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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds contextual details: results sorted by primary metric, returns paired data with citation URIs, handles off-calendar fiscal years for companies, and replaces multiple sequential lookups. No contradictions.

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 concise yet comprehensive. It front-loads the purpose with example phrases, then efficiently covers data sources, sorting, output format, and edge cases. Every sentence adds value, and it avoids redundancy with the schema.

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 what is returned (paired data + citation URIs). It covers entity types, parameter constraints, data sources, sorting behavior, and special handling (off-calendar fiscal years). The tool is complex but thoroughly described.

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% with both parameters described. The description adds significant meaning: for type='company' it specifies data from SEC EDGAR/XBRL including revenue, net income, cash, debt; for type='drug' it specifies FAERS, FDA, trial counts. It also clarifies that values are tickers/CIKs for companies and names for drugs, and the min/max 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 clearly states it performs side-by-side comparison of 2-5 entities (companies or drugs) with specific data sources. It provides example natural language phrases and explicitly distinguishes from single-entity lookups by stating 'ALWAYS PREFER over sequential single-pack lookups', effectively differentiating from siblings like 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 explicitly says when to use the tool (comparison queries like 'compare X and Y', 'rank these companies') and what to prefer it over ('sequential single-pack lookups'). It also explains the behavior for each entity type and the constraints on the values parameter.

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