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

Beyond the annotations (readOnly, openWorld, idempotent, non-destructive), the description discloses the data source (SEC EDGAR/XBRL for companies), how off-calendar fiscal years are handled, and that results are sorted by primary metric. This significantly enriches behavioral transparency without contradicting 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?

Despite its length, every sentence provides value—trigger examples, entity count limits, data specifics, and scheduling behavior. The information is front-loaded with the purpose before diving into details.

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?

The tool has no output schema, but the description compensates by explaining return characteristics: paired data with citation URIs, sorted by primary metric, and the data fields per type. This gives the agent a complete mental model for selection and invocation.

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 documents the two parameters with full coverage, the description adds critical semantics: for type='company' it specifies exactly which financial metrics are retrieved, and for drug it specifies FAERS counts. This helps the agent anticipate the tool's output based on chosen values.

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 concrete trigger phrases ('Compare X and Y' / 'X vs Y') and clearly states the tool performs side-by-side comparisons of 2–5 entities. It explicitly distinguishes itself from sequential single-pack lookups, 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?

The description explicitly says 'ALWAYS PREFER over sequential single-pack lookups when comparing entities', providing clear guidance on when to use this tool. It also breaks down use cases by type (company vs drug), eliminating ambiguity about applicable scenarios.

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