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

Adds significant behavioral detail beyond annotations: single parallel call, handles off-calendar fiscal years, sorts results by primary metric, and returns citation URIs. Annotations already indicate read-only and idempotent, but description expands on data sources and result structure.

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?

Single dense paragraph with front-loaded natural language triggers, then key behavioral details. Every sentence adds value, but could be slightly more structured with bullet points or separation of input/output. Still concise and effective.

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?

Covers input (type and values with examples), behavior (parallel call, sorting), and output (paired data + citation URIs). No output schema exists, but description adequately describes return format. For a complex multi-entity comparison tool, this is 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. Description adds meaning beyond schema: explains what data each type pulls (10-K, FAERS), gives examples for values (tickers vs names), and clarifies sorting behavior, helping agent use parameters correctly.

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 companies or drugs, using specific financial or adverse event data. It includes natural language triggers like 'compare X and Y' and 'which is bigger,' making the purpose immediately recognizable and distinguishing it 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?

Explicitly instructs 'ALWAYS PREFER over sequential single-pack lookups when comparing entities' and mentions it replaces 8-15 sequential lookups, giving clear when-to-use guidance. Also implies not to use for single entity lookups via contrast with triggers and efficiency claim.

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