get_build_usage_metrics

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

With no annotations, the description carries the full behavioral burden. It does explain that this returns aggregate counts over a reported date range and positions it as aggregate rather than raw event data. But it leaves ambiguity around what 'reported date range' means and does not describe pagination, output shape, or whether the tool requires specific analytics permissions.

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 two sentences, with the core purpose and metric list front-loaded, followed immediately by a practical use case. Every sentence earns its place and there is no redundant repetition.

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 tool with two parameters and no nested output, the description names the metric fields and the context in which they should be consumed. The main remaining gap is the vague 'reported date range' and the absence of any mention of how 'limit' affects the returned series, but the description is still sufficient for most selection purposes.

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 100%, so the schema already documents both parameters. The description adds no new meaning about the 'limit' parameter or its relationship to the returned data points, so it stays at the baseline.

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 action (Get), the resource (TestFlight usage metrics for a build), and enumerates the exact metrics returned: install, session, crash, invite, and feedback counts. This makes the tool easy to distinguish from sibling tools focused on raw feedback, diagnostics, or tester-level metrics.

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 second sentence gives a concrete use case: 'Use it to turn raw feedback and crash counts into rates.' This provides clear context for when the tool is useful. However, it does not explicitly name sibling alternatives or state when not to use this tool.

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