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

Annotations already declare read-only and idempotent behavior. The description adds value by detailing what data is pulled (10-K financials for companies, FAERS/trial counts for drugs), handling of off-calendar fiscal years, sorting by primary metric, and 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 front-loaded with the core purpose and usage examples. Every sentence adds value, covering behaviors, types, and a note on efficiency. It is slightly long but packed with useful information. Minor trimming possible without losing clarity.

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?

For a tool with 2 parameters and no output schema, the description explains input constraints (2-5 items), data sources, metrics returned, and result format (sorted, with citation URIs). It covers the main use cases adequately. No explicit mention of error handling or limits beyond max items, but sufficient for agent decision-making.

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. The description adds meaning beyond the schema by explaining the interpretation of 'type' values (company pulls specific financials, drug pulls safety/trial data) and providing examples for 'values' (tickers for companies, drug names). This enhances the agent's understanding.

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 in a single parallel call. It distinguishes from sibling tools like entity_profile by explicitly preferring it over sequential single-entity lookups and provides query examples (e.g., 'X vs Y', 'rank these companies').

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 context: when comparing entities, use this tool instead of sequential lookups. It does not explicitly state when not to use it, but implies that for single entity queries, other tools like entity_profile are appropriate. The guidance is clear but lacks exhaustive exclusion criteria.

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