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metaclaw-manager

Self-management skill for MetaClaw - configure LLM models, channels, skills, and all settings through natural language

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Informações da origem

Repositório
yetone/metaclaw-dist
Última atividade na origem
30 de março de 2026 às 12:08
Idioma detectado do SKILL.md
inglês
Estrelas
8
Forks
0

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SKILL.md
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name
metaclaw-manager
description
Self-management skill for MetaClaw - configure LLM models, channels, skills, and all settings through natural language
license
MIT
compatibility
["metaclaw"]
allowed-tools
["ReadFile","WriteFile","EditFile","Bash"]
metadata
{"version":"0.1.0","author":"MetaClaw","builtin":true}
# 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
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