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Get Trending Movies & TV

tmdb.movies.trending
Read-onlyIdempotent

Retrieve trending movies, TV shows, or people from The Movie Database (TMDB) for daily or weekly time periods.

Instructions

Get trending movies, TV shows, or people — daily or weekly (TMDB)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoContent type: "movie", "tv", "person", or "all" (default "movie")
windowNoTime window: "day" or "week" (default "week")
languageNoISO 639-1 language code (e.g. "en-US"). Default: en-US
pageNoPage number (1-500, default 1)
Behavior3/5

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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds valuable context beyond annotations: it identifies TMDB as the external data source and clarifies the scope includes three distinct entity types (movies, TV shows, people).

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?

Exemplary brevity: a single sentence packs the resource type, content variants, time granularity, and data source with zero redundancy. Every word earns its place and critical information is front-loaded.

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

Completeness4/5

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

Given the simple parameter structure (4 optional primitives, 100% schema coverage) and rich annotations, the description provides sufficient context. It appropriately omits return value details (no output schema exists) while conveying the essential API behavior.

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?

While the schema has 100% description coverage, the description adds semantic grounding by enumerating the concrete options ('movies, TV shows, or people' for type; 'daily or weekly' for window) that map to the schema enums, reinforcing the parameter purposes beyond technical specifications.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves 'trending' content (movies, TV, people) with time granularity (daily/weekly) and identifies the TMDB source. The 'trending' keyword effectively distinguishes this from sibling tools like 'search' or 'discover', though it doesn't explicitly contrast with them.

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 usage by specifying the time windows ('daily or weekly') and content types available, guiding parameter selection. However, it lacks explicit guidance on when to choose this over 'tmdb.movies.discover' or 'tmdb.movies.search' for finding popular content.

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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