yetone/metaclaw-dist/metaclaw-manager

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  • community
  • ext:[{"type":"config","description":"Configuration overrides"}]
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Self-management skill for MetaClaw - configure LLM models, channels, skills, and all settings through natural language

Install

npx vskill@latest install yetone/metaclaw-dist/metaclaw-manager

Semi-extensibleMentions customization, but needs skill-specific knowledge. Read the extensible skills standard

SKILL.md

MetaClaw Manager

This skill enables MetaClaw to manage its own configuration and state through natural language commands.

Configuration File

MetaClaw uses metaclaw.toml for configuration. The file is located in the project root or can be specified via --config.

Reading Configuration

To check current settings, read the metaclaw.toml file:

ReadFile: metaclaw.toml
Modifying Configuration

Use EditFile to modify specific settings in metaclaw.toml. Common modifications:

Change LLM model:

toml
[llm]
model = "claude" # Options: claude, gpt4, gemini, azure, huggingface, or full provider/model string

Adjust agent behavior:

toml
[agent]
max_iterations = 25
sandbox = "basic" # Options: none, basic, docker

Enable/disable channels:

toml
[channels.slack]
enabled = true
[channels.discord]
enabled = false

Environment Variables

API keys and secrets are stored in .env (never in metaclaw.toml). Common variables:

  • ANTHROPIC_API_KEY - Anthropic Claude
  • OPENAI_API_KEY - OpenAI GPT
  • GEMINI_API_KEY - Google Gemini
  • SLACK_BOT_TOKEN / SLACK_APP_TOKEN - Slack
  • DISCORD_BOT_TOKEN - Discord
  • TELEGRAM_BOT_TOKEN - Telegram

Skill Management

List installed skills:

bash
metaclaw skill list

Install a skill:

bash
metaclaw skill install <url-or-path>

Create a new skill:

bash
metaclaw skill create <name> --desc "description"

Skills are stored in:

  • Project: .metaclaw/skills/
  • User: ~/.metaclaw/skills/

Channel Management

List channels:

bash
metaclaw channel list

Start server with channels:

bash
metaclaw start

Diagnostics

Check system status:

bash
metaclaw version
pip show metaclaw

Test LLM connection:

python
from metaclaw.llm import LLMProvider
provider = LLMProvider(model="claude")
# await provider.chat(messages=[{"role": "user", "content": "test"}])

Guidelines

  • Never store API keys in metaclaw.toml - always use .env
  • When changing models, verify the API key env var is set
  • When enabling channels, guide the user through token setup
  • Back up metaclaw.toml before making changes
  • Test changes by restarting the agent

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

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Extension points

  • configConfiguration overrides

Works with

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