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

Annotations indicate readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds critical context: for type='company' it pulls latest 10-K financials from SEC EDGAR/XBRL, handles off-calendar fiscal years correctly; for type='drug' it pulls FAERS adverse-event counts, FDA approval counts, and active trial counts. It also explains sorting by primary metric and return of citation URIs. No contradiction.

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 paragraph that effectively front-loads examples and purpose. Every sentence adds value, but the structure could be slightly improved with bullet points for readability. Still, it is concise for the complexity.

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 complexity (two entity types, multiple data sources), the description covers main behaviors comprehensively: data sources, sorting, return of paired data and citation URIs. It compensates for the lack of an output schema by explaining the result characteristics.

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?

Input schema has 2 parameters (type, values) with 100% schema coverage. The description adds meaning beyond the enum and array descriptions: explains what data is pulled for each type (e.g., revenue, net income, cash, debt for company; FAERS counts, FDA approvals, trials for drug) and specifies value formats (tickers/CIKs for company, drug names).

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, using action verbs like 'compare', 'rank', and 'head to head'. It distinguishes itself from sibling tools such as entity_profile (single entity) and deep_research (extensive research).

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 instructs to prefer this tool over sequential single-pack lookups when comparing entities, and provides examples like 'which is bigger', 'rank these companies'. It sets clear expectations for when to use.

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