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

Annotations already indicate read-only, open-world, idempotent behavior. The description adds valuable context: it pulls latest data, handles off-calendar fiscal years, returns sorted by primary metric, and provides citation URIs. No contradictions 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 moderately long but each sentence adds value. It is front-loaded with natural language examples. However, it could be slightly more concise by removing redundant phrases like 'head to head'.

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?

Given no output schema, the description adequately explains the return format (paired data + citation URIs) and sorting. It covers data sources, entity types, and the efficiency gain (replaces 8-15 lookups). For a 2-param tool, this is very complete.

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%, so baseline is 3. The description adds meaning beyond schema: explains how 'values' should be formatted (tickers/CIKs for company, names for drug), sets limits (2-5), and describes the return data per type. This is substantial added value.

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 states the tool performs side-by-side comparison of 2-5 entities (companies or drugs) in one parallel call. It specifies the data sources (SEC EDGAR for companies, FAERS for drugs) and distinguishes from sequential single-entity lookups, making the purpose unambiguous.

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 provides explicit triggers ('Compare X and Y', 'which is bigger', 'rank these companies') and strongly recommends this tool over sequential lookups. It could be improved by explicitly mentioning when not to use (e.g., for single entities use entity_profile), but the guidance is already very clear.

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