列出可用年度
list_yearsRead-onlyIdempotent
列出目前支援的年度、資料版本與基本工資（月薪/時薪）。計算前可先用本工具確認有效的 year 值。
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| years | Yes |
台灣勞健保勞退試算
TDQS
A4.5/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare it read-only and non-destructive. The description adds context about the specific data returned (wage details) and its role in validation, complementing the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: the first lists outputs, the second provides usage guidance. No wasted words; front-loaded with core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool with no parameters and an output schema, the description fully covers what the tool does and when to use it. No gaps given the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the description correctly implies no input is needed. It references valid year values without introducing ambiguity, meeting the baseline for param-free tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool lists supported years, data versions, and basic wages. It distinguishes itself from sibling calculation tools by indicating its purpose as a preparatory step.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises using this tool before calculations to confirm valid year values, providing clear context for when to use it. Since all siblings are calculation tools, no explicit exclusions are necessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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TDQS
A4.3/5.0
Disambiguation5/5
Each tool targets a distinct calculation scenario (e.g., payroll, pension types, supplementary premiums, income tax) with no functional overlap. The descriptions clearly differentiate their purposes.
Naming Consistency5/5
All tools follow a consistent 'calculate_' prefix for computational tools and 'list_years' for enumeration, using snake_case throughout. The verb_noun pattern is uniform.
Tool Count5/5
9 tools cover the core aspects of Taiwan's labor insurance, health insurance, pension, and tax calculations without redundancy. The count is well-matched to the domain's complexity.
Completeness5/5
The set includes all major calculations required for payroll and benefits: employer/employee burdens, multiple pension options, supplementary premiums, tax withholding, prorated scenarios, and a year reference tool. No obvious gaps.