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genpark-jev-typed-state-action-router-mcp

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    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to arbitrate typed state-action schemas and dispatch deterministic actions locally, so routine or reflexive decisions are resolved in sub-millisecond fashion instead of incurring expensive frontier-LLM calls. It also applies token-saving pre-escalation filters, escalating only ambiguous or multi-hop plans to larger models while enforcing reversible execution checkpoints, strict token budgets, and local-first memory retention.
      7
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to resolve routine typed routing, loop-stall arbitration, and tool safety checks locally instead of invoking a frontier LLM, returning schema-enforced decision outputs and telemetry at sub-millisecond latency. Also provides reversible execution checkpoints, token budgets, and decay-based episodic memory for safe, privacy-preserving autonomous operation.
      7
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to resolve typed routing, loop-stall arbitration, and tool safety checks locally at sub-millisecond latency, avoiding unnecessary frontier LLM calls. It enforces reversible execution checkpoints, token budgets, and decayed episodic memory for safe, privacy-first autonomous operation.
      7
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to combine ambient multimodal perception, continuous episodic memory, and recency-decay context briefing for fast deterministic decisions and safe tool routing. It integrates with MCP clients to reduce unnecessary frontier LLM calls while enforcing token budgets and local-first memory retention.
      7
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables personal AI agents to perceive ambient context, retain episodic memory with decay, act proactively, and route routine decisions through fast System-1 reflexes while escalating ambiguous multi-hop plans to frontier LLMs. Includes reversible execution checkpoints, token budgets, and local-first memory retention, and plugs into MCP clients like Claude Desktop, Cursor, and Windsurf.
      7
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables personal AI agents to route routine, reflexive decisions through fast deterministic System-1 cognition while reserving frontier LLM calls for ambiguous multi-hop plans. Combines ambient perception, decayed episodic memory with contradiction resolution, and proactive sensing behind reversible execution checkpoints, token budgets, and local-first memory retention.
      7
      MIT