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

Given the annotations (readOnlyHint=false, openWorldHint=true), the description adds significant behavioral context: it explains the credit charging logic (1 credit per asked mention, free for 10 minutes, different mention charges again), the deduplication of copies, the exclusion of the input mention from results, and that meta.credits_used indicates cache usage. This is rich and non-obvious behavior that the annotations don't cover.

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 long, but every sentence provides essential behavioral or use-case detail, and the most important purpose is front-loaded. The credit logic and cache behavior are crucial for correct usage and are clearly organized. No wasted words.

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 single-parameter tool with no output schema, the description covers everything an agent needs: what the input should be, what happens to the output (similar mentions, sorted by similarity), edge cases (collapsing copies, excluding input), and billing/caching semantics. The use of meta.credits_used is also explained.

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 schema already covers the id parameter perfectly (100% coverage with format and source description). The tool description doesn't repeat parameter details but adds a critical constraint (collected in the last 30 days) that is already in the schema, so it adds minimal extra value. 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 clearly states that this tool finds mentions similar to a given one, listing the exact use case (showing a complaint is not a one-off) and scope (across all keywords and Explore runs). It distinguishes it from list_mentions and get_keyword_results by defining the similarity behavior, though it doesn't explicitly name a sibling alternative.

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 explains when to use it (to find similar mentions, gather more quotes) and mentions the 30-day input freshness constraint, which implies the input must come from recent results. It doesn't explicitly say when not to use it or compare to siblings, but the use case is fairly clear.

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