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

Annotations already cover readOnly, idempotent, and non-destructive behavior. The description adds substantive beyond-annotation context: the four result statuses, the condition for 'unknown', the data sources compared, and the beta/free status. 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?

The description front-loads the core purpose and is generally tight. Minor redundancy exists: 'which is free' and 'Free while in beta' both convey the same cost information, slightly reducing the score from a perfect 5.

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 read-only verification tool with a comprehensive output schema, the description covers the purpose, input semantics, result interpretation, and edge cases such as insufficient data. Nothing critical is missing for an agent to select and invoke it correctly.

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 100% coverage for both parameters, including types, constraints, and default values. The description only reinforces the conceptual role of these parameters (change time and comparison window) without adding details beyond the schema, so the baseline 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 opens by answering the core question the tool resolves ('after a change was made, did this store's revenue signals actually recover?') and specifies the comparison windows and result categories. This makes it easy to distinguish from siblings like diagnose_revenue_incident or get_checkout_health_snapshot, which are about diagnosis/health rather than post-change verification.

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 intended use case is clear: call this after a change has been applied to verify the fix held. It also provides interpretive guidance ('unknown when too little new data has arrived... A quiet ten minutes is not a recovery'). However, it does not explicitly name alternatives or state when NOT to use it, so it stops short of a 5.

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