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

Beyond the readOnlyHint annotation, the description discloses specific data sources (SEC EDGAR/XBRL for companies, FAERS for drugs), how off-calendar fiscal years are handled, and that results are sorted by primary metric. It also mentions return of citation URIs, adding valuable 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 but well-structured, moving from user intent examples to core functionality to type-specific behavior and output. Every sentence adds value with no filler; it is front-loaded with the key purpose and usage directive.

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?

With no output schema, the description covers return format (paired data + citation URIs), sorting behavior, entity-specific data, and even fiscal year edge cases. It provides sufficient context for an agent to select and invoke the tool correctly without needing additional information.

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?

Although the schema already covers both parameters 100%, the description significantly enriches meaning: for 'type' it lists exact metrics pulled (10-K revenue, net income, cash, long-term debt; FAERS counts, FDA approval counts, active trial counts), and for 'values' it provides example formats (tickers/CIKs, drug names) and clarifies the off-calendar fiscal year handling.

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 opens with example user queries and then defines 'side-by-side comparison of 2–5 companies or drugs in ONE parallel call,' clearly stating the verb, resource, and scope. It distinguishes itself from single-entity tools like entity_profile by emphasizing the parallel comparison and specific entity types.

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 states 'ALWAYS PREFER over sequential single-pack lookups when comparing entities' and that it 'Replaces 8–15 sequential lookups,' offering direct guidance on when this tool is the right choice. This is a clear directive against alternative approaches.

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