customer_insights_active_users

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

Annotations already indicate readOnlyHint=true, destructiveHint=false, openWorldHint=true, idempotentHint=true. The description adds behavioral context not in annotations: that specific filters are ignored, and it outlines the response structure (usersDistribution fields). No contradictions detected.

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 extremely concise: two sentences plus a spec link. The first sentence states the purpose, the second clarifies filters and response structure. No wasted words.

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 no output schema, the description adequately explains the response structure (usersDistribution fields). Parameters are fully described. For a simple read-only tool with two optional parameters, this is complete enough. Could mention potential empty results, but not critical.

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?

Both parameters have clear schema descriptions (ISO date format). The description adds meaning by explaining that they filter 'monthly distribution buckets' and that other filters are ignored, which goes beyond the schema alone. Schema coverage is 100%, so this is strong.

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 it retrieves 'paid-vs-non-paid active-user distribution across the customer base, per month,' specifying the group key and bucket values. It distinguishes from sibling tools by noting that productId/hosting/product filters are ignored, making the purpose and scope unambiguous.

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 explicitly states that only startDate/endDate filters apply and that other common filters (productId/hosting/product) are ignored, providing clear guidance on valid usage. It could be improved by explicitly referencing sibling tools for alternative breakdowns, but the current guidance is sufficient.

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