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Get trending books

get_trending_books
Read-onlyIdempotent

List the books trending on ShelfClub: the books its readers have been shelving come first, then the catalog's most widely read books. Returns up to 10 books, each with its ShelfClub id, authors, description, reader rating, series, shelfclub.app link, and mood, vibe and pace tags (machine-generated, or voted for by at least three readers of the book).

Input Schema

NameRequiredDescriptionDefault
limitNoHow many books to return.

Output Schema

NameRequiredDescriptionDefault
booksNo
statusYes"try_again_later": the service was busy and looked nothing up, so the other fields are absent.
tagProvenanceNoWhere the moods, vibes, pace and genres come from.
retryAfterSecondsNoWith "try_again_later", when known: how long to wait.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / properties / books / items / properties / id / description
      Previous value: -"The Shelfclub id of the book."New value: +"The ShelfClub id of the book."
  2. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the bar is lower; the description still adds real context — the ranking semantics, the 10-item ceiling, and the provenance of vibe/mood/pace tags (machine-generated or reader-voted with a 3-vote threshold). It does not mention pagination or whether the ranking is cached/fresh, but the added disclosure is well beyond the annotations.

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?

Two sentences, front-loaded with the core behavior and the ordering rule before the return payload. The parenthetical about tag provenance is dense but each clause carries information; nothing is padding.

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 one-parameter read tool with an output schema and full annotation coverage, this is nearly complete: it explains ordering, cap, returned fields and tag provenance. Only ranking freshness/recency window 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 the single limit parameter is already documented with default 5 and maximum 10. The description only reinforces the cap ('up to 10 books') and adds no interpretation of what limit trades off against within the two-tier ordering, so the schema does the heavy lifting.

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 gives a specific verb and resource ('List the books trending on ShelfClub') and, crucially, defines the ranking rule (recently shelved first, then most-read), which is the entire distinguishing feature versus siblings like search_books or get_similar_books. An agent can tell what this returns without opening the 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?

Usage is implied by the 'trending' framing but there is no explicit when-to-use/when-not guidance and no sibling is named as an alternative for related needs (e.g., mood-based discovery or title search). The agent must infer routing from the word 'trending'.

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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