Vee3

rotten-tomatoes.movie_details

Look up a movie on Rotten Tomatoes by slug (for example shawshank-redemption).

Returns title, year, rating, runtime, genres, description, poster and hero images, Tomatometer and Popcornmeter scores, cast highlights, and where to watch links.

Cost = 5 tokens.

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": {
      "movie_slug": "<movie_slug>"
    },
    "name": "rotten-tomatoes.movie_details"
  }
}

Input Schema

Name	Required	Description	Default
`movie_slug`	Yes	Movie slug (for example shawshank-redemption).

Output Schema

Name	Required	Description
`cast`	No	Featured cast with name, slug, and imageUrl.
`slug`	No	Movie slug.
`year`	No	Release year.
`title`	No	Movie title.
`tomatometer`	No	Critic Tomatometer score and metadata.
`popcornmeter`	No	Audience Popcornmeter score and metadata.

Schema Changelog

Changes observed during successful MCP inspections.

First observedJun 18, 2026

TDQS

A4.3/5.0

Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the operation is a read-only lookup ('Look up'), lists the exact output fields, and even notes the token cost. It does not mention error handling or rate limits, but for a simple read tool this is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: first states the purpose with an example, second lists the return fields and cost. Every sentence adds value, front-loaded with the core action, and there is no redundant or filler content.

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?

For a simple one-parameter read tool, the description is complete. It specifies the input format (slug), provides an example, lists all major output categories, and states the cost. An output schema exists, so detailed return values are not required, and the description exceeds that requirement.

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% because the movie_slug property is fully described with the same example as in the top-level description. The description adds no new meaning beyond the schema, so the baseline score of 3 is appropriate.

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 uses a specific verb ('Look up a movie') and identifies the resource (Rotten Tomatoes movie by slug) with a clear example. It distinguishes itself from sibling tools like tv_show_details and celebrity_details by explicitly stating 'movie'.

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?

The description clearly states when to use the tool (when you need movie details by slug) and provides context for how to specify the movie. It does not explicitly name alternatives or exclusion criteria, but the sibling tool names (e.g., tv_show_details) imply the boundary.

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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