比例付与日数の計算

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

No annotations are provided, so the description carries the full burden. It states 'calculates', implying a read-only operation, but does not explicitly confirm non-destructive behavior or disclose any side effects, prerequisites, or error conditions. For a calculation tool, this is adequate but could be more explicit.

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 a single, tightly phrased sentence in Japanese that directly conveys the tool's purpose. Every word is meaningful, and the structure is front-loaded with the core action ('calculates proportional entitlement days'). No redundancies.

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 complexity (5 parameters, no output schema), the description is brief. It does not explain the output (presumably days) or the relationships between parameters (e.g., mutual exclusion of weekly/annual days). Although the schema covers these details, the description could improve completeness by summarizing key inputs and output behavior.

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 value by framing the calculation within Japanese labor law ('statutory minimum standards') and hinting at the primary parameters (weekly or annual scheduled days). This context helps an AI agent understand the legal significance, extending beyond the schema's technical descriptions.

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 action: it calculates proportional entitlement days for annual paid leave for part-time workers based on statutory minimum standards. It uses specific verbs ('calculates') and resources ('proportional entitlement days'), and distinguishes itself from siblings like 'calculate_entitlement' by specifying 'proportional' and 'statutory minimum'.

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 the tool is for calculating proportional leave for part-time employees, but it does not explicitly state when to use this tool versus siblings like 'calculate_entitlement' or 'check_attendance_rate'. No alternatives or exclusions are mentioned, leaving the agent to infer usage context.

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