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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint correctly. The description adds detailed behavioral context: for companies, it pulls specific financial metrics from SEC EDGAR/XBRL with correct fiscal year handling; for drugs, it pulls FAERS and FDA data. It also explains sorting by primary metric and citation URI generation, going well beyond 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 concise yet comprehensive. It front-loads with common query patterns, uses bullet-like phrasing, and every sentence provides unique value. No redundancy with the schema or annotations.

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 the tool's moderate complexity (two entity types, different data sources, sorting, citations) and no output schema, the description completely covers what the tool does, what data it returns, and why it should be preferred. It leaves no critical gaps for an AI agent.

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 enums for type and min/max constraints for values. The description adds crucial meaning: it explains that 'company' values should be tickers/CIKs (with examples ['AAPL', 'MSFT']) and 'drug' values should be names (with examples ['ozempic', 'mounjaro']), which is not fully captured in the schema alone.

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 defines the tool's purpose: side-by-side comparison of 2–5 companies or drugs in one parallel call. It provides explicit examples ('X vs Y', 'rank these companies') and distinguishes from siblings like entity_profile by stating it replaces sequential single-pack lookups.

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 gives explicit usage guidance: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It also lists concrete query patterns ('which is bigger', 'head to head') and specifies the number of entities (2–5), leaving no ambiguity about when to invoke this tool.

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