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

Annotations already indicate readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. Description adds valuable behavioral context: data sourcing (SEC EDGAR/XBRL for companies, FAERS for drugs), handling of off-calendar fiscal years, sorting by primary metric, return of paired data and 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?

Description is somewhat lengthy but front-loaded with natural language triggers that aid discoverability. Every sentence provides useful information; however, it could be slightly more concise by removing redundant phrases like 'rank these companies' as examples. Overall well-structured.

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, description adequately explains return format (paired data + citation URIs) and sorting behavior. It covers both entity types, edge cases (off-calendar fiscal years), and the comparative advantage over sequential lookups. Comprehensive for a tool of this 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?

Both parameters (type, values) have 100% schema description coverage. Description adds meaning by explaining that values should be tickers/CIKs for company and drug names for drug type, provides examples, and specifies min/max items (2–5). This enriches the schema beyond enum labels.

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?

Description starts with natural language triggers ('Compare X and Y', 'X vs Y') and clearly states it performs side-by-side comparisons of 2–5 companies or drugs. It specifies data sources (SEC EDGAR for companies, FAERS for drugs) and distinguishes itself from sequential lookups. The verb 'compare' and resource 'entities' are 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?

Explicitly instructs 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' This provides clear when-to-use guidance and contrasts with alternative approaches (sequential single-pack lookups). It also explains different data sources for company vs drug types.

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