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

Beyond the readOnlyHint annotation, the description reveals the return structure (daily series, all-time monthly rollup), the data source (hourly churn rollup), and an important edge case ('valid but unknown country returns empty arrays'). Also notes 'keyless-cacheable' behavior. 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 cover purpose, output shape, edge case, and caching, with no filler. 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?

No output schema exists, so the description carries the burden of describing returns. It explains the series types and the edge case, but could be more explicit about the exact array fields. Overall adequate for the tool's moderate complexity.

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 parameters are already documented. The description adds semantic context for the country code (valid but unknown -> empty arrays) and clarifies that from/to bound the daily series. This provides extra meaning beyond the raw 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?

The description clearly states the resource and scope: 'Per-country participant churn' and 'New (joiner) vs departed (leaver) participants for one country'. It distinguishes from sibling tools like get_access_point_churn by focusing on country-level data, and specifies the output shape (daily series + monthly rollup).

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 usage context is implied by the name and description (for country-level churn), but there are no explicit alternatives or when-not-to-use conditions. Sibling tool names exist but are not referenced, so the agent must infer when this tool is the right choice.

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