episode_recommender

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

No annotations are provided, so the description carries full responsibility. The verb 'Get' implies a safe, read-only operation, and the description adds the behavioral context of being based on user preference. However, it does not mention any side effects, rate limits, or behavior on unknown episodes, which would enhance transparency. No contradictions with annotations since none exist.

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, well-structured sentence that is front-loaded with the primary action ('Get episode recommendations') and contains zero redundancy. It efficiently conveys the essential information without wasting 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?

For a simple tool with only two parameters and no output schema, the description is largely sufficient. It explains the core function and based on what input. However, it does not specify the return format (e.g., a list of episode titles) or any edge-case behavior, which would be useful given there is no output schema. Still, the tool's simplicity means this is not a critical gap.

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 input schema already documents both parameters with descriptions (100% coverage): 'episode' is 'Episode title you liked' and 'count' is 'Number of recommendations (default: 5)'. The tool description adds minimal extra semantics beyond the schema, only reinforcing the 'enjoyed' aspect. Thus, a baseline score of 3 is appropriate.

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 uses a specific verb ('Get') and resource ('episode recommendations') with a clear basis: 'based on a Star Trek episode you enjoyed'. It clearly distinguishes from sibling tools like 'get_episode' (which fetches a specific episode's details) and 'list_episodes' (which lists all episodes), making the tool's purpose unambiguous.

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 implies the primary use case: when you have a Star Trek episode you enjoyed and want recommendations. However, it provides no explicit guidance on when to use this tool versus alternatives, nor does it mention any exclusions (e.g., 'for direct episode info, use get_episode'). The context is clear but not explicit about decision boundaries.

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