payroll.kr_minimum_wage_check

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

Annotations already establish readOnly/idempotent/closed-world, and the description goes well beyond them: it discloses the 209-hour conversion basis, the exclusion ratio for bonuses and cash welfare (0% since 2024), the three-condition probation reduction, precise-value comparison, and round-up of the shortfall. It does not disclose behavior of the less obvious switches (e.g. include_proposed, as_of), leaving a small gap.

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?

Purpose is front-loaded in the first clause, and the subsequent sentences each add a distinct rule (conversion basis, inclusions/exclusions, rounding, scope limits) with little redundancy. It is dense but every sentence earns its place; a structured list of the calculation steps would have improved scanability.

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?

The output schema removes any need to describe return values, and the legal and arithmetic model is well covered. However, for a 14-parameter tool with zero schema documentation, roughly eight parameters remain unexplained, which is a material completeness gap even given the rich domain context provided.

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 0% across 14 parameters, so the description carries the full burden, yet it clarifies only a handful: wage_amount/wage_unit, monthly_bonus, monthly_welfare_cash and on_probation. Key inputs such as include_proposed, as_of, simple_labor_job, weekly_paid_hours, daily_contract_hours, weekly_contract_hours, monthly_standard_hours and contract_one_year_or_more are never mentioned, so an agent cannot infer their meaning or units.

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 verb and resource ('한국 최저임금 충족 여부를 검토한다') with the governing legal basis (최저임금법 제5조·제6조, 시행령 제5조). No sibling in the payroll.* family performs a minimum-wage compliance check, so the resource is unambiguous on its own.

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?

Explicitly excludes scopes ('도급제, 택시 운전, 적용 제외 인가는 다루지 않는다') and enumerates what wage components are in and out of the calculation, which effectively tells the agent when this tool does and does not apply. It stops short of naming a sibling alternative for the excluded cases, so it is not a full when/when-not/alternative statement.

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