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

With no annotations, the description carries the full burden and does a strong job: it distinguishes maternity vs childcare rules, discloses the 14-day rule, explains bonus premium exemption conditions, and highlights two counterintuitive edge cases. The main gap is that it never states what the tool returns—whether it outputs exempt months, booleans, or premium types—and it does not address how leaves spanning October 2022 are handled.

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?

Four dense sentences pack the key distinctions, the 14-day rule, bonus conditions, and two high-value edge cases with no filler. The structure front-loads the core contrast and then lists the counterintuitive results, making it easy to absorb, though it is slightly longer than strictly necessary.

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?

For a complex regulatory topic with no output schema and no annotations, the description covers the main rules and gotchas well, which is valuable. However, it omits the return value shape, does not explain how to interpret results, and ignores the 'worked_days' parameter, leaving an agent to guess about the tool's output and optional inputs.

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 baseline is 3; the description adds real meaning for 'kind' by contrasting maternity vs childcare behavior and for 'start'/'end' by describing edge cases like a single day on the last day of a month. It does not mention 'worked_days' at all, but the schema already documents that parameter clearly, so the description still adds net value.

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 title '産休・育休の保険料免除月' and tool name 'check_leave_exemption' clearly indicate the tool checks insurance premium exemption months for maternity/childcare leave, and the description reinforces this by explaining the rules that govern those exemptions. However, the description never explicitly states 'returns the exempt months' or 'checks eligibility', relying on inference from the name and title. It also does not differentiate the tool from its siblings like check_insurance_eligibility.

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 implies this tool is used when determining insurance premium exemptions for maternity/childcare leave, and it explicitly warns that employment insurance is never exempt, giving a clear boundary. It does not name any alternative tools or state when to prefer them, and the usage context is only implied through the rule explanations rather than direct guidance.

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