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

Annotations already disclose that the tool is read-only, idempotent, and non-destructive, so the description needs only to add contextual behavior. It adds that data comes from Mixpanel and that results represent cohort return counts, but it does not discuss authentication nuances, rate limits, or empty-result behavior.

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 front-loaded: action, data source, outcome, then a concrete invocation example. There is no filler, and every sentence earns its place.

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 three-parameter read-only tool with strong annotations, an output schema, and a complete input schema, the description is largely sufficient. The main gaps are explicit sibling differentiation and any caveat about Mixpanel availability or retention-window interpretation.

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 has 100% parameter descriptions and already includes an example, so the bar is at baseline 3. The description's example call is helpful for reinforcement but does not add meaning beyond what the schema provides.

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 states a specific action and resource: getting Mixpanel user retention cohort data, and clarifies the metric as 'how many users return over time.' It is semantically distinct from siblings like get_events or get_funnels, though it does not explicitly name the alternative it is not.

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 implies the use case—retention analysis in Mixpanel—but gives no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives or conditions under which a different sibling tool should be chosen.

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