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Get TMDB Person Credits

tmdb_get_person_credits

Retrieve a person's movie and TV credits, filtered by cast or crew role, with options for media type, sort order, and result limit.

Instructions

Gets a bounded movie, TV, or combined filmography filtered by cast or crew roles.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
sortByNopopularity
languageNo
personIdYes
mediaTypeNocombined
creditTypeNoall
Behavior2/5

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

There are no annotations provided, so the description bears full responsibility for disclosing behavioral traits. It mentions 'bounded' (implying a limit) and 'filtered' (implying creditType/mediaType), but these directly restate schema parameters. It does not disclose output structure, default sorting, language behavior, or what happens with invalid inputs. The agent gains little beyond the schema.

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 a single concise sentence that front-loads the action ('Gets') and packs relevant filters into a compact phrase. There is no redundant or filler content, making it extremely efficient.

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

Completeness2/5

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

With six parameters, no output schema, and no annotations, a robust description is essential. However, this description only covers two parameters conceptually, omits return value structure, default sorting/pagination behavior, and any usage prerequisites. It is too sparse for an agent to fully understand the tool's capabilities and limitations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema_description_coverage is 0%, so the description must compensate. It alludes to mediaType ('movie, TV, or combined') and creditType ('cast or crew'), but provides no explanation for personId, limit, sortBy, or language. The schema has enums and defaults, but the description does not clarify their semantics or interaction (e.g., how sortBy works, default behavior).

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 clearly states the function: 'Gets a bounded movie, TV, or combined filmography filtered by cast or crew roles.' It uses a specific verb ('gets') and specifies the resource (person credits) and key filters (media type and credit type). This distinguishes it from sibling tools like tmdb_get_person (person details) and tmdb_get_credits (credits for a specific title).

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 when to use the tool (to retrieve a person's filmography) but provides no explicit exclusions or alternatives. For instance, it does not contrast with tmdb_search_people or tmdb_get_credits, leaving the agent to infer the correct context from the name and sibling list. No 'when-not-to-use' guidance is given.

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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