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

Despite annotations already indicating read-only, idempotent, and non-destructive behavior, the description adds meaningful context: specifies data sources (SEC EDGAR/XBRL for companies, FAERS for drugs), handles off-calendar fiscal years, sorts results by primary metric, and returns citation URIs. No contradictions with 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 adds value: trigger phrases, capability, data specifics, sorting behavior, and output format. It is front-loaded with the most important usage context and remains focused throughout.

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 only 2 parameters and no output schema, the description fully covers inputs, behavior, and output expectations. It explains the return format (paired data + citation URIs) and the sorting by primary metric, making it complete for an agent to 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?

Schema coverage is 100%, so baseline is 3. The description enriches parameter meaning by describing what each type pulls (revenue, net income for company; adverse-event counts, FDA approvals for drug) and how values map (tickers/CIKs vs names). This goes beyond the schema's brief field 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 comparison of 2–5 companies or drugs in one parallel call, with explicit trigger phrases like 'X vs Y' and 'which is bigger'. It distinguishes itself from sequential lookups by emphasizing preference over them.

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?

Provides explicit when-to-use guidance: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities', along with concrete example queries. It also explains what it replaces (8–15 sequential lookups), making the choice clear.

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