apple_podcasts_summary

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

With no annotations provided, the description carries the full burden and does so excellently. It discloses that Apple counts unique devices rather than people, defines an engaged listener precisely (20 minutes or 40% of an episode), and warns that each period is a separate API call to Apple with throttling implications. These are non-obvious behavioral facts essential for correct use.

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?

Four tight sentences: state what it does, define key metrics, give usage context, and warn about API behavior. No filler or repetition; every sentence earns its place and the most important information is front-loaded.

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?

Despite having no output schema, the description tells the caller what to expect in return (metrics per period plus totals) and gives necessary caveats (device-based counting, engaged listener threshold, Apple's lag, range limits). For a read-only reporting tool with a fully specified input schema, this is complete enough to invoke 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?

The input schema already covers 100% of parameters with detailed descriptions, so the baseline is 3. The description adds value by explaining why 'keep the range short' (each period is a separate call) and by defining what the returned listener metrics actually mean, which clarifies the data behind the parameters. It doesn't describe each parameter individually, but the schema already does that.

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 opens with 'Show-level listening summary from Apple Podcasts Connect' and enumerates exactly which metrics are returned (plays, unique listeners, engaged listeners, followers) and how they are aggregated (per period and totalled). This clearly distinguishes it from siblings like apple_podcasts_episodes and apple_podcasts_followers by scope and content.

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 a direct usage cue: 'Use it for "how is the show doing on Apple" questions.' It also notes that this is owner-side data not exposed by hosting APIs. However, it does not explicitly mention when NOT to use it or name alternative sibling tools, so it falls short of the top tier.

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