book-library-mcp

get_book_infographic_text

Retrieve infographic text for a book by slug, choosing between ChatGPT or Gemini variants with automatic fallback.

Instructions

Return the contents of <slug>_book_infographic_<source>.txt.

source is one of chatgpt (default) or gemini. Falls back to whichever variant exists if the requested one isn't present.

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": {
      "slug": "<slug>"
    },
    "name": "get_book_infographic_text"
  }
}

Input Schema

Name	Required	Description	Default
`slug`	Yes
`source`	No		chatgpt

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 5, 2026

TDQS

A4.1/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It usefully reveals fallback behavior between chatgpt and gemini variants, but it does not state what happens if neither variant exists, nor any other runtime behavior or limitations.

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 compact, front-loaded with the primary function, and contains no filler. Every sentence adds necessary detail about file naming, valid source values, or fallback behavior.

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

Completeness5/5

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

For a simple two-parameter getter, the description covers the essential behavior: what is returned, how the filename is composed, source options, and fallback logic. The presence of an output schema means return-value details do not need to be in the description.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must explain parameters. It does so by placing them in the filename template and explaining that `source` is either `chatgpt` or `gemini` with a default. This adds meaningful semantics beyond the bare schema property names.

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 tool returns the contents of a specific file pattern (`<slug>_book_infographic_<source>.txt`), making the resource and action unambiguous. It also differentiates from sibling tools by focusing on infographic text rather than metadata, summaries, action items, or notes.

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 gives solid guidance for the `source` parameter, including valid values and fallback behavior. However, it does not explicitly explain when to choose this tool over siblings like get_book_metadata or get_chapter_summary, so tool-selection guidance is only implied.

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

Deploy Server