Retrieve all public Rotten Tomatoes editorial taxonomies and the content types each filters, so you can use accepted terms with the term discovery endpoint.
Rotten Tomatoes editorial taxonomy discovery. Returns the complete set of public editorial term vocabularies accepted by the term discovery endpoint, with the content types each taxonomy filters.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.17.6Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. 'Returns the complete set' implies a read-only, unpaginated listing, which is useful, but it discloses no auth requirements, rate limits, or whether results are cached/static. It gives a basic behavioral picture without contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences with the resource identified first and the return content second. No filler, no restatement of the name, everything front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description must describe the return shape, and it does: a complete set of term vocabularies with associated content types. That is sufficient for a zero-parameter read tool, though it stops short of explaining the fields within each taxonomy.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so per the rubric the baseline is 4. No parameter ambiguity exists for the description to resolve.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific resource (Rotten Tomatoes editorial taxonomies) and what a call yields: the public editorial term vocabularies plus the content types each filters. However, it does not differentiate this from close siblings such as rottentomatoes_editorial_terms and rottentomatoes_editorial_types, so an agent may struggle to pick among them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit when-to-use or when-not-to-use guidance, and no sibling is named as an alternative. The phrase 'accepted by the term discovery endpoint' hints at a use case but never states the condition that selects this tool over the other editorial_* tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.