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Li-ship-dot

fast-jev-compaction

by Li-ship-dot

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    • A
      license
      Not graded
      quality
      B
      maintenance
      Provides deterministic context compaction and safety gating for AI agents, preserving original messages verbatim while dropping irrelevant ones and flagging destructive commands.
      2
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to deterministically shrink multi-turn conversation history and prompts by stripping verbose boilerplate and filler tokens while preserving critical tool parameters and named entities. This lets users cut inference costs by roughly 40-60% without losing essential context, running either as a native MCP server over JSON-RPC stdio or as an importable zero-dependency Python module.
      7
      MIT
    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables MCP-compatible clients and autonomous agents to dynamically compress long-horizon context by pruning verbose tool outputs, HTML boilerplate, and semantic redundancy by 40-70%. It reduces token burn and latency through deterministic, zero-dependency processing.
      7
      -
    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to analyze their session context usage and surgically remove heavy or unnecessary events from their history, preserving coherent transcripts and freeing token budget without restarting.
      -
    • A
      license
      Not graded
      quality
      A
      maintenance
      Scores AI agent context entries for relevance using Jev and prunes or summarizes those that are no longer useful, helping MCP hosts reduce token usage and context bloat.
      MIT

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