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

Annotations declare readOnlyHint, openWorldHint, idempotentHint true, and destructiveHint false. The description adds rich behavioral details: data sources (SEC EDGAR/XBRL, FAERS), fiscal year handling, result sorting by primary metric, and return of paired data with 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 dense but well-organized, starting with example queries, then listing data sources, then clarifying behavior. It could be slightly more concise by grouping the data source details, but every sentence adds value and the structure is logical.

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?

Despite no output schema, the description explains what is returned (paired data, citation URIs) and how results are sorted. It covers both entity types in detail, addresses edge cases (off-calendar fiscal years), and the annotations provide additional safety guarantees. The tool is fully specified for its complexity.

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 both parameters (type, values) with full descriptions. The description adds semantic value by specifying that company values should be tickers/CIKs and drug values should be names, and provides examples ('AAPL', 'MSFT', 'ozempic'). This goes beyond the schema's enum and type constraints.

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 one parallel call. It provides example queries and differentiates from sequential single-pack lookups, making the purpose clear and distinct from sibling tools like get_entity or 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 clearly specifies when to use this tool (comparison queries like 'X vs Y', 'rank these companies') and advises preferring it over sequential lookups. It also includes concrete query examples, providing both positive guidance and exclusion conditions.

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