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

Annotations already declare readOnlyHint, destructiveHint, etc., so the description adds context beyond them: it explains SEC EDGAR/XBRL data source, off-calendar fiscal year handling, and result sorting. This enriches the behavioral understanding 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 dense but well-organized, starting with user phrasing, then purpose, usage preference, and type-specific details. While longer than ideal, each sentence adds critical behavior or context, and the structured flow aids comprehension.

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 adequately explains the return value (paired data + citation URIs) and covers data sources, sorting, and type-specific metrics. It gives a complete picture for the tool's simple parameter set.

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 input schema already covers both parameters with descriptions, so the baseline is 3. The description adds significant value by explaining what each type pulls (e.g., 10-K metrics for company, FAERS counts for drug) and giving concrete examples for values, going beyond the 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 a single call, distinguishing it from sequential lookups. It uses specific verbs like 'compare' and 'rank' and cites concrete query examples, making its purpose unmistakable.

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?

It explicitly says to 'ALWAYS PREFER' this tool over sequential single-pack lookups when comparing entities, and provides clear examples of when to use it (X vs Y, which is bigger, rank these). This gives strong guidance on when to invoke it instead of alternatives like entity_profile.

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