apple_podcasts_followers

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

With no annotations, the description carries the full burden. It discloses a key behavioral nuance: 'Read the resolvedColumn field in the response before interpreting the numbers: Apple's follower column has been both a running total and a per-period count, and which one you get changes what 'change' means.' It also mentions output structure (one value per period plus change) and implicitly that it's a read operation.

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 tightly written sentences. The first sentence states purpose and output, the second gives a use case, and the third warns about interpreting the data. No wasted words; front-loaded and easy to parse.

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?

There is no output schema, so the description must compensate. It explains the data shape (one value per period plus change) and the critical resolvedColumn caveat. It could be more explicit about the response structure, but for a trend tool this is sufficient. The schema fills in parameter behavior, and the description covers the essential interpretation pitfall.

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 provides 100% coverage with detailed descriptions for all four parameters, including defaults, date formats, and truncation behavior. The description adds no parameter-specific guidance, but the schema already does the heavy lifting, so a baseline 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 clearly states the tool's function: 'Follower trend for the show on Apple Podcasts over a date range: one value per period plus the change across the window.' It specifies the resource (follower trend) and scope (over a date range), distinguishing it from sibling tools like apple_podcasts_summary and apple_podcasts_episodes.

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 gives an explicit use case: "Use it for 'is my Apple following growing'." This tells the agent when to choose this tool. However, it does not name alternative tools or provide exclusion criteria, so it misses the 'when-not-to-use' aspect.

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