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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable context: it names the data source (BLS Current Employment Statistics), coverage (650,000 US worksites), and notes the Fed uses the same data. It also gives an example of the returned metrics (MoM, YoY, trend). This exceeds the minimal annotation coverage.

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 single paragraph but well-structured: usage cases, output description, example, and source. It is somewhat lengthy but every sentence adds value, especially the example illustrating the output format. It is not overly verbose.

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?

There is no output schema, so the description covers the return values (employment, MoM, YoY, trend classification) and provides an example. It also gives source and use cases. For a one-parameter enum tool, this is largely complete, though it could clarify the exact response structure.

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 0%, and the description does not explain each enum value. However, it does mention 'major sector' and provides a healthcare example, adding partial meaning. The parameter is a simple enum of sector names, so the description partially compensates for the missing schema 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 clearly states it 'Returns BLS payroll employment by major sector with month-over-month change, year-over-year change, and trend classification.' It specifies the resource (BLS sector employment data) and distinguishes it from sibling tools by focusing on sector-specific labor market 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 opens with explicit use cases: 'benchmarking workforce planning against sector labor market conditions, assessing industry growth trajectory for strategic planning, providing economic context for board reporting, or evaluating talent acquisition timing.' It does not explicitly mention when not to use or alternatives, but provides clear context.

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