op3_show_downloads

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds meaningful context beyond annotations: it excludes bots and updates only once a day, which calibrate agent expectations about data freshness and composition. Doesn't overpromise a specific response shape.

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?

Tree compact sentences with no filler: first defines the payload, second gives usage guidance, third states caveats. Front-loaded with the most important distinguishing information.

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?

The tool is simple with one required parameter, no output schema, and annotations covering safety. The description tells the agent what values are returned, when to prefer it, how fresh data is, and what data quality caveats exist — enough to invoke it correctly.

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 description coverage is 100% and the only parameter, identifier, already documents accepted formats (uuid, podcast:guid, RSS feed URL). The description adds no extra meaning beyond the schema, so baseline 3 applies.

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?

Description states it returns a show's headline download metrics: 30-day total, week-by-week breakdown for four weeks, and weekly average. It also contrasts itself with 'raw query tools', helping an agent distinguish it from the many sibling aggregation and query tools.

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?

Gives explicit direction to prefer this tool over 'raw query tools' whenever it can answer the question, and notes it is a 'fast answer' to a common query. It doesn't name exact sibling tools or formally state when not to use it, but the category-level guidance and freshness limitation are useful.

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