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

Description adds rich behavioral details beyond annotations: it pulls data from SEC EDGAR/XBRL for companies, handles off-calendar fiscal years correctly, and for drugs uses FAERS data. Annotations already indicate read-only, idempotent, open-world, and non-destructive, which align. No contradictions.

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: purpose first, then usage examples, then data source details. It's somewhat dense but every sentence contributes. Slightly longer than necessary but not excessively wordy.

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 no output schema, the description explains the return format (paired data + citation URIs) and that results are sorted by primary metric. Given the tool's complexity and full schema coverage, this is complete for an AI agent to understand the 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% with descriptions for both parameters. Description adds value by providing concrete examples (e.g., ['AAPL','MSFT'] for companies, ['ozempic','mounjaro'] for drugs) and explaining the 2-5 limit, but the schema already covers the basics.

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 it performs side-by-side comparison of 2-5 companies or drugs in one parallel call, with specific metrics for each type (e.g., revenue, net income for companies). It distinguishes itself from sequential single-pack lookups, which are slower.

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?

Explicitly states 'ALWAYS PREFER over sequential single-pack lookups when comparing entities', giving clear when-to-use guidance. Example queries like 'rank these companies' help. It doesn't explicitly mention when not to use (e.g., more than 5 entities) or alternatives like entity_profile for single entities, but the schema limits are implied.

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