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genpark-agentic-prompt-compression-token-sieve-skill

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    • 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 AI agents and MCP-compliant clients to dynamically shrink long-horizon context windows, pruning verbose tool outputs, HTML boilerplate, and semantic redundancy by roughly 40-70% without frontier LLM round-trips. Runs deterministically as a zero-dependency Python stdio server, accepting a payload plus optional compression and risk-bound options.
      7
      -
    • A
      license
      A
      quality
      A
      maintenance
      Provides reversible context compression for AI agents, reducing token usage while preserving the ability to retrieve original content, and serves as an MCP server for integration with tools like GitHub Copilot and Claude Code.
      3
      1
      Apache 2.0
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables MCP-compatible developer environments to shrink verbose tool outputs—test logs, git diffs, directory listings, and file dumps—before they reach the context window, preserving compiler errors, failure signatures, and decisive anchors. It runs either as direct callable tools or as a transparent proxy wrapping other MCP servers such as filesystem, git, or terminal providers.
      1
      MIT
    • F
      license
      Not graded
      quality
      B
      maintenance
      Enables autonomous agents to tokenize session context windows and compact dialogue history deterministically, exposing this capability to MCP-compatible clients like Claude Desktop and Cursor. Helps manage context length and reduce token usage in agent sessions through a zero-dependency Python MCP server.
      7
      -

    Maintenance

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