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

Annotations indicate readOnly, openWorld, idempotent, non-destructive. The description adds rich behavioral details: for companies, it pulls latest 10-K data from SEC EDGAR/XBRL with correct handling of off-calendar fiscal years; for drugs, it pulls FAERS adverse event counts, FDA approval counts, and active trial counts. It also mentions sorted output and citation URIs.

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 comprehensive but slightly lengthy. It is well front-loaded with example triggers and immediately states the core functionality. Every sentence adds value, though a minor redundancy could be trimmed.

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 simplicity (2 parameters, no output schema), the description is remarkably complete. It covers data sources, edge cases (off-calendar fiscal years), sorting, and the number of sequential lookups it replaces. No gaps remain.

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 both parameters described. The description adds valuable context: explains that 'values' for company type are tickers/CIKs (with examples like AAPL, MSFT) and for drug type are names (with examples like ozempic, mounjaro). It clarifies the format and constraints.

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 starts with example queries ('Compare X and Y', 'X vs Y', etc.) and explicitly states it does side-by-side comparison of 2–5 companies or drugs. It clearly distinguishes from sequential single-pack lookups, making the 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 says 'ALWAYS PREFER over sequential single-pack lookups when comparing entities' and provides criteria for when to use (comparing companies or drugs). It also explains how results are sorted (by primary metric) for queries like 'largest'/'most'.

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