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docshelf_search

Read-onlyIdempotent

Retrieve matching Markdown sections from a shelf using plain-text queries, returning ranked snippets and direct URLs for fetching content.

Instructions

Plain-text search across every Markdown file in the shelf.

Tokens are space-split; each must appear (case-insensitive) for a hit to count. If no file contains all tokens, the search falls back to any-token matching and the response reports match_mode: "any". Heading/title matches are ranked above body-only matches, and for a split document the section files are returned rather than the whole-file parent. Results include the relative path, a word-boundary-trimmed snippet, and — if a remote is configured — the fetch URL so the model can pull the matching file directly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.4.1
  2. Removedv0.3.0
  3. First observedv0.2.0

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnly, idempotent, and non-destructive annotations, the description discloses case-insensitive token matching, all-token vs. any-token fallback with match_mode, heading-priority ranking, section-file behavior for split documents, and the remote fetch URL. These are substantive behavioral details that materially affect how an agent interprets results.

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?

The description is front-loaded with the core purpose in the first sentence, and every subsequent sentence contributes operational detail. It is thorough without being bloated or repetitive.

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

Completeness4/5

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

For a read-only search tool with an output schema and strong annotations, the description covers scope, matching, fallback, ranking, split-document behavior, and result fields. The sole notable gap is the lack of explanation for the optional shelf_path parameter, which prevents a perfect score.

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?

The description does not explain the shelf_path parameter at all and does not mention max_results. Since schema description coverage is reported as 0%, the description was expected to compensate for parameter-level meaning, but it only covers query semantics and result shape, leaving the optional parameters ambiguous.

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 opens with a specific verb and resource: 'Plain-text search across every Markdown file in the shelf.' It clearly distinguishes this tool from sibling read, list, and write tools, and the detailed matching semantics make its purpose unmistakable.

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 makes the intended use clear: keyword search over the whole shelf, with explicit fallback and ranking behavior. It does not explicitly name alternatives or state when to prefer docshelf_read_document, but the search-versus-read distinction is strongly implied.

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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