Movie Recommendations

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Get movie recommendations by ID' implies a read-only operation but doesn't specify critical traits like whether it requires authentication, rate limits, pagination behavior (beyond the 'page' parameter in schema), or what the output format looks like (e.g., list of movies with details). For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, straightforward sentence ('Get movie recommendations by ID'), making it appropriately concise and front-loaded. There's no wasted verbiage, and it directly states the core function. However, it could be slightly improved by adding a bit more context without sacrificing brevity, but it's efficient as is.

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 complexity of a recommendation tool with 2 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'recommendations' entail (e.g., similar movies, user-based suggestions), how results are structured, or any behavioral aspects like error handling. For a tool that likely returns a list of movies, more context is needed to guide effective use, especially with many sibling tools that might serve similar purposes.

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?

The description adds minimal meaning beyond the input schema, which has 100% coverage with clear descriptions for 'movie_id' (TMDB movie ID) and 'page' (page number 1-1000). It implies that 'movie_id' is used to fetch recommendations, but doesn't elaborate on how recommendations are generated or the relationship between parameters. With high schema coverage, the baseline is 3, as the description doesn't compensate with additional insights but doesn't detract either.

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 'Get movie recommendations by ID' restates the tool name 'movie_recommendations' with minimal elaboration, making it tautological. It specifies the action ('Get') and resource ('movie recommendations') but lacks detail on what 'recommendations' entails (e.g., similar movies, personalized suggestions). Compared to siblings like 'movie_similar' or 'movie_popular', it doesn't clearly differentiate its purpose beyond the basic name.

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?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'movie_similar' and 'movie_popular' that might overlap in functionality, it doesn't specify scenarios (e.g., use for recommendations based on a specific movie ID, not for trending or genre-based lists). There's no mention of prerequisites, exclusions, or comparative contexts, leaving usage ambiguous.

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