bls_cpi_breakdown

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

Annotations already declare readOnlyHint=true, so the bar is lower. The description adds context about component breakdowns and identifying inflation drivers, but doesn't disclose other behavioral traits such as data frequency, geographic scope, or response format.

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?

Two concise sentences with a clear front-loaded action and resource. The dash and examples add useful detail without fluff, making it highly efficient.

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 simple read-only lookup with two well-documented parameters and no output schema, the description sufficiently conveys what the tool does and its purpose. It lacks explicit output format details but is adequate for selection and invocation.

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 provides 100% coverage of both parameters (start_year and end_year) with descriptions and defaults. The tool description adds no additional parameter semantics beyond what the schema already specifies.

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?

Clearly states it gets a breakdown of Consumer Price Index by component, listing specific categories (food, shelter, energy, etc.). This distinguishes it from generic BLS sibling tools like bls_series_data, though it doesn't explicitly name 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?

Implies usage when component-level CPI detail is needed ('Shows which categories are driving inflation'), but provides no explicit when-to-use vs alternatives, nor any exclusion criteria.

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