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

Annotations declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds significant behavioral context: for company, it pulls LATEST 10-K financials with specific fields (revenue, net income, cash, long-term debt) and handles off-calendar fiscal years; for drug, it pulls FAERS adverse-event counts, FDA approval counts, active trial counts. It also states results are sorted by primary metric and includes 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 paragraph that front-loads common user intents and then explains behavior. It is reasonably concise, but could be slightly more structured (e.g., bullet points for different types). Every sentence adds value; no repetition.

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 2 parameters with full schema coverage, rich annotations, and no output schema, the description adequately explains what data is returned (financials or drug counts), sorting behavior, and citation URIs. It also notes it replaces 8-15 sequential lookups, giving a sense of efficiency. The description is complete for an agent to correctly invoke the tool.

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 has 100% description coverage for both parameters. The description adds real-world context: for values parameter, it provides examples (tickers/CIKs for company, drug names) and reinforces min/max items. For type, it clarifies the data sources for each enum value. This adds value beyond the schema descriptions.

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 comparisons of 2-5 companies or drugs, with example phrases like 'compare X and Y' and 'head to head'. It distinguishes itself from sequential single-pack lookups by explicitly stating 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' The verb+resource is specific: comparing entities in a parallel call.

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 guidance: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It explains when to use each type (company vs drug) and what data each pulls. It does not provide explicit when-not scenarios, but the context is clear that this tool is for comparisons, not single entity lookups.

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