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

Annotations already mark it read-only/idempotent, but the description adds substantial behavioral context: data sources (SEC EDGAR/XBRL, FAERS), handling of off-calendar fiscal years, sorting by primary metric, parallel execution, and citation URIs. No contradiction 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 information-dense and well-structured, starting with trigger phrases and core function, then entity-specific details, and ending with output format. While longer than two sentences, every sentence adds value and no content is redundant.

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?

For a tool with no output schema, the description explains return values ('paired data + citation URIs') and sorting behavior. It covers both entity types and common use cases, though 'paired data' could be more explicit about the exact response format. Overall, sufficient 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 covers 100% of parameters with baseline descriptions, but the description enriches meaning by detailing what metrics are pulled for each type. For example, type='company' pulls 10-K revenue and net income, while type='drug' pulls FAERS counts. This goes beyond the schema's simple enum and array 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 explicitly states the tool performs side-by-side comparison of 2–5 companies or drugs in a single call, with specific metrics for each type. It distinguishes itself from siblings by saying 'ALWAYS PREFER over sequential single-pack lookups when comparing entities,' making the 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?

Provides concrete trigger phrases such as 'Compare X and Y' and 'which is bigger/better/larger,' and clearly instructs to prefer this over sequential single-pack lookups. The description also specifies when to use type='company' vs type='drug', giving both context and alternatives.

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