genpark-agent-recursive-self-critique-reflection-skill

mcp
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SUMMARY

Multi-agent recursive self-critique and reflection engine executing iterative evaluation-revision loops to autonomously repair logic defects, test failures, and hallucinations.

README.md

genpark-agent-recursive-self-critique-reflection-skill

Python 3.9+
License MIT
MCP Compatible
GenPark AI
Zero Dependencies

Production-Grade AI Agent Infrastructure Skill • 100% Standard Library Python • Native Model Context Protocol (MCP)

🌐 GenPark MCP Hub • 📦 GenPark Official • 📖 Documentation


📌 Overview & Capability

genpark-agent-recursive-self-critique-reflection-skill is a deterministic, high-performance, zero-dependency Python tool and native Model Context Protocol (MCP) server engineered for next-generation personal agents, multi-agent frameworks, and autonomous developer workflows.

Executive Capability: Multi-agent recursive self-critique and reflection engine executing iterative evaluation-revision loops to autonomously repair logic defects, test failures, and hallucinations.

⚡ Key Highlights

  • 🐍 Zero External pip Dependencies: Implemented entirely with pure Python standard library for instant zero-overhead execution.
  • 🔌 Native Model Context Protocol (MCP): Plugs directly into any MCP-compliant client via JSON-RPC 2.0 stdio.
  • ⚡ Sub-Millisecond Execution: Slashes token burn and latency by resolving routine agent tasks deterministically without frontier LLM round-trips.
  • 🛡️ Production-Hardened: Comprehensive error handling, boundary validation, and telemetry.

🏗️ Architecture

graph LR
    Agent([🤖 Autonomous Agent / IDE]) -->|MCP Protocol / JSON-RPC| Server[⚡ genpark-agent-recursive-self-critique-reflection-skill Server]
    Server --> Core[🧠 Deterministic Processing Core]
    Core --> Out[📊 Actionable Result & Telemetry]
    Out --> Agent

🚀 Quickstart & Usage

1. Direct Python Client Execution

python example_usage.py

2. Programmatic Integration

from client import AgentRecursiveSelfCritiqueReflection

client = AgentRecursiveSelfCritiqueReflection()
result = client.run_reflection_benchmark()
print(result)

🔌 Model Context Protocol (MCP) Setup

Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:

claude_desktop_config.json

{
  "mcpServers": {
    "genpark-agent-recursive-self-critique-reflection-skill": {
      "command": "python",
      "args": ["/path/to/genpark-agent-recursive-self-critique-reflection-skill/mcp_server.py"]
    }
  }
}

Direct MCP Testing

python mcp_server.py --test

📊 Technical Specifications

Parameter Type Required Description
payload string / dict Yes Primary context, text, or task input
options dict No Execution flags, thresholds, or sensitivity bounds

Maintained with ❤️ by GenPark AI Engineering • Powering Next-Gen Autonomous AI Agents 🌍

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