Fetch a Letterboxd film's star-rating distribution, with counts and percentages for each half-star bucket from 0.5 to 5.0. Provide a slug to see how viewers rated the film.
Get a Letterboxd film's rating distribution. Returns a film's full star-rating distribution (0.5 to 5.0 in half-star buckets) with counts and percentages.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Letterboxd film slug |
Changes observed during successful MCP inspections.
v1.5.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does disclose the shape of the result (0.5–5.0 half-star buckets with counts and percentages), which is genuinely useful behavioral context absent an output schema, but it says nothing about access requirements, rate limits, or failure modes for an invalid slug.
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 purpose front-loaded and the return shape immediately after. No filler, no repetition of the tool name, every clause carries information.
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?
For a simple single-parameter read tool with a fully documented schema, the description covers what the tool returns even though no output schema exists. The only gap is how it relates to the other letterboxd_film_* tools, which an agent would need to disambiguate on its own.
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?
There is a single parameter with 100% schema description coverage ('Letterboxd film slug'), so the schema already documents it. The description adds no slug format or sourcing guidance, leaving this at the baseline for fully-covered schemas.
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 verb and resource: 'Get a Letterboxd film's rating distribution,' and the second sentence narrows the resource to half-star buckets with counts and percentages. It does not, however, distinguish this from the sibling letterboxd_film, which plausibly also surfaces rating data, 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the name and description — call it when you need the rating breakdown for a given film slug — but there is no explicit when-to-use, no when-not-to-use, and no pointer to letterboxd_film or letterboxd_film_reviews as alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.