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datasets_goodreads_authors_facets

Facet Goodreads authors data by genre or run ID and filter by query, name, genre, rating, or ratings count to return top 50 value counts.

Instructions

Facet Goodreads authors dataset. Returns value counts over the Goodreads authors dataset for the required facet, either genres or run_id. Filters q, name, genre, run_id, min_rating (0 to 5) and min_ratings_count narrow the result, which lists the top 50 values with their counts.

Input Schema

NameRequiredDescriptionDefault
qNoFull-text query over name, about and genres, max 256 characters
nameNoExact author name filter, max 128 characters
facetYesFacet enum: genres, run_id
genreNoExact genre filter, max 128 characters
run_idNoExact crawl run-id filter, max 128 characters
min_ratingNoMinimum average rating, 0 through 5
min_ratings_countNoMinimum number of ratings

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / facet / enum
      Added value: +[
+  "genres",
+  "run_id"
+]
  2. Added

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses the return shape (top 50 values with their counts) and that facet is required, which is real behavioral context. However it says nothing about read-only nature, pagination limits beyond the top-50 cap, or any auth/rate constraints.

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 what the tool does and followed by the result shape. The second sentence is long but carries no filler; each clause (facet values, filter list, top-50 output) earns its place.

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 facet/aggregation tool with full schema coverage and no output schema, the description supplies the key missing piece — that the result is a ranked list of top-50 values with counts. It is close to complete, lacking only guidance on default behavior and interaction between the filters.

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%, so the schema already documents all 7 parameters including the facet enum and the 0-5 range. The description largely restates these ('either genres or run_id', 'min_rating (0 to 5)') rather than adding syntax or interaction detail, so baseline 3 applies.

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 states a specific verb and resource: 'Facet Goodreads authors dataset' and 'Returns value counts over the Goodreads authors dataset.' The value-counts framing distinguishes it conceptually from search/item siblings, though it never names them explicitly, so an agent must infer the difference.

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 — the tool aggregates value counts for a facet — but there is no explicit when-to-use guidance, no statement of when to prefer it over datasets_goodreads_authors_search or _item, and no exclusions. Adequate but leaves the routing decision to inference.

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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