compare_employment

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations: the area-type matching constraint and the specific return metrics (total jobs, industry mix, earnings, age breakdown). No contradictions found.

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: the first states the core purpose and scope, the second adds constraints and return summary. No fluff, front-loaded, every word earns its place.

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 purpose, constraints, and high-level return content. Combined with rich annotations and full schema coverage, it provides enough context for correct selection and invocation. The absence of an output schema is mitigated by listing expected metrics.

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 baseline is 3. The description adds minimal parameter-specific meaning beyond restating the geoid count (2-10) and area-type constraint already present in the schema. The return metrics mentioned are output-related, not parameter semantics.

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 compares employment data for multiple areas side by side, with a specific verb ('Compare') and resource ('employment data'). It distinguishes itself from sibling tools like get_employment (single area) and compare_demographics (different resource) by focusing on multi-area employment comparison.

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 clear usage context: use for comparing 2-10 areas and requires all geoids to share the same area type. It doesn't explicitly name alternatives or exclusion cases, but the use case is unambiguous.

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