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rottentomatoes_editorial_search

Search Rotten Tomatoes editorial articles and guides by query, with page and limit controls, returning content subtypes and total pages.

Instructions

Rotten Tomatoes editorial search. Searches public Rotten Tomatoes editorial content, including articles and guides. Results come from its anonymous WordPress REST search endpoint and include content subtype plus total-page metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoOne-based result page from 1 to 10000; default 1
limitNoRows per page, default 10, range 1 to 100
queryYesEditorial search text; maximum 200 bytes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral transparency burden. It does disclose useful context: results come from an anonymous WordPress REST endpoint and include content subtype plus total-page metadata, implying read-only, no-auth access. However, it doesn't mention rate limits, error behavior, or pagination semantics beyond what the schema provides. This is adequate but not thorough.

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?

The description is three sentences with the purpose front-loaded. It's tight and readable, though the opening phrase 'Rotten Tomatoes editorial search' slightly repeats the tool name, and the WordPress endpoint detail is arguably implementation trivia. Overall it earns its place without bloat.

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

Completeness3/5

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

For a simple search tool with no output schema, the description would be more complete if it outlined the response structure. It hints at 'content subtype plus total-page metadata' but doesn't name other fields, sorting, or pagination defaults beyond the schema. It's minimally adequate but not fully complete for an agent that needs to interpret results.

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 description coverage is 100%, so the baseline applies. The description adds no new parameter meaning beyond what the schema already documents for query, page, and limit. It doesn't explain the interaction between page and limit or what 'total-page metadata' means for pagination. No extra value over the schema.

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 clearly states a specific verb and resource: 'Searches public Rotten Tomatoes editorial content, including articles and guides.' The scope is narrow enough to distinguish it from movie/person/series lookups, though it doesn't explicitly name sibling tools such as rottentomatoes_search. This is a strong, specific purpose statement.

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 implies usage for editorial articles and guides but never explicitly states when to prefer this tool over rottentomatoes_search or other RT endpoints, nor does it give any exclusions. An agent must infer the distinction from the word 'editorial.' This is implied guidance, not explicit, and could be improved by naming alternatives.

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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