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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the 'over time' aspect and the cohort month/week grouping, which is somewhat behavioral. However, it does not disclose additional details such as pagination, result limits, or handling of missing data. Given annotations, this is acceptable but not rich.

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 a single concise sentence with no redundant words. It front-loads the core action and immediately lists the key output metrics and grouping options. Every element earns its place, and there is 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?

Given that an output schema exists (which presumably describes the return format), the description does not need to explain return values. The essential aspects for calling the tool—what it returns and the parameters—are covered by the schema. The description provides a clear high-level overview. The only minor gap is the lack of explicit usage context, but for a read-only query tool with rich schema and annotations, this is adequate.

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 description coverage is 100%, so all parameters are already documented in the input schema. The description only reiterates the metric names and period granularity, which are already present in the schema's enum descriptions. It adds no new semantic information beyond what the schema provides, so the baseline score of 3 is appropriate.

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 verb 'Get' and the resource 'customer cohort analysis', and lists the key metrics (LTV, repeat purchase rate, revenue) and time granularity (month/week). It is specific and unambiguous, but it does not explicitly differentiate from sibling tools like get_ltv_summary or run_repeat_purchase_rate, which could overlap in purpose.

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?

There is no guidance on when to use this tool versus alternatives. For example, it does not explain when to prefer cohort analysis over a simple LTV summary or repeat rate report, nor does it mention any prerequisites or context. The agent is left to infer usage from the tool name and schema.

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