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

The description adds substantial behavioral details beyond annotations: for type='company' it pulls latest 10-K financials with correct off-calendar handling; for type='drug' it pulls FAERS, FDA approval, and trial counts. It also mentions sorting by primary metric and returning paired data with citation URIs. No contradiction with annotations (readOnlyHint, openWorldHint, etc.).

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 moderately long but well-structured. It front-loads trigger phrases to aid tool selection, then explains functionality and returns. Every sentence adds value, though a minor reduction in verbosity 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?

Despite lacking an output schema, the description covers all critical aspects: input constraints (2-5 entities), behavior per type, sorting, and output format (paired data + citation URIs). This is comprehensive enough for an agent to use the tool correctly.

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%, but the description adds meaning: it explains that 'company' values should be tickers/CIKs and 'drug' values names, and clarifies what each entity type returns. It also gives examples like ['AAPL','MSFT'] and ['ozempic','mounjaro'], which helps the agent select correct inputs.

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 starts with clear trigger phrases ('Compare X and Y', 'X vs Y', etc.) and explicitly states the tool performs 'side-by-side comparison of 2–5 companies or drugs'. It distinguishes this from sequential single-pack lookups, which are likely done by 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 explicitly says 'ALWAYS PREFER over sequential single-pack lookups when comparing entities', providing strong guidance on when to use. It also gives example queries. However, it does not explicitly mention when not to use it (e.g., for more than 5 entities), but the context is clear enough.

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