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Crawlora MCP

rottentomatoes_publication_reviews

Read-only

Fetch the critic reviews one Rotten Tomatoes publication published, newest first, with stable review ids, ISO created_at and updated_at times, critic identity, publication name, quote, score sentiment and the original article URL, limit per page (max 20) and pageable with the returned end_cursor (keep limit the same while paging). Pass the encrypted publication id (encrypted_publication_id on any review row); a numeric publication id is rejected. Use rottentomatoes_publication for the publication profile.

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": "rottentomatoes_publication_reviews"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesPublication id: encrypted_publication_id
afterNoPagination cursor: pass data.page_info.end_cursor from the previous response
limitNoReviews per page, default 10, max 20. Keep it the same on every page of one walk.

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

A4.4/5.0
Behavior4/5

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

Annotations already cover readOnly and openWorld, so the bar is lower. The description adds genuine operational context: newest-first ordering, stable ids, ISO timestamps, numeric ids rejected, and the pagination constraint to keep limit constant.

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?

Front-loaded with purpose and packed with useful detail, but it is one dense run-on sentence with heavy comma-separated listing, which slightly hurts readability.

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

Completeness5/5

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

With an output schema present, annotations covering safety, and full param coverage, the description supplies all the operational detail an agent needs: id format, pagination mechanics, and field contents.

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 100%, so baseline is 3, but the description adds value beyond the schema: the encrypted_publication_id requirement, the numeric-id rejection, and the 'keep limit same while paging' rule for after/limit.

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 (Fetch) and resource (critic reviews one publication published) with clear scope (newest first, with stable ids and metadata). It explicitly routes to rottentomatoes_publication for the profile, distinguishing it from the sibling.

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?

Names the alternative (rottentomatoes_publication) for profile data and explains the paging workflow. It doesn't disambiguate this from other review tools like critic_reviews or movie_reviews, but the when/when-not and paging context are clear.

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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