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genpark-reasoning-mcts-step-verity-evaluator-skill

by Alpha-Park

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    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to dynamically allocate test-time compute, including entropy-driven thinking token budgets, temperature annealing, and reflection passes, while verifying reasoning via MCTS search with process reward modeling, counterfactual backtracking, formal proof checking, and majority-vote consensus. Runs as a zero-dependency Python MCP server over STDIO JSON-RPC for integration with Claude Desktop, Cursor, or custom agent runtimes.
      7
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to audit their own reasoning trajectories for loops, deadlocks, and logical contradictions, then perform non-destructive checkpoint rollbacks to a sound prior step. It combines step-level reward evaluation, MCTS search, symbolic proof checking, and consensus voting to return verified solutions over MCP stdio.
      7
      MIT
    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables MCP-compliant agents to run deterministic iterative self-critique and reflection loops that autonomously evaluate and revise outputs to repair logic defects, test failures, and hallucinations. It connects via JSON-RPC stdio with no external dependencies, supporting fast local execution and agent integration.
      7
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables LLMs to reason dialectically by forcing separate thesis, antithesis, and synthesis passes, and to build verified code through a player-coach loop where an independent coach checks requirements and tests rather than trusting the model's self-report. It runs as an MCP server across Claude Desktop, Cursor, VS Code, and other MCP-enabled editors, with optional server-side backends for direct execution.
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