Public Sector Employment Tool

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

Annotations already convey readOnly, destructive, idempotent, and openWorld hints. The description adds valuable behavioral context: data source, year range (2017-present), and supported government types. This adds clarity 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 a focused 4-sentence paragraph that front-loads the purpose and efficiently covers data types, filtering, and availability. No superfluous content; every sentence 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?

The description covers data scope, filtering, and time range. It lacks details on output structure (since no output schema), which is a minor gap. However, for a read-only tool with well-documented inputs, it is nearly complete.

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%, so the schema already describes parameters thoroughly. The description adds an overview and common variable examples but does not significantly enhance understanding beyond the schema. Baseline 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 retrieves government employment and payroll statistics from the Annual Survey of Public Employment & Payroll, specifying the data types (full-time/part-time, hours, payroll) and filtering options. It distinguishes itself from siblings by naming the exact survey and focusing on public sector 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 context for typical use (public employment data) but does not explicitly contrast with sibling tools or explain when to avoid using it. No alternatives are mentioned, leaving the agent to infer use cases from the survey name.

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