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

The description adds behavioral context beyond annotations: off-calendar fiscal year handling, sorting by primary metric, and citation URIs. It does not contradict any annotation; all provided hints (readOnly, openWorld, idempotent) are consistent with the description.

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 well-structured, front-loading example queries and the core purpose. While it is slightly lengthy due to detailed data source explanations, each sentence adds value. Could be tightened slightly without losing clarity.

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 lack of output schema, the description covers input requirements, data sources, sorting, citations, and efficiency gains. It does not explicitly describe the output structure beyond 'paired data + citation URIs', which is a minor gap. Overall, it is fairly complete for a complex tool.

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 coverage is 100%, and the description enriches both parameters: it explains the enum values for 'type' (company/drug) with data sources, and specifies the format and size constraints for 'values' (tickers/CIKs for company, drug names, min 2 max 5). This adds significant meaning beyond the schema.

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 performs side-by-side comparisons of 2-5 companies or drugs, with specific data sources for each type. It distinguishes itself from sequential lookups and includes example queries, making its purpose 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 advises preferring this tool over sequential single-pack lookups and provides example queries that trigger it. It details when to use company vs drug type, but lacks explicit exclusion criteria for single-entity lookups or alternative tools like entity_profile.

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