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drakonkat

wizzy-mcp-tmdb

tv_airing_today

Find TV shows currently airing today to get timely viewing recommendations and discover what's on television right now.

Instructions

Retrieves TV series airing today. Input: page (optional), language (optional ISO 639-1), timezone (optional). Output: JSON with paginated results. Purpose: Discover TV shows currently airing for timely recommendations by AI agents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageNo
pageNo
timezoneNo

Implementation Reference

  • The handler function fetches TV shows airing today from the TMDB API endpoint '/tv/airing_today' using the tmdbFetch helper, with optional parameters for page, language, and timezone, and returns the data as a formatted JSON text content block.
    handler: async ({page, language, timezone}) => {
        const data = await tmdbFetch('/tv/airing_today', {page, language, timezone});
        return {content: [{type: 'text', text: JSON.stringify(data, null, 2)}]};
    }
  • Input schema defining optional parameters: page (number >=1), language (string), timezone (string). No additional properties allowed.
    inputSchema: {
        type: "object",
        properties: {page: {type: "number", minimum: 1}, language: {type: "string"}, timezone: {type: "string"}},
        additionalProperties: false
    },
  • The complete tool definition object added to the 'tools' array, which is used by the MCP server's ListToolsRequestHandler to expose the tool and by CallToolRequestHandler to dispatch calls to the handler based on name.
    {
        name: "tv_airing_today",
        description: "Retrieves TV series airing today. Input: page (optional), language (optional ISO 639-1), timezone (optional). Output: JSON with paginated results. Purpose: Discover TV shows currently airing for timely recommendations by AI agents.",
        inputSchema: {
            type: "object",
            properties: {page: {type: "number", minimum: 1}, language: {type: "string"}, timezone: {type: "string"}},
            additionalProperties: false
        },
        handler: async ({page, language, timezone}) => {
            const data = await tmdbFetch('/tv/airing_today', {page, language, timezone});
            return {content: [{type: 'text', text: JSON.stringify(data, null, 2)}]};
        }
    },
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 of behavioral disclosure. It mentions the output format ('JSON with paginated results'), which adds useful context beyond the input schema. However, it lacks details on rate limits, authentication needs, or error handling, leaving gaps in behavioral transparency for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, starting with the core function and following with input/output details and purpose. Every sentence adds value, but the structure could be slightly improved by separating input and output details more clearly, though it remains efficient with minimal waste.

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 the tool's moderate complexity (3 optional parameters, no annotations, no output schema), the description is partially complete. It covers the purpose, input parameters, and output format, but lacks details on behavioral aspects like pagination handling or error cases, making it adequate but with clear gaps for a tool with no structured support.

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?

The description lists the parameters ('page (optional), language (optional ISO 639-1), timezone (optional)'), but with 0% schema description coverage, it does not add sufficient meaning beyond the schema. It specifies the language format ('ISO 639-1'), which is helpful, but fails to explain the purpose or constraints of 'page' and 'timezone', not fully compensating for the low schema coverage.

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 specific action ('Retrieves TV series airing today') and resource ('TV series'), distinguishing it from siblings like 'discover_tv' or 'trending_tv' by focusing on today's airings. It explicitly mentions the purpose ('Discover TV shows currently airing for timely recommendations by AI agents'), making the tool's function unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for usage ('Discover TV shows currently airing for timely recommendations by AI agents'), indicating when to use this tool for real-time TV discovery. However, it does not explicitly state when not to use it or name alternatives among siblings, such as 'trending_tv' for broader trends, leaving some guidance implicit.

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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