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

Annotations indicate readOnlyHint=false and destructiveHint=false, so the tool is a write operation but not destructive. The description adds context about what to report but doesn't disclose side effects, authentication requirements, or confirmation behavior. It doesn't contradict the annotations, but it doesn't significantly enhance the behavioral picture beyond them.

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 two sentences, front-loading the purpose and then the usage context. Every word contributes value, and it's appropriately concise for a straightforward feedback tool.

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?

The tool has no output schema and only three parameters, all documented. The description covers the purpose and when to use it. Minor gaps like what happens after submission (e.g., confirmation) aren't critical for correct invocation, making this adequate but not exhaustive.

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 100%, with each parameter (business_id, type, comment) already documented in the schema. The description adds no additional parameter semantics, so the baseline of 3 applies.

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: reporting data quality issues for a business, with concrete examples of issues (incorrect phone numbers, wrong addresses, etc.). It distinguishes itself from sibling tools like get_business or search_businesses by focusing on feedback rather than data retrieval.

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 provides when-to-use guidance ('Use when you notice incorrect phone numbers, wrong addresses, outdated info, or closed businesses'), but it doesn't mention when not to use it or name alternative tools. While no sibling directly competes, explicit exclusions would make the guidance stronger.

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