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

Annotations already indicate safe, read-only, idempotent behavior. The description adds significant behavioral context: performance (replaces 8–15 sequential lookups), sorting by primary metric, handling of off-calendar fiscal years, data sources (SEC EDGAR/XBRL, FAERS, FDA), and output format (paired data + pipeworx:// 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 a single moderately long paragraph but every sentence provides valuable information. It is front-loaded with example phrases and the core action. Could be slightly more structured (e.g., bullet points for details), but remains clear and concise without 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?

For a tool with no output schema, the description sufficiently explains the return format (paired data, citation URIs, sorted by primary metric). It covers input, output, behavioral nuances, and use cases. Given the complexity (2 params, enum types, array of up to 5 items), the description is fully adequate.

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, but the description adds extensive meaning: for type='company' it explains exactly which financial metrics are pulled (revenue, net income, cash, debt) and handles fiscal years; for type='drug' it lists FAERS counts, FDA approvals, active trials. For values, it specifies tickers/CIKs for companies and drug names, with examples. This goes well beyond the schema.

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 performs side-by-side comparison of 2–5 companies or drugs in one parallel call, with example phrases like 'Compare X and Y' and 'rank these companies'. It clearly distinguishes from sequential single-pack lookups, which are 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 provides explicit guidance: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It also details what data is retrieved per type, but does not include exclusions or when not to use the tool.

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