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

With no annotations provided, the description carries the full behavioral burden. It discloses that health rates differ by prefecture and change each March, pension is national, employment insurance changes each April, FY2025 and FY2026 are held, and an out-of-coverage date returns out_of_coverage rather than a guess. The March crossover nuance is especially valuable.

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 one dense sentence that front-loads the full list of outputs before explaining timing and parameter conditions. Every clause contributes a distinct fact, and while it is long, the complexity of the rate-year interactions justifies the length.

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 that no output schema exists, the description thoroughly covers the query space: available rates, prefecture dependence, national pension, employment-insurance bands, as_of fiscal-year behavior, and the March mismatch. The only notable gap is that it does not describe the exact response structure or field names.

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 meaningful context beyond the schema: business_type triggers employment insurance rates, as_of selects the in-force rate on that date, and the fiscal-year timing interplay between health and employment insurance is clarified. This is more than the schema provides alone.

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 enumerates what the tool returns: health insurance, long-term care, pension, child-support rates, bonus caps, and the employer-only child-care contribution. It is specific about scope and distinguishes this from obvious siblings like get_minimum_wage or list_workers_compensation_rates, though it does not explicitly name alternatives.

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 gives concrete usage guidance: add business_type for employment insurance rates, pass as_of to select the rate in force on a date, and be aware of the March crossover between health and employment insurance years. It does not explicitly state when not to use this tool or name alternative tools, but the parameter-driven conditions are clearly explained.

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