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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds rich behavioral details: it specifies data sources (SEC EDGAR/XBRL for companies, FAERS for drugs), handles off-calendar fiscal years, sorts results by primary metric, and includes 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 well-structured with front-loaded query patterns and detailed behavior, but it is slightly verbose with repetitive emphasis on terms like 'largest/most/biggest'. Every sentence adds value, but minor trimming could improve conciseness.

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?

The description explains return values (paired data + citation URIs) and sorting behavior, but it lacks explicit structure of the paired data and does not name the primary metric for each type. Given the absence of an output schema, these minor gaps reduce completeness slightly.

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?

While the input schema has 100% coverage with descriptions, the tool description adds significant meaning beyond the schema. It explains what each 'type' value retrieves (10-K data vs. drug stats) and provides concrete examples for the 'values' parameter (e.g., tickers, drug names), enhancing usability.

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 uses specific verbs like 'compare', 'side-by-side comparison', and 'rank' to clearly define the tool's purpose. It explicitly distinguishes itself from sequential single-pack lookups by stating 'ALWAYS PREFER over sequential single-pack lookups when comparing entities', which differentiates it from sibling tools 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 provides clear guidance on when to use the tool, including example queries and the recommendation to use it over sequential lookups. However, it does not explicitly state when not to use it (e.g., for single entity lookups), leaving a minor gap in usage exclusions.

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