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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the agent knows this is a safe, repeatable, closed computation. The description adds the composition of the computation and that results are ranked, but omits anything further about behavior beyond what the annotations and the existing output schema already convey.

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 efficiently packed sentences that front-load the core computation before the example use cases. Every clause earns its place, though the enumerated output list is somewhat dense.

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, full annotation coverage and 100% schema description coverage, the description only needs to orient the agent, which it does. It is complete enough, though it could have noted the ranking/sort behavior relationship to the sort_by parameter more explicitly.

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 description coverage is 100%, so the schema already documents all six parameters including defaults, enums and bounds. The description only restates that hourly wage and weekly hours drive the comparison, adding no syntax, format or constraint detail beyond the schema; baseline 3 is appropriate.

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?

States a specific action (compute the same wage/hours across all 26 cantons) and enumerates the computed outputs (monthly employer cost, net wage, family allowance fund rate, admin fee, minimum wage, ranked). This clearly distinguishes it from the sibling estimate_employer_cost, which is a single-case estimator rather than a cross-canton 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?

Gives concrete triggering questions ('where is it cheapest', 'how much does the canton matter') and a use case (table for several cantons), which tells the agent when this tool applies. It stops short of explicitly naming an alternative sibling or stating when NOT to use it, so it does not reach a 5.

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