get_occupation_wages

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

With no annotations provided, the description discloses key behavioral details: it returns median plus 10th/25th/75th/90th percentiles and notes SOC format requirements. It does not mention side effects or error handling, but for a read-style data retrieval tool, this is sufficient.

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?

Four concise sentences each add unique value: purpose, SOC format, filters, and output details. No redundant or filler content.

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?

Given the tool has an output schema and moderate parameter count, the description covers the essential usage: SOC requirement, optional filters, and return content. It lacks explicit guidance on default behavior or parameter relationships, but is adequate for a data retrieval tool.

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%, so the description must compensate. It explains the SOC format with an example and lists optional filters (industry, geography, year) but does not differentiate between geo, metro, and state parameters, leaving some ambiguity.

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's function with a specific verb ('Get') and resource ('wage data for a BLS occupation'). It distinguishes from sibling tools like get_county_wages by focusing on occupation-level percentiles, and the SOC format example adds clarity.

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?

Provides clear context that this tool is for occupation wage data with optional industry/geography/year filters. However, it does not explicitly mention alternatives or exclusionary conditions, so it stops short of full usage guidance.

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