Get movie recommendations

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds behavioral context about the recommendation basis and comparison to get_similar, without contradicting the annotations. It does not discuss rate limits or pagination details, but that is acceptable given the annotations.

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

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

The description is three sentences, each serving a distinct purpose: explaining the tool, giving usage preference, and providing input source. It is front-loaded and contains no unnecessary words.

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

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

Given the presence of an output schema, the tool definition is complete. It covers purpose, usage guidelines, input source, and differentiation from siblings. No additional details are needed for effective invocation.

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

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

Schema coverage is 100%, so the baseline is 3. The description implicitly references the required parameter (movie id) but does not add new meaning beyond the schema. The page parameter is not mentioned, but the schema describes it adequately.

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

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

The description clearly states the tool retrieves TMDB recommendations for a given movie ID, explains the basis (co-viewing/personalization data), and explicitly distinguishes it from the sibling tool get_similar. It also directs users to obtain the ID from search_movies.

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

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

Explicitly advises to prefer this over get_similar as the default choice and explains the difference in recommendation logic. Also provides guidance on getting the movie ID from search_movies.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.