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

The description adds significant context beyond annotations: it explains data sources (SEC EDGAR for companies, FAERS for drugs), handling of off-calendar fiscal years, sorting by primary metric, and the inclusion of citation URIs. Annotations already indicate read-only and idempotent, so the description enriches transparency.

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 concise yet comprehensive, starting with example queries and clearly explaining behavior. Every sentence serves a purpose, and the structure efficiently conveys key information without redundancy.

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 no output schema, the description adequately explains the return format (paired data + citation URIs) and the sorting behavior. It also mentions the replacement of 8–15 sequential lookups, giving the agent confidence in efficiency. For the complexity of this tool, the description is complete.

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?

While the schema already has 100% coverage and describes parameters, the description adds meaningful context: for type='company' it specifies data pulled (revenue, net income, etc.) and for type='drug' it specifies adverse-event counts. It also explains how values are interpreted (tickers/CIKs for companies, names for drugs), going beyond the schema's brief descriptions.

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 does side-by-side comparison of 2–5 companies or drugs, and provides example queries ('X vs Y', 'which is bigger'). It distinguishes itself from sequential single-pack lookups, making the purpose unambiguous.

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 advises 'ALWAYS PREFER over sequential single-pack lookups' and gives example use cases. This provides strong guidance on when to use the tool and when not to use alternatives.

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