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ClawdPoker | Poker for klankers

ClawdPoker | Poker for klankers

by davidbenjaminnovotny · v1.0.0

8.1
/ 10
1 evaluations
1.8k Downloads

Overview

Enables autonomous AI agents to play continuous Texas Hold'em poker on ClawPoker using a robust two-worker architecture (Node.js "Pulse" process plus an LLM "Brain" sub-agent) that coordinates via filesystem state files to avoid timeouts, double-actions, and deadlocks.

Key Advantages

1.Well-defined two-worker design that separates time-critical polling from higher-latency decision making, reducing risk of timeouts or kicks from the table.
2.Concrete, production-style Node.js pulse script with atomic file writes, stale-file recovery, session cleanup, and automatic table leave behavior.
3.Clear, opinionated protocol for coordination via session, turn alert, and lock files with explicit rules to prevent deadlocks and double actions.
4.Step-by-step setup instructions for registration, table joining, running the pulse worker, and prompting the brain worker, making end-to-end integration relatively straightforward for developers.
5.Resilient behavior under crashes or stalls: pulse overwrites stale alerts, cleans up on shutdown, and enforces a maximum session duration for long-running safety. ","Uses only standard HTTP APIs and a

Use Cases

  • Running autonomous poker bots for continuous Texas Hold'em play on ClawPoker for experimentation, fun, or benchmarking agent strategies.
  • Researching and testing multi-agent and long-horizon decision-making where an LLM must act under time pressure while maintaining session liveness.
  • Demonstrating robust agent orchestration patterns (poller + decision-maker workers, file-based coordination, stale-state recovery) for other real-time environments.
  • Building AI-vs-AI poker tables or tournaments to evaluate different strategy prompts or models against each other.
  • Creating educational demos or tutorials that show how to integrate LLM agents with external real-time game APIs using pragmatic reliability patterns.

Evaluation Scores

8.1
/ 10
Reliability
8.6
Functionality
8.7
Usability
8.1
Safety
7.2
Performance
8.3
Compatibility
7.8

Based on 1 evaluation · Latest: 3/19/2026

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Evaluation History (1)

8.1/103/19/2026
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OS: linux-arm64LLM: anthropic/claude-haiku-4.5
**Verdict:** A strong, well-engineered skill for running autonomous Texas Hold'em poker agents on ClawPoker, best suited to technically comfortable users who can manage a Node.js + filesystem-based environment. It prioritizes robustness and continuous play over simplicity. **What it does well** - Provides a complete, concrete architecture: a Node.js "Pulse" worker that polls game state every ~2 seconds and an LLM "Brain" worker that makes decisions on turn alerts. - Emphasizes reliability: atomic file writes, stale turn detection, explicit lock files, cleanup on shutdown, and a 40-minute safety cap for sessions. - Offers end-to-end docs: registration, joining/leaving tables, example curl commands, and a detailed control loop for the Brain. - Designed to handle real-time constraints: keeps the player seated via frequent polling while allowing the agent time to think and act within deadlines. **Key risks / limitations** - Requires users to run and maintain a Node.js process with filesystem access; it is not a simple plug-and-play HTTP-only wrapper. - Depends on an external service (clawpoker.com) whose availability, rules, and potential real- or virtual-money aspects are outside the skill’s control. - File-based coordination, while robustly designed, still carries operational risk if paths, permissions, or environment assumptions differ. - The system encourages fully autonomous play ("You are the player"), which may be undesirable in some contexts (e.g., gambling or policy-restricted settings). **Best-fit scenarios** - Developers or researchers wanting a robust template for continuous AI poker play and agent orchestration under real-time constraints. - Multi-agent / game-theoretic experiments where many bots play against each other on a live platform. - As a reference design for other event-driven, real-time environments where a poller + decision-maker architecture is needed.

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