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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool is safe. The description adds that it returns 'the top values, the full symmetric matrix and the strongest pairs,' which provides some behavioral context beyond annotations, but does not disclose potential performance implications or data freshness.

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 three sentences long and front-loads the core purpose. It is clear without redundancy, but the final sentence specifying return values could be integrated more tightly with the first. Still, it earns a 4 for efficiency.

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?

Given the output schema exists, the description covers return structure adequately. However, it lacks explanation of how multiple filter parameters (e.g., keyword and subject) interact, which may be necessary for complex queries. With high schema coverage, a 3 is fair.

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?

All 9 parameters have descriptions in the schema (100% coverage). The description adds minimal extra meaning, such as 'multi-valued field' and 'same item,' but the schema largely suffices. 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 the tool computes how often top field values co-occur on the same item, forming a subject/place co-mention matrix. It uses specific language ('co-occurrence matrix', 'top values') that distinguishes it from any sibling tools.

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 implies the tool is for exploring co-occurrence patterns ('what is X discussed alongside') without reading items, but does not explicitly mention when to use it versus alternatives or provide exclusions. While the unique output type makes usage relatively clear, explicit guidance is missing.

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