitoring, or bridge notification issues.

Why use Clawkeeper on TypingMind?

Because you install it once and use it with any model. Clawkeeper is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Clawkeeper in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/SafeAI-Lab-X/ClawKeeper/tree/main/legacy/clawkeeper-watcher/skills/clawkeeper. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Clawkeeper?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Clawkeeper?

As many as you like. As long as a model supports skills, you can use Clawkeeper with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Clawkeeper AI skill free?

It is published on GitHub by SafeAI-Lab-X. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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