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datasets_apple_books_item

Read-only

Retrieve one named public Apple Books dataset record by kind and numeric ID. Kind: book, audiobook, author, series, or audiobook_series. Unavailable placeholders and internal crawl errors are not exposed. Use datasets_apple_books_search to discover records.

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": {
      "kind": "<kind>",
      "id": "<id>"
    },
    "name": "datasets_apple_books_item"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesNumeric Apple Books resource ID.
kindYesApple Books record kind: book, audiobook, author, series, or audiobook_series.

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the read-only and open-world profile, so the bar is lower, yet the description adds real context: only public records are served, and unavailable placeholders plus internal crawl errors are deliberately not surfaced. That is meaningful data-quality information an agent needs to interpret gaps or failures; it does not, however, say what a lookup miss returns.

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 short sentences, front-loaded with the core action, and each carries information. Minor redundancy in restating the kind list already present in the schema keeps it just under top marks.

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 only two required parameters, both documented, an output schema covering return values, and annotations covering safety, the description supplies what remains: the valid kind vocabulary, the public-only scope, and the discovery sibling. Only the not-found/miss behavior is left unstated.

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

Parameters3/5

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

Schema coverage is 100% and both parameters carry descriptions, so the baseline is 3. The description's kind enumeration and 'numeric ID' phrasing duplicate what the schema already states rather than adding format or edge-case guidance.

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 precise verb and resource (retrieve one Apple Books dataset record), constrained by two keys (kind, numeric ID), and names the sibling used for discovery. An agent can distinguish it from datasets_apple_books_search and datasets_apple_books_facets without opening any schema.

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?

'Use datasets_apple_books_search to discover records' explicitly routes the agent to the alternative when it lacks a kind/ID, implying this tool is the lookup step after discovery. There is no exclusion for other cursor cases (e.g. live apple_books_* endpoints), but the main fork is resolved.

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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