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

Beyond the readOnlyHint annotation, the description details data sources (SEC EDGAR/XBRL for companies, FAERS/FDA/clinicaltrials.gov for drugs), how fiscal years are handled, sorting by primary metric, and the inclusion of citation URIs. It also quantifies the efficiency gain (replaces 8-15 sequential lookups).

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, starting with common trigger phrases, then the core action, then type-specific details, and finally the value proposition. While slightly long, every sentence adds essential information; no redundancy.

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 moderate complexity (two entity types, multiple metrics per type) and the lack of an output schema, the description covers data sources, sorting behavior, and output format (paired data + URIs). It is comprehensive enough for effective use, though it could optionally mention rate limits or error scenarios.

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?

The description adds significant context beyond the schema: it specifies that 'values' should be tickers/CIKs for companies and drug names for drugs, and explains what data fields are retrieved for each type. This helps the agent understand the expected input format and output semantics.

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 does side-by-side comparison of 2-5 companies or drugs in a single call, with explicit example queries and a strong distinction from sequential single-entity lookups (entity_profile). It leaves no ambiguity about the tool's function.

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 prefers this tool over sequential single-pack lookups when comparing entities, and provides concrete example triggers. However, it does not explicitly state when not to use it or mention alternative tools beyond the implied contrast.

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