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

Beyond the read-only/idempotent annotations, the description adds rich behavioral context: data sources (SEC EDGAR/XBRL, FAERS), handling of off-calendar fiscal years, sorting by primary metric, and citation URI output. This significantly enhances understanding of what the tool does internally.

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 packed with useful information—trigger phrases, preference rule, data details, and return format—but the all-caps 'ALWAYS PREFER' and multiple example phrases make it slightly verbose. Still, every sentence earns its place, and it is well-structured.

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 two parameters and no output schema, the description fully covers what the agent needs: it states data sources, metrics, sorting behavior, and return format (paired data + citation URIs). For a tool of this complexity, it leaves no critical gaps.

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 schema already describes both parameters with 100% coverage, but the description adds valuable semantics: type='company' maps to 10-K financials, type='drug' maps to FAERS counts, and values must be tickers/CIKs vs drug names. It also clarifies the 2-5 limit with examples, 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 identifies the tool as a side-by-side comparison of 2–5 entities in one parallel call, with explicit trigger phrases like 'X vs Y' and 'rank these companies'. It distinguishes itself from sequential single-pack lookups, making its purpose and scope 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 instructs the agent to prefer this tool over sequential single-pack lookups when comparing entities and provides concrete query examples that signal when to use it. This gives actionable usage guidance with a clear alternative.

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