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

Annotations already declare readOnlyHint and destructiveHint, reducing the burden, but the description goes beyond them by disclosing specific data sources (SEC EDGAR/XBRL, FAERS), handling of off-calendar fiscal years, sorting by primary metric, and the return of paired data plus citation URIs. This adds significant behavioral detail without contradicting any 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 well-structured, starting with trigger phrases and then detailing behavior by type. Every sentence contributes useful information, though the 'Replaces 8–15 sequential lookups' line is somewhat promotional and the examples could be trimmed without losing clarity.

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 no output schema, the description compensates well by explaining what data is returned, how results are sorted, and that citations are included. It covers both entity types, parameter constraints, and the key advantage of parallel execution, making it complete for an agent to select and 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 parameters are already documented, but the description adds meaningful semantics by explaining what each type actually retrieves (company: 10-K financials; drug: FAERS counts, FDA approvals, trials). This goes beyond the schema's enum labels and enriches parameter understanding.

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, with explicit trigger phrases like 'X vs Y' and 'rank these companies.' It also differentiates itself from sequential single-entity lookups, making its purpose unambiguous and distinct from sibling tools such as entity_profile.

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 explicitly says to 'ALWAYS PREFER' this tool when comparing entities, and provides clear context for when to use it (comparing companies/drugs). However, it doesn't name alternative sibling tools or state explicit when-not-to-use conditions, so it stops short of a full usage guide.

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