rank_minimum_wages

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

Annotations already cover read-only, idempotent, and non-destructive behavior, so the bar for additional disclosure is lower. The description adds that the national weighted average is included and specifies the ordering ('cheapest first'), which is useful. However, the phrase 'plus most expensive' is ambiguous—it could mean the ranking includes both ends or simply that the most expensive is at the end. No contradiction with annotations, but the behavioral disclosure is minimal and slightly unclear.

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 compact and front-loaded with the core purpose, followed by use cases and a note about the national average. No redundant sentences; every line earns its place. It is well-structured for quick agent parsing.

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's simplicity (one optional parameter, output schema present), the description covers the essential aspects: what it ranks, ordering, and the inclusion of the national average. It does not explicitly describe the output format, but the output schema handles that. It could mention limit behavior explicitly, but the schema already does. Overall complete enough for an agent to call correctly.

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%, with a single parameter 'limit' fully described in the schema (default, max, purpose). The description adds no additional parameter semantics, which is acceptable given the high coverage. Baseline of 3 applies.

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: ranking Japan's 47 prefectures by current minimum wage, with an explicit ordering ('cheapest first') and inclusion of the most expensive. This is a specific verb+resource that distinguishes it from sibling tools like get_minimum_wage (single lookup), get_minimum_wage_history (historical data), and list_prefectures (just listing). No ambiguity.

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 provides clear use cases ('cost-of-labor comparisons, relocation planning, and HR budgeting') that signal when this tool is appropriate. However, it does not explicitly contrast with sibling tools or state when not to use it. The context is helpful but lacks explicit exclusions or alternative routing.

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