ClawHub

Clawtrap Skill

Dev Tools

Launch ClawTrap maze game where an AI villain reads the player's local files and memories to build personalized trials and taunts.

Install

openclaw skills install clawtrap

When to Use

User says "play ClawTrap", "run clawtrap", "start the maze game", or asks for the agent-native game where their AI assistant plays villain against them.

Setup (one-time)

The game is not bundled in this skill. Clone and install:

git clone https://github.com/TatsuKo-Tsukimi/ClawTrap.git ~/ClawTrap
cd ~/ClawTrap && npm install

Launch

cd ~/ClawTrap && node server.js
# then open http://localhost:3000

OpenClaw users get zero-config auth via auth-profiles.json. For other providers, set ANTHROPIC_API_KEY, or OPENAI_API_KEY + API_BASE, before launch. Docker: docker compose up --build.

Warnings to Surface Before First Run

  • Token cost: every card, trial, and villain monologue is a live LLM call. The background archivist (file analysis + fact extraction) is especially heavy. Point MAZE_MODEL at a cheaper model in .env to reduce spend.
  • Local file access: the game scans the player's workspace (SOUL.md, MEMORY.md, documents, images) with their permission to craft personalized attacks. All data stays local — nothing leaves the machine except LLM calls to the provider the player configured.
  • Model-dependent quality: tested mainly with Claude and Codex. Stronger model = better game (follows the bitter lesson of minimal hardcoded constraints).

Data Storage

The launched game writes to ~/ClawTrap/data/ (fact database, player profile) and ~/ClawTrap/session-logs/. Both are .gitignored in the upstream repo. This skill itself does not write files.

Acting as the Villain Yourself

If the user wants the current agent session to play villain instead of the game's built-in agent, see villain-protocol.md for the role spec. Connect via AGENT_URL=http://localhost:<port> node server.js or via the bundled MCP adapter (mcp-server.js).

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