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

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses specific data sources (SEC EDGAR/XBRL, FAERS, FDA approval counts), fiscal-year handling, sorting by primary metric, and citation URI return format. No contradiction with annotations; this adds substantial behavioral context.

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 and well-structured, opening with trigger phrases that immediately aid tool selection, followed by functional behavior, per-type details, and output characteristics. Every sentence earns its place; no fluff or repetition.

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 no output schema, the description compensates by explaining it returns paired data and citation URIs. It covers both entity types, data sources, sorting, fiscal-year edge cases, and efficiency rationale ('replaces 8–15 sequential lookups'), making it complete 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?

The schema already describes both parameters, but the description adds significant semantics: 'type' determines which data source is used (company vs drug), and 'values' examples clarify format (tickers/CIKs vs drug names). It also explains how results are sorted, which aids parameter interpretation. While schema coverage is 100%, the description enriches meaning beyond the basic schema.

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 comparison of 2–5 companies or drugs in one parallel call, with explicit trigger phrases ('Compare X and Y', 'X vs Y'). It distinguishes from siblings by positioning itself as the preferred tool over sequential single-pack lookups, making its 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?

The description gives explicit when-to-use triggers and instructs 'ALWAYS PREFER' over sequential lookups, which is strong usage guidance. It also differentiates between company and drug types. However, it does not explicitly state when NOT to use the tool (e.g., when more than 5 entities need comparison), leaving a minor gap in exclusion guidance.

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