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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds useful provenance ('BLS data'), implying an authoritative external source and a monthly cadence, but says nothing about data lag, refresh timing, or return format. With annotations carrying the behavioral burden, this is a modest but real addition.

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?

A single front-loaded sentence that lists the payload first and the source last. Every clause earns its place by naming a distinct metric; there is no filler.

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-parameter read with no output schema, the description effectively enumerates the metrics the caller will receive, which compensates for the absent output schema. Annotations cover the safety profile. Only minor gaps remain (refresh cadence, units/seasons), so 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?

The tool takes zero parameters, so the baseline is 4, and schema coverage is 100% with an empty properties object. Nothing about argument semantics is left for the description to clarify.

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 states the exact resource (the US labor market) and enumerates the precise signals returned – nonfarm payrolls, unemployment rate, wage growth, JOLTS openings/quits, and participation. An agent can tell it apart from the finance/crypto siblings (equity_signal, smart_money, token_scan) purely by domain. It lacks a leading verb like 'retrieve', but the resource and contents are unambiguous.

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?

There is no when-to-use guidance, no statement of prerequisites, freshness, or the conditions that would select this over a sibling. The 'signal' framing implies retrieval for macro analysis, but that is inference, not guidance.

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