Follower counts over time

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

Annotations already cover safety (read-only, idempotent, non-destructive), and the description adds useful non-annotation behavior: it requires Apple Podcasts Connect credentials and identifies the data source. It does not disclose output format or pagination, but for a safe read operation this is a reasonable level of disclosure. No contradiction with 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?

Three sentences, each earning its place: what the tool returns, why the metric matters, and what credentials are needed. The core definition is front-loaded and there is no repeated schema or annotation 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?

For a simple, optional-parameter read with rich schema coverage and read-only annotations, the description provides the source, the metric, and the auth prerequisite. It could be slightly more explicit about the expected response shape (e.g., a series of counts per reporting period) since there is no output schema, but the description covers what an agent needs to call 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%, so the schema already documents date and date_type formatting, enums, and defaults. The description only adds the generic 'reporting period' context, which does not materially improve parameter understanding. This matches the baseline for high schema coverage.

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 states a clear resource ('follower numbers for your show') and scope ('across a reporting period') sourced from Apple's content performance report. It is unambiguous, but unlike a 5 it does not explicitly name sibling tools or exclusion conditions to differentiate it from get_top_shows or get_show_analytics.

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 a monitoring use case by calling followers a leading indicator for rank changes, and it states the credential requirement. It does not explicitly specify when to choose this tool over alternatives such as get_top_shows, find_chart_position, or get_show_analytics, nor any when-not-to-use conditions.

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