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

With no annotations present, the description carries the burden of behavioral disclosure. It states that the tool returns structured records and requires an API key. However, it does not disclose practical behaviors such as pagination behavior, maximum result limits, sort order, or how filters combine (AND/OR semantics), which are important for an effective search tool.

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 rich but compact, covering action, scope, return structure, use cases, and authorization in a single block. It is slightly expansive in the list of use cases, but each sentence contributes meaningful information and the core action is front-loaded.

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?

Without an output schema, the description appropriately explains the return format and acknowledgement of the API key requirement. It remains incomplete on pagination details, default behavior with no filters, and clarification of date bounds, but overall it provides enough context for an agent to begin using the tool correctly.

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 description maps natural languages like state, company, effective date range, and county to several parameters, which is helpful given 0% schema coverage. Still, it does not explain limit and offset, date formats, or how 'start_date' and 'end_date' interplay, so the meaning of two semantically significant parameters is left to the caller to infer.

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 uses a specific verb and resource ('Search US WARN Act mass-layoff and plant-closing notices'), enumerates search filters, and describes the structured return fields. It clearly distinguishes this tool from sibling tools like describe_dataset and layoff_coverage_stats by framing it as the search interface to WARN notice data.

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 strong contextual guidance with concrete use cases: layoff tracking, corporate distress, employment-law research, and recruiting/outplacement leads. It does not explicitly name sibling tools or state when not to use this tool, but the use-case framing implies appropriate scenarios and sets clear expectations.

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