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

Annotations already indicate readOnly, openWorld, idempotent, non-destructive traits. The description adds substantial behavioral context: exact data sources (SEC EDGAR/XBRL for companies, FAERS for drugs), correct handling of off-calendar fiscal years, sorting by primary metric, and return of citation URIs. No contradiction 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 a single dense paragraph but front-loads the core purpose and example phrases. Every sentence adds value (use cases, type-specific behavior, sorting, alternatives). Could be slightly improved with bullet lists for clarity, but remains highly efficient.

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 the tool's modest complexity (2 params, no output schema), the description covers all essential aspects: when to use, what data is returned for each type, sorting, citation URIs, and data source details. The agent can confidently invoke this tool without additional context.

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 adds meaning beyond the schema: it provides example inputs (e.g., 'AAPL', 'MSFT'), specifies min/max items, explains that values depend on type (tickers vs drug names), and describes how results are sorted. This enriches parameter 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 explicitly states the tool's function: 'side-by-side comparison of 2–5 companies or drugs in ONE parallel call.' It provides concrete example phrases (e.g., 'Compare X and Y', 'which is bigger') and clearly distinguishes it from sibling tools like entity_profile by emphasizing it replaces multiple sequential 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 gives clear when-to-use guidance: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It explains the data returned for each entity type and sorting behavior. However, it does not explicitly state when NOT to use the tool or name specific alternatives (beyond the implicit single-entity lookups).

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