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Get Related TMDB TV Series

tmdb_get_related_tv

Retrieve TV recommendations or similar series for a given series ID. Use the kind parameter to select broader recommendations or narrower similar matches.

Instructions

Gets TV recommendations by default, or narrower similar-series matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNorecommendations
pageNo
languageNo
seriesIdYes
Behavior2/5

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

With no annotations, the description must carry the full behavioral burden. It reveals the default recommendations mode and dissimilarity to similar-series matching, but omits critical details such as authentication requirements, return format, pagination behavior, or the read-only nature of the operation.

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, front-loaded sentence with no unnecessary words. It efficiently conveys the core function while leaving room for additional useful detail without becoming verbose.

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?

For a tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks return-value expectations, dependency on seriesId, and comparative context with sibling tools. The only substantive addition is the recommendations/similar split, but significant gaps remain.

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 descriptions cover 0% of parameters, so the description must compensate. It provides minimal semantic value for the 'kind' parameter by distinguishing recommendations from similar-series matches, but fails to clarify seriesId, page, or language meaning beyond basic types and enums.

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 uses a specific verb ('Gets') and clearly identifies the resource ('TV recommendations' or 'similar-series matches'), immediately distinguishing it from sibling tmdb_get_related_movies. The phrase 'by default' and 'narrower similar-series matches' further pinpoints the tool's purpose.

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

Usage Guidelines2/5

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

There is no explicit guidance on when to use this tool versus alternatives like tmdb_get_related_movies or tmdb_search_tv. The description only hints at internal modes ('by default', 'narrower similar-series matches') but lacks when/when-not context or alternative references.

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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