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

Annotations (readOnlyHint=false, destructiveHint=false) are neutral, but the description adds significant behavioral context: it returns 202, is applied by a human, score and band are ignored, and payment is never from prepaid balance. This goes beyond annotations and prepares the agent for asynchronous, human-mediated execution.

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 dense but efficient; each sentence adds value—purpose, human review, pricing, alternative. It is front-loaded with the primary action. It could be slightly trimmed for brevity, but it avoids redundancy and is well-structured for an agent scanning for key details.

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?

Despite having 8 parameters and no output schema, the description covers the essential behavior: async human application, return code 202, pricing, and the free alternative. It does not specify the response body format, but for a correction proposal that is acceptable. The context is sufficiently complete for an agent to 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?

Schema description coverage is only 13% (only context is described), so the description must compensate. It names the key editable fields (name, description, url, industries, tags) and notes that score/band are ignored, adding meaning beyond the schema. However, it omits the 'contact' parameter and doesn't elaborate on how 'context' is used (though schema covers it). Overall, it addresses most parameters but not all.

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 proposes corrections to a listing's name, description, url, industries, and tags. It uses the specific verb 'propose corrections' and identifies the resource ('what we say about you'). It also differentiates from siblings like report_correction (free for own company) and dispute_finding, making its role unmistakable.

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 explicitly explains when to use this tool versus the alternative: 'If this is your own company and our data about it is wrong, report_correction is free.' It also clarifies the pricing model and that it is a paid influence action, giving agents clear selection criteria without ambiguity.

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