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

With no annotations provided, the description must convey behavioral traits. It discloses that the submission is free, read by a human, and that reports help fix defects. However, it does not clarify whether the tool is read-only, whether it has side effects, or whether it returns a confirmation. The description partially informs the agent of behavior but stops short of a complete transparency picture.

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 a single, tightly written paragraph of about 70 words. It front-loads the core purpose ('Report something wrong') with examples, then adds the key practical details (free, read by human, include expected vs got). Every sentence earns its place with zero redundancy, making it concise and effectively scannable.

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 straightforward feedback tool with a rich schema, the description covers the essential context: when to use it, what kinds of issues to report, and how to phrase the problem. It does not discuss return values, but there is no output schema and the tool likely returns a simple acknowledgment. The description is complete enough for correct invocation.

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 already has 100% coverage with detailed descriptions for each of the 6 parameters. The description adds minimal extra semantic value—it advises to 'Say what you expected as well as what you got,' which loosely maps to the 'expected' field, but it does not explain parameter syntax or formats beyond what the schema provides. Baseline 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 states a clear verb and resource: 'Report something wrong with a result.' It enumerates concrete examples (wrong data, filter not filtering, ranking off-topic, unreproducible number, useless answer), making the tool's purpose unambiguous and immediately actionable. Though it does not explicitly contrast with the sibling 'report_correction', the purpose is specific enough that an agent can tell what it does.

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 gives clear context for when to use it (when something is wrong with a result) and emphasizes it's the 'fastest way to get a defect fixed.' However, it does not mention when not to use it or reference any alternatives like the similar 'report_correction' tool. The guidance is implied but not explicit about exclusions or competing choices.

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