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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is established. The description adds valuable behavioral context: it clarifies that cases are 'concluded', defines the ordering ('highest first'), and specifies the fields returned (employer, industry, findings dates). This enriches the agent's understanding beyond the 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 two sentences with no filler. It front-loads the core purpose and immediately follows with return structure and a usage example. Every sentence earns its place, making it highly efficient for an agent to parse.

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 explains exactly what is returned: ordered cases with employer, industry, and findings dates. It also covers the optional filters and the domain (Wage & Hour enforcement). Annotations handle safety and world-view, so nothing an agent needs to invoke this correctly is missing. The description is complete for its complexity.

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?

The schema covers all parameters with descriptions (coverage 100%), including limit, naics, since, state, and _apiKey. The description mentions optional filtering by NAICS or state, which aligns with the schema but does not add new detail. Since the schema is complete, the description neither supplements nor contradicts parameter semantics; a baseline of 3 is appropriate.

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's purpose: ranking employers by back wages owed in concluded Wage & Hour cases. It uses a specific verb ('rank'), identifies the resource ('employers by back wages'), and specifies optional filters (NAICS or state). This distinguishes it from sibling tools like whd_search or whd_employer, which serve different lookup needs.

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 a concrete use case: "Use for 'who owes the most back wages in <industry>'." This gives clear context for when to invoke this tool. It does not explicitly mention alternatives or exclusions, but the 'Use for' phrasing implies the intended scenario without being misleading.

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