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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by revealing that the tool runs a 'sample query' and returns coverage metadata, which helps the agent understand what kind of operation occurs beyond the annotation hints.

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?

Two sentences, no filler. The first sentence is front-loaded with the tool's core output, and the second sentence immediately states the usage context. Every phrase adds value.

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 zero-required-parameter reporting tool, the description fully specifies what the agent will learn: publication date, update frequency, and findings-date range. The absence of an output schema is adequately compensated by the explicit list of returned coverage details.

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% because the only parameter, _apiKey, is already fully documented in the schema with its type and optionality. The description does not need to add parameter detail, so the baseline score 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 names the exact resource (Wage & Hour enforcement dataset) and the specific information it reports: publication date, update frequency, and findings-date range. It is clearly distinguishable from siblings like whd_search or whd_employer because it is a dataset-level coverage check rather than a case or employer lookup.

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 states when to use the tool: 'Use to check how current the enforcement data is before relying on an absence of cases.' This gives the agent a concrete decision trigger and explains the practical consequence of the data's freshness, which is more than most tool descriptions provide.

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