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

Beyond the readOnly/idempotent/destructive annotations, the description discloses data sources (SEC EDGAR/XBRL, FAERS, FDA), handling of off-calendar fiscal years, sorting by primary metric, and return of paired data with citation URIs. This adds significant behavioral context and does not contradict annotations.

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, usage preference, data source details, sorting behavior, and return format. It is front-loaded with query patterns for immediate recognition, and despite its length, it contains no fluff.

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 tool's complexity (two entity types, multiple data sources, sorting) and absence of an output schema, the description adequately explains what data is pulled, how results are sorted, and the return format (paired data + citation URIs). It provides enough context for an agent to select and use the tool 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% with descriptions for both parameters, so baseline is 3. The description adds valuable context: type='company' maps to specific financial metrics and type='drug' to adverse-event and trial counts, plus examples for the values array. This goes beyond the schema's basic 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 performs side-by-side comparisons of 2–5 companies or drugs in one parallel call, using trigger phrases like 'Compare X and Y' and 'head to head'. It distinguishes itself from sibling tools by focusing on multi-entity comparison rather than single lookups.

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 instructs to ALWAYS PREFER this tool over sequential single-pack lookups when comparing entities, and notes it replaces 8–15 sequential lookups. This provides clear when-to-use guidance and points to the alternative (sequential lookups), though it doesn't name specific sibling tools.

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