state_layoff_totals

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

With no annotations provided, the description carries the full burden. It discloses that the tool returns only aggregates, that notices without headcount count as 0 workers, and that ordering differs by mode. It does not explicitly state read-only or no side effects, but 'Aggregates only' implies a safe query operation. A 4 reflects this strong coverage with minor omissions (e.g., no mention of rate limits or response size).

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?

Four sentences, each earning its place. The core purpose is front-loaded, conditional behavior is neatly summarized, and the constrast with search_layoff_notices is left for last without bloat. No redundant wording.

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?

With no output schema, the description explains the return structure at a semantic level: series grouping and ordering, totals object, and counting conventions. It does not name exact output fields (e.g., 'notices', 'workers') but that is easily inferable. Slightly more detail on the exact JSON shape would make it fully complete, hence 4.

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 coverage is 100%, but the description adds substantial meaning: it explains that year is optional, state changes the grouping behavior, and year restricts to a four-digit year. This goes well beyond the schema's terse type descriptions.

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 opens with 'Monthly WARN notice counts and workers affected' – a specific verb, resource, and data type. It then clearly differentiates two modes of operation (state vs. no state) and explicitly names a sibling tool ('use search_layoff_notices for the notices'), making it easy to distinguish from alternatives.

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 gives explicit when-to-use guidance: aggregates only, and when not to use it (for individual notices, use search_layoff_notices). It also explains the conditional behavior of the two parameters, telling the agent exactly how to get national vs. state-specific results.

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