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

Annotations already establish readOnly/idempotent/non-destructive, so the bar is lower, and the description adds genuinely new context: the upstream data source and the privacy exclusion ('contact people named in the filings are left out'). It stops short of noting coverage limits such as which years of filings are included.

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?

Front-loaded with the resource and the source, and every sentence carries content. It is somewhat dense and restates 'What a US employer offered' twice, a minor redundancy rather than waste.

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?

With no output schema, the description usefully enumerates the return shape (filing counts, median, typical range, most common job titles with median wage). Combined with the source and privacy notes, an agent has enough to call and interpret the 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 100% and both parameters carry their own descriptions, so the baseline is 3. The description's only parameter-relevant content is echoing example employer names already implied by the schema, adding little.

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 opens with a specific resource (wages offered on US work visa filings) and names the exact data source (DOL disclosure data for H-1B, H-1B1, E-3 LCAs). It clearly distinguishes itself from a generic salary tool like check_salary by tying scope to visa filings.

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 embedded example queries ('what does Google pay software engineers?', 'how much does Infosys pay on H-1B?') give strong context for when to invoke it. However, it never contrasts with siblings like check_salary or check_visa_sponsor, so the agent must infer when this is preferable to those.

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