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

Annotations already establish read-only, open-world, idempotent, and non-destructive behavior. The description adds rich behavioral detail: pulls from SEC EDGAR/XBRL for companies and FAERS for drugs, correctly handles off-calendar fiscal years, sorts results by primary metric, and returns paired data with citation URIs. 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 dense but every sentence earns its place: trigger phrases, entity types, data sources, sorting, output format, and efficiency gains. It is front-loaded with the most relevant usage signals and contains no filler.

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?

For a tool with two parameters and no output schema, the description is thorough. It covers when to use, input format, data sources, edge cases (off-calendar fiscal years), and return format (paired data + citations). This is sufficient for an agent to select and invoke correctly.

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%, so both parameters are already described. The description adds meaningful context beyond the schema: examples for each type (AAPL/MSFT, ozempic/mounjaro), what data is pulled per type, and behavior like fiscal-year handling. This enriches understanding above the baseline.

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's purpose: comparing 2–5 companies or drugs in one parallel call. Trigger phrases like 'X vs Y' and 'which is bigger' make it easy to identify when this tool applies. It also distinguishes itself from sequential lookups, making it distinct from sibling tools such as entity_profile.

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 provides strong when-to-use guidance: any comparison request (e.g., 'X vs Y', 'rank these companies') and explicitly says to prefer this over 8–15 sequential lookups. It implies when not to use (for a single entity) by limiting to 2–5 entities, but does not explicitly name alternative tools like entity_profile for single-entity cases.

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