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

Beyond annotations that indicate read-only, open-world, and idempotent behavior, the description details that the tool makes a single parallel call, sorts results by primary metric, and returns paired data with citation URIs. It also explains how financial data is sourced (latest 10-K, handling off-calendar fiscal years), which is valuable context not captured by 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 dense but front-loaded with trigger phrases and examples. Every sentence contributes value, though it could be slightly more concise. The structure is logical: first trigger examples, then usage guidance, then data details.

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 covers purpose, usage, behavioral details, parameter semantics, and result characteristics (sorted, citations). It explains data sources for both entity types and mentions sorting behavior. No additional information seems necessary for an agent to correctly invoke the tool.

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 descriptions for both parameters. The description enriches these by providing concrete examples (tickers/CIKs for company, drug names for drug) and clarifies that values array should contain 2-5 items. This adds meaningful context beyond 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 states the tool's purpose: 'side-by-side comparison of 2–5 companies or drugs in ONE parallel call.' It uses specific verbs and provides example queries, effectively distinguishing it from sibling tools like entity_profile which likely do single-entity 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 explicitly states 'ALWAYS PREFER over sequential single-pack lookups when comparing entities,' providing clear guidance on when to use this tool. It also explains the data sources for company and drug types, but does not explicitly state when not to use or mention alternatives beyond single lookups.

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