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

The description adds substantial behavioral detail beyond the annotations: log-normal modeling, GNI/Gini calibration, null statutory minimum behavior, monthly/annual and USD/local currency outputs, and optional salary/percentile behaviors. This is rich context that would not be visible from annotations or schema alone, and it contradicts none of the annotations.

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 dense but purposeful, packing the model, output dimensions, and parameter behavior into one structured paragraph. All content earns its place, though the formula line is technical and slightly heavy for an agent that mainly needs to understand what the tool returns.

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 an output schema and rich annotations already present, the description covers the remaining essentials: model inputs, full band list, currency and period variants, optional parameter behavior, and data caveats. Nothing needed to call the tool correctly is missing.

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 parameters are already documented. The description adds useful interpretive detail, such as salary being located on the curve to yield percentile plus 'out-earns %' and percentile returning an exact threshold wage, which enhances parameter understanding beyond the schema.

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 what the tool does: it models a country's wage distribution and returns a specific set of salary bands (survival floor, statutory minimum, p50, p75, p90, p99), so purpose is unambiguous. It does not explicitly distinguish itself from a sibling like localize_salary, though the 'benchmark' framing and band output make the distinction reasonably clear.

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 gives a clear use boundary: results are 'model estimates for benchmarking, not payroll data,' which tells the agent where this tool is and is not appropriate. It does not name alternative tools or provide exhaustive when-to-use versus when-not-to-use guidance, so it stops short of full routing instructions.

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