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

With no annotations, the description carries the full behavioral burden. It discloses that feedback is free, requires a URL or jobId for reproduction, and is the only way the system learns about bad page reads, but it does not explain what happens after submission, whether it is anonymous or stored, or any rate limits.

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 front-loaded with the core action and remains reasonably concise. The final sentence provides a justification for using the tool, which is helpful but slightly verbose.

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 feedback tool with no output schema and 80% schema coverage, the description adequately explains when to use it and what to provide. It lacks details on post-submission behavior, but that is not critical for a correctly invoked call.

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 80%, so the baseline is 3. The description reinforces the use of 'url' or 'jobId' (reference) for reproduction and implies the verdict is 'good' or 'bad', but adds little meaning beyond the schema's own descriptions.

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 clear verb+resource: submit feedback ('Tell us an answer was good or bad') on web tool output quality. It does not explicitly name sibling tools or distinguish itself from them, but the name and context make the purpose obvious.

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?

It gives a clear condition for use: 'Use it when a result is wrong' with concrete examples (empty markdown, missing button, mismatched data). It also implies use for good results via 'good or bad', but offers no when-not-to-use guidance or alternative tools.

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