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Library of Context

Library of Context

by hwillGIT
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

library_shelve_document

DestructiveIdempotent

Chunk and persist long text as multiple retrievable books, with optional replacement of existing chunks.

Instructions

Chunk and persist a larger local text document as multiple books. Set replace_edition to replace prior chunks from the same source.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "text": "<text>",
      "source": "<source>"
    },
    "name": "library_shelve_document"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYes
sourceYes
catalogNoJSON catalog metadata or exact-match catalog filters.
collectionNoOptional library collection/namespace; defaults to the configured collection.
importanceNo
chapter_tokensNo
overlap_tokensNo
replace_editionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare destructive and idempotent behavior. The description adds valuable context by explaining the chunking behavior and that replace_edition replaces prior chunks from the same source, which clarifies the destructive semantics beyond the annotation flags.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences front-load the core purpose and add the single most important behavioral caveat. There is no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The core chunk-and-persist flow and replacement behavior are covered, and annotations provide the safety profile. However, with 8 parameters, 25% schema description coverage, and no output schema, the description leaves important operational details—like how importance, chapter_tokens, and overlap_tokens affect output—to inference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 25%, and the description only elaborates on replace_edition. Parameters like chapter_tokens, overlap_tokens, importance, and catalog semantics remain under-specified; their names give hints, but the description does not compensate for the low schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Chunk and persist') and the resource ('a larger local text document'), with a distinctive outcome ('as multiple books'). This distinguishes it from sibling tools like library_shelve, which likely handles a single unsplit document.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context: use this for larger local text documents that need chunking, and use replace_edition to update previously persisted chunks. It does not explicitly name alternatives or give when-not-to-use guidance, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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