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drakonkat

wizzy-mcp-tmdb

by drakonkat
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

trending_people

Discover currently popular actors, directors, and other entertainment professionals by retrieving trending people data for daily or weekly analysis.

Instructions

Retrieves trending people (actors, directors, etc.). Input: time_window (required: day|week), page (optional), language (optional ISO 639-1). Output: JSON with paginated trending results. Purpose: Discover currently popular people for trend analysis by AI agents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageNo
pageNo
time_windowYes

Implementation Reference

  • mcp-tmdb-server.js:683-686 (handler)
    The asynchronous handler function that implements the core logic of the 'trending_people' tool. It fetches trending persons data from the TMDB API endpoint `/trending/person/${time_window}` using the shared `tmdbFetch` utility, passing optional page and language parameters, and returns the JSON-stringified data wrapped in MCP content format.
    handler: async ({time_window, page, language}) => {
    const data = await tmdbFetch(`/trending/person/${time_window}`, {page, language});
    return {content: [{type: 'text', text: JSON.stringify(data, null, 2)}]};
}
  • mcp-tmdb-server.js:673-682 (schema)
    The JSON schema for input validation of the 'trending_people' tool. Defines required 'time_window' (enum: day/week), optional 'page' (number >=1), and 'language' (string). Enforces no additional properties.
    inputSchema: {
    type: "object",
    properties: {
        time_window: {type: "string", enum: ["day", "week"]},
        page: {type: "number", minimum: 1},
        language: {type: "string"}
    },
    required: ["time_window"],
    additionalProperties: false
},
  • mcp-tmdb-server.js:670-687 (registration)
    The complete tool registration object for 'trending_people' within the 'tools' array. Includes name, description, inputSchema, and inline handler. This object is used by the MCP server's ListTools and CallTool handlers to register and invoke the tool.
    {
    name: "trending_people",
    description: "Retrieves trending people (actors, directors, etc.). Input: time_window (required: day|week), page (optional), language (optional ISO 639-1). Output: JSON with paginated trending results. Purpose: Discover currently popular people for trend analysis by AI agents.",
    inputSchema: {
        type: "object",
        properties: {
            time_window: {type: "string", enum: ["day", "week"]},
            page: {type: "number", minimum: 1},
            language: {type: "string"}
        },
        required: ["time_window"],
        additionalProperties: false
    },
    handler: async ({time_window, page, language}) => {
        const data = await tmdbFetch(`/trending/person/${time_window}`, {page, language});
        return {content: [{type: 'text', text: JSON.stringify(data, null, 2)}]};
    }
},

Tool Definition Quality

A3.6/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that the output is 'JSON with paginated trending results', which adds useful behavioral context beyond the input schema. However, it doesn't cover aspects like rate limits, authentication needs, error handling, or whether this is a read-only operation (though 'retrieves' implies it). Some key behavioral traits are missing.

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 front-loaded with the core functionality, followed by input/output details and purpose. Every sentence adds value: the first states what it does, the second explains parameters, the third describes output, and the fourth clarifies the use case. No wasted words, and it's appropriately sized for a tool with 3 parameters.

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

Completeness3/5

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

Given 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is moderately complete. It covers input semantics and output format but lacks details on error cases, rate limits, or example responses. For a tool with no structured support, it should do more to compensate, especially regarding behavioral aspects.

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?

The schema description coverage is 0%, so the description must compensate. It adds meaning by explaining that time_window is for 'day|week' (matching the enum), page is for pagination, and language uses ISO 639-1 format. This clarifies parameter purposes beyond the bare schema, though it doesn't detail default values or constraints like page minimum. Good compensation for low schema coverage.

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 verb 'retrieves' and resource 'trending people (actors, directors, etc.)', making the purpose specific. It distinguishes from siblings like trending_movies and trending_tv by focusing on people, though it doesn't explicitly contrast with trending_all which might include people. The purpose statement at the end reinforces the use case for AI agents.

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 for 'trend analysis' and 'discover currently popular people', providing some context. However, it lacks explicit guidance on when to use this tool versus alternatives like trending_all, person_details, or search_tmdb_person, and doesn't mention prerequisites or exclusions. The guidance is present but not comprehensive.

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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