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genpark-context-window-lost-in-middle-reorderer-skill

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    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to retrieve relevant context via a zero-dependency hybrid search engine that blends sparse keyword-based lexical ranking with dense vector similarity scores into one fused result set, then refines it with knowledge graph triplet expansion and lost-in-the-middle context reordering. It also provides episodic memory consolidation, recency decay, and semantic query caching, exposed as a JSON-RPC 2.0 stdio MCP server for clients such as Claude Desktop, Cursor, and Windsurf.
      7
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables hybrid retrieval over agent memory and documents by fusing BM25 lexical and cosine vector rankings with reciprocal rank fusion, plus knowledge graph expansion, semantic caching, and context reordering for RAG.
      7
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to run hybrid retrieval, reciprocal rank fusion, knowledge graph expansion, semantic caching, and context reordering so critical evidence is placed at prompt boundaries to reduce lost-in-the-middle degradation.
      7
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      MCP server that enables persistent, hybrid, local memory for LLM agents, with vector + BM25 search, knowledge graph, and policy-driven retention, providing token-budgeted context injection for AI assistants.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to maintain multi-tier memory across working scratchpad, dialogue buffer, and episodic stores with recency decay. Supports hybrid BM25/vector retrieval, rank fusion, graph expansion, and context reordering for optimized MCP-based memory and RAG workflows.
      7
      MIT