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

The description enriches the read-only/idempotent annotations with specific behavioral details: it pulls 10-K financial metrics from SEC EDGAR/XBRL, handles off-calendar fiscal years, sorts results by primary metric, and returns paired data with citation URIs. This goes well beyond the annotations and provides actionable expectations.

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 yet efficient. It front-loads with user intent examples, then covers data sources, behavior, and output, finishing with an ROI statement ('Replaces 8–15 sequential lookups'). Every sentence adds value 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 the moderate complexity (2 params, no output schema), the description fully compensates by stating what is returned (paired data, citation URIs), how results are sorted, and the data source specifics. This is sufficient for an agent to invoke the tool and interpret results 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?

The input schema already covers both parameters with descriptions, enumeration for 'type', and constraints for 'values'. The description adds some context (e.g., what metrics are pulled for each type) but does not significantly change parameter understanding. With 100% schema coverage, the baseline of 3 is appropriate.

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 in one parallel call. It uses specific verbs like 'compare', 'rank', and 'head to head', and explicitly distinguishes itself from sequential single-pack lookups, making its purpose and scope 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 provides explicit example queries ('Compare X and Y', 'which is bigger/better', 'rank these companies') and specifies when this tool should be preferred over sequential lookups. It also differentiates behavior between company and drug types, offering clear usage context.

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