calculate_french_salary

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

No annotations are provided, so the description must carry the burden. It lists the outputs (net salary, contributions, employer cost) which implies a read-only calculation. However, it does not explicitly state the side-effect-free nature or any potential limitations (e.g., accuracy assumptions, regional variations).

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 sentences efficiently capture purpose, inputs, outputs, and a pointer to related tools. No extraneous information. The structure is front-loaded with the core action and results.

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 presence of an output schema (implied by context signals) and full parameter coverage, the description is largely complete. It lists expected outputs and points to related calculators. Minor gaps: no mention of error handling or precision guarantees.

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 baseline is 3. The description does not add meaning beyond the schema: it repeats the parameter names and types but does not provide examples, ranges, or behavior for edge cases (e.g., negative salary, invalid status).

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 converts French gross salary to net salary for 2026, specifying three employment statuses. It mentions the outputs (monthly/annual net, social contributions, employer cost), and distinguishes itself from siblings by referencing related 'finance-france' calculators via list_bundles.

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 does not provide explicit guidance on when to use this tool over alternatives, such as other salary converters or French tax calculators. It only hints at related tools via 'list_bundles', but lacks when-not-to-use or prerequisite information.

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