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

The description discloses that it pulls LATEST 10-K financials, handles off-calendar fiscal years, sorts results by primary metric, and returns paired data with citation URIs. This goes beyond the annotations (readOnlyHint, openWorldHint, idempotentHint) to explain data sources and output behavior, without contradicting any annotation.

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 densely informative but somewhat long, starting with trigger phrases and then the core functionality. Each sentence adds value, but the trigger list and value-proposition statement make it slightly less concise than ideal. Overall it's well-structured and front-loaded.

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?

Despite having no output schema, the description covers the tool's inputs, data sources, sorting behavior, and output format (paired data + citation URIs). It also mentions the off-calendar fiscal year handling, making it a complete description for an AI agent to use 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 description adds significant meaning to the 'type' and 'values' parameters beyond the schema. For type='company', it specifies exactly which financial metrics are pulled; for type='drug', it lists adverse-event counts, FDA approvals, and trial counts. It also implies values semantics (tickers/CIKs for company, names for drug) with examples, enriching 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 it performs side-by-side comparison of 2–5 companies or drugs in a single parallel call, using specific verbs and resources (SEC EDGAR/XBRL for companies, FAERS/FDA/trials for drugs). It distinguishes from sibling tools like entity_profile by focusing on comparisons and explicitly positions itself as preferable to sequential 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?

The description provides explicit trigger phrases ('X vs Y', 'which is bigger', 'rank these companies') and states 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It also outlines the number of entities (2–5) and the distinction between company and drug types, which guides when to invoke.

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