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

Annotations already declare readOnly/openWorld/idempotent safety. The description adds meaningful behavioral context: data sources (SEC EDGAR/XBRL, FAERS), handling of off-calendar fiscal years, result sorting by primary metric, and citation URIs. It doesn't address limitations like latency or data availability, but the added context is solid.

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 and front-loaded with query examples, but it is longer than strictly necessary. Every sentence contributes useful information, and the structure flows from usage to data details to output format, earning its length.

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 covers input constraints, data fields per type, sorting behavior, return format (paired data + citation URIs), and efficiency benefit. This is enough for an agent to select and invoke the tool 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%, but the description enriches both parameters: type is explained with per-enum data details, and values gets explicit examples, count constraints, and formatting guidance (ticker/CIK vs drug names). This goes well beyond the basic schema 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 clearly identifies the tool as a side-by-side comparison for 2–5 companies or drugs in one parallel call, with concrete query examples ('X vs Y', 'rank these companies'). It distinguishes from sequential single-pack lookups by emphasizing 'ALWAYS PREFER' and 'Replaces 8–15 sequential lookups', and from sibling tools by specifying a unique comparison scope.

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?

Explicitly states when to use: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities' and provides usage scenarios via example queries. It also clarifies the two modes (company vs drug) and what data each pulls, giving clear contextual guidance.

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