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

Annotations indicate no special read-only, open-world, or destructive hints. The description clarifies it is a feedback mechanism ('This helps improve the engine'), implying a side-effect operation. No contradiction, and it adds behavioral context beyond 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 is only three sentences, front-loaded with the core purpose, followed by usage examples and a boundary. Every sentence adds value without redundancy.

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 feedback tool with five parameters (three required) and no output schema, the description sufficiently covers purpose, usage, and behavioral context. No additional details on return values are needed.

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 coverage is 100% with all five parameters described in the schema. The description does not add additional parameter details beyond the schema, which is acceptable at the baseline of 3.

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 tool's purpose: to report when a tool result was unhelpful, incomplete, or wrong. It uses specific verbs ('report', 'call this whenever') and distinguishes from siblings by being a feedback tool, not a recommendation or cart tool.

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 explicit guidance on when to use the tool ('whenever you override a recommendation, skip a cart result, or notice the engine output doesn't match') and when not to ('Do not use proactively — only when you observe an actual issue'). This clearly differentiates from alternative actions.

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