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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: the $0.10 per call cost, the payment-required error on unpaid calls, and the fact that unknown metrics return an error listing valid ones. It doesn't detail pagination or exact return shape, but the output schema exists and the added cost/error behavior goes beyond 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 states the core function first, then the output ordering, then the routing guidance, then the cost/error note. Every sentence earns its place, and the cost warning is a critical operational detail that is placed at the end without bloating the description.

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 screening tool with a rich input schema, output schema, and comprehensive annotations, the description covers the essential operational context: what it returns, how results are ordered, when to use alternatives, and the cost/error behavior. Nothing an agent needs to decide whether to call this tool 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 schema already documents all three parameters. The description adds context about the filters format (JSON list of triples, up to 8, unknown metric error) and the limit default/ordering, but these are also largely in the schema. Baseline 3 is appropriate because the schema carries the heavy lifting and the description doesn't add significant new parameter meaning beyond what's already there.

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 states a specific verb ('Screen'), a resource ('US public companies'), a scope ('one fiscal year'), and the output ordering ('largest revenue first'). It also names sibling tools (company_financials, industry_aggregate) to distinguish itself, making it clear what this tool is for.

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 says when to use this tool ('Use it to discover companies') and when to use alternatives ('use company_financials for one known company's history and industry_aggregate for cohort benchmarks'). This is direct routing guidance with no ambiguity.

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