get_retention_cohorts

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

Without annotations, the description carries the full burden. It discloses the return format (JSON string with monthly cohort table) and the meaning of values above 100% (expansion), which adds useful behavioral context. However, it does not explicitly state that this is a read-only operation or describe any side effects or permissions needed, though 'Get' implies safety.

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 compact and well-structured with separate sections for purpose, args, and returns. Every sentence adds value, with no redundant 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?

The description covers purpose, parameters, and return value, making it adequate for a simple read-only tool with only two optional parameters. It also provides a useful interpretation of the output (>100% indicates expansion). However, it could be more explicit about the default behavior when app_id is empty, but the overall completeness is high.

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 provides no descriptions (0% coverage), so the description is essential. It explains 'app_id' as 'Filter by app (optional)' and 'months' as 'How many months to track per cohort (default 12),' which adds meaning beyond the raw schema. Both parameters are adequately explained.

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 'Get monthly revenue retention cohort table' – a specific verb and resource. This distinguishes it from sibling tools like get_churn_analysis or get_customer_ltv by focusing on retention cohorts.

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 provides no explicit guidance on when to use this tool versus alternatives. 'Get monthly revenue retention cohort table' implies a use case but does not mention exclusions or alternative tools. There is no context such as 'for churn analysis, use X instead.'

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