downloads

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

With no annotations, the description does add real behavioral context: it discloses that the result is a period-over-period comparison (last N days vs. the N before), that it counts first-time rather than repeat downloads, and that `days` is capped at 1-30. It does not cover auth requirements, aggregation granularity, or what the response contains.

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?

Two tight sentences with the metric and comparison logic front-loaded, followed by the filtering and range constraints. No filler.

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 and no annotations, so the description is the only source of truth, yet it never says what the return looks like — per-day series vs. totals, per-app breakdown, or units. For a metric-reporting tool with zero structured support, that is a meaningful 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?

Schema coverage is 0%, so the description must carry the parameters, and it does: `app` is a substring match against title, SKU, or Apple id with null meaning all apps, and `days` is bounded to 1-30 whole days. Only the default value (7) is left to the schema.

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?

Names a specific metric ('first-time downloads') from a specific source ('App Store Connect Sales and Trends') and states the comparison window. An agent can distinguish it from proceeds/subscribers/events by the resource, though no sibling is named explicitly.

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?

Explains the `app` filter behavior ('leave it out for all apps') and the valid `days` range, which implies usage but never states when to pick this tool over `proceeds` or `subscribers`. Usage is inferable from the metric name rather than guided.

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