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

Annotations already mark the call as read-only, idempotent, and non-destructive. The description adds meaningful behavioral context beyond that: the cost per call, the payment-required error for unpaid calls, and the specific grouping/revenue-bucket behavior. 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 compact and front-loaded: it opens with what the tool returns, then gives the use case and alternative, then the cost/error caveat. Every sentence earns its place and none are redundant.

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 read-only comparison tool with a rich output schema and full parameter documentation, the description covers the core behavior, use case, alternative tool, and a critical payment constraint. Nothing needed to invoke it correctly is missing.

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 description coverage is 100%, so the baseline is 3. The description reinforces that the tool compares a company's metrics for a fiscal year, but it does not add materially new meaning to the cik or fy parameters beyond what the schema already provides.

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 names the specific resource ('One company's metrics for a fiscal year'), the comparison target ('its industry cohort'), and the actual content ('percentiles of every metric for each revenue size bucket in its 2-digit SIC group'). It also explicitly distinguishes itself from the sibling industry_aggregate, so an agent can select it correctly.

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?

It states the intended use case ('judge whether a company's margins, returns or leverage are above or below sector norms') and names the alternative for a different need ('use industry_aggregate for a cohort without a specific company'). This is explicit when-to-use and when-not-to-use guidance.

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