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grimoire-beholder-mcp

grimoire-beholder-mcp

by Palanx
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_section

Retrieve the full text and summary of a specific book section using its book ID, chapter index, and section index.

Instructions

Fetch one section's full text and summary.

The parent of a search_book hit, or a section located via get_book_outline's chapter_index/section_index map.

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": {
      "book_id": "<book_id>",
      "chapter_index": "<chapter_index>",
      "section_index": "<section_index>"
    },
    "name": "get_section"
  }
}

Input Schema

NameRequiredDescriptionDefault
book_idYes
chapter_indexYes
section_indexYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses that the tool returns 'full text and summary', implying a read-only operation. However, it doesn't specify behavior for invalid indices or any error conditions. For a simple fetch, this is adequate but not comprehensive.

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 two sentences long, front-loaded with the main action. Every sentence adds value: the first defines the function, the second explains how to locate the section. There is no unnecessary text.

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 tool is simple (fetch with three integer parameters), but there is no output schema. The description mentions 'full text and summary' but does not elaborate on the response structure or what 'summary' entails. It is complete enough for basic use but leaves some ambiguity.

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 input schema has 0% description coverage, meaning no parameter descriptions. The parameter names (book_id, chapter_index, section_index) are self-explanatory, but the description adds minimal meaning beyond the schema. It only indirectly references chapter_index and section_index. With zero coverage, the description should compensate more.

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

Purpose4/5

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

The description clearly states it fetches one section's full text and summary. It mentions how sections are located via search_book or get_book_outline, but does not explicitly differentiate from sibling tools like get_book_outline, which returns the outline structure. The purpose is clear but not fully differentiated.

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

Usage Guidelines3/5

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

The description indicates when to use this tool: after obtaining indices from search_book or get_book_outline. It does not explicitly state when not to use it or provide alternatives. The usage context is clear but lacks exclusions.

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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