youth_unemployment

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

With no annotations, the description carries the burden of behavioral disclosure. It clearly states what the tool returns (rate, gap, trend) and cites the source (ABS Labour Force), implying a read-only data retrieval. However, it doesn't specify units (e.g., percentage points) or whether the rate is seasonally adjusted, leaving minor gaps.

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 two sentences long, front-loaded with the main payload, and every word contributes. It avoids unnecessary detail while providing both what and when. No redundancy or 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, single-value tool, the description fully covers the essential information: what the tool returns, the context for using it, and the data source. No output schema exists, but the description sufficiently conveys expectations for a simple indicator.

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 has zero parameters, so the input schema is empty. The description doesn't need to explain any parameter semantics; it's clear that no arguments are required. Baseline 4 is appropriate as there is nothing to document.

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 ('Get') and clearly identifies the resource: the current AU youth (15-24) unemployment rate compared to the overall rate, including the gap and trend. This distinguishes it from sibling tools like real_wages or gender_pay_context, which target other indicators.

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 second sentence explicitly states when to use this tool: when asked 'how bad is youth unemployment in Australia?' or when comparing youth labour market conditions to the broader workforce. This is clear usage guidance with concrete trigger phrases.

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