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    • F
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      maintenance
      Enables analysis of documents far larger than an LLM's context window by executing constrained symbolic Nucleus commands against them server-side, with in-memory handle storage that returns compact stubs instead of full result sets. Also provides a server-side memory pad so agents can stash context and retrieve it later, cutting token usage dramatically.
      2 npm
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    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables analysis of documents far larger than an LLM's context window by executing symbolically-constrained Nucleus commands server-side instead of arbitrary generated code, without vector databases or chunking. It also lets agents stash large text results as compact in-memory handles and memos, cutting token usage by 90%+ while keeping full data retrievable on demand.
      2 npm
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    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables analysis of documents far larger than an LLM's context window by letting the model emit validated S-expression commands that execute server-side over full-text-indexed handles. Supports recursive sub-queries, multi-document context selectors, and a server-side memory pad that keeps bulky text out of the conversation.
      2 npm
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    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables token-efficient analysis of very large documents by letting an LLM issue symbolic Nucleus commands to a Lattice engine and keeping large results in server-side handles, avoiding vector databases or chunking. Supports recursive queries, multi-context loading, and memo stashing to work beyond the model's context window.
      2 npm
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    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables token-efficient analysis of documents far larger than an LLM context window by executing constrained symbolic Nucleus commands through a Lattice logic engine and returning compact handles or final results. Supports recursive sub-queries, multi-document loading, and server-side memo storage to reduce context roundtripping.
      2 npm
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    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables MCP clients to analyze documents far larger than their context window by having the model emit validated symbolic S-expression commands that are parsed and executed server-side against the loaded content. In-memory handles, recursive sub-queries, and server-side memos keep token usage low while preserving full data for on-demand expansion.
      2 npm
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