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Leer los subrayados de un libro

read_book
Read-only

Devuelve los subrayados de un libro importado, literales y con su página y posición, y las notas que el usuario escribió en el Kindle, por páginas de 15.000 caracteres. Los que Amazon cortó al exportar llevan «Incompleto»: no los presentes como la frase entera. Si next no es null, vuelve a llamar con from = next.

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": {
      "id": "<id>"
    },
    "name": "read_book"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesEl id que dio list_books.
fromNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already establish that this is a safe read operation, so the description only needs to add context — and it does: page size of 15,000 characters, the presence of a 'next' cursor in the response, and the fact that Amazon-truncated highlights are tagged 'Incompleto'. It goes slightly beyond pure data description with a presentation instruction, but that is useful behavioral context rather than a contradiction.

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

Conciseness4/5

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

Three dense sentences with the return content front-loaded, then the truncation caveat, then the pagination rule. No filler, though the truncation warning is phrased as a presentational instruction rather than tool behavior and could be trimmed.

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?

With no output schema, the description must explain what comes back, and it does: highlights with page/position, notes, a 'next' cursor, and the 15,000-character page size. For a simple two-parameter read tool this is nearly sufficient, with only the starting state when 'from' is omitted left unstated.

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 coverage is only 50%: 'id' is documented in the schema, but 'from' has no schema description. The description compensates by explaining that 'from' takes the 'next' value from a prior response, which is exactly the missing semantic. It does not, however, state that 'from' is an offset or that omitting it starts at the beginning.

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?

States a specific verb and resource: returns highlights (verbatim, with page and position) plus Kindle notes for an imported book. This clearly separates it from siblings like read_note, read_chat or read_pinterest, so an agent can pick it without opening a schema.

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?

It gives a concrete follow-up rule for pagination (if next is not null, call again with from = next), which is real usage guidance. However, it never says when to choose this over list_books (to discover ids) or import_highlights, nor states any exclusion or prerequisite.

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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