法規名稱轉 pcode
get_taiwan_pcode將法規名稱（含常見簡稱如勞基法、個資法）轉換為全國法規資料庫 pcode 代碼，支援模糊比對與建議。
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| law_name | Yes | 法規名稱，例如：民法、勞基法、消保法 |
taiwan-law
TDQS
A3.7/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses fuzzy matching and suggestions, but does not explain output format, error behavior, or exactly how suggestions are returned. For a simple conversion tool, this is minimal but not severely lacking.
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?
One sentence that is front-loaded and contains no redundant information. It immediately states the conversion purpose and includes useful examples without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool, the description covers the core purpose and fuzzy matching, but without an output schema, the return format is not explained, and usage guidance is missing. It is adequate but leaves gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema already describes the law_name parameter with examples. The description adds similar examples and mentions fuzzy matching, but does not add significant new parameter semantics beyond the schema.
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 clearly states a specific verb (轉換) and resource (法規名稱 to pcode), and distinguishes from siblings by focusing on pcode conversion rather than searching or retrieving laws. Examples of common abbreviations further clarify the scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a pcode is needed from a law name, but does not explicitly state when to use this tool over alternatives like search_taiwan_laws or get_taiwan_law_versions. There is no mention of exclusions or prerequisites.
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 legal source or action: laws, regulations, interpretations, judgments, MOJ documents, bills, legislative history, and intent analysis. Even similar tools like search_taiwan_laws vs search_taiwan_regulations are clearly separated by scope (full-text vs name-only) and descriptions provide sufficient boundary definitions.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with a domain prefix (taiwan or moj). The verbs are limited to get, search, and analyze, and the object nouns are unambiguous (e.g., interpretations, judgments, laws, regulations, bills). No mixed conventions or vague verbs.
Tool Count5/5
14 tools is well-scoped for a comprehensive Taiwan legal research server, covering search, retrieval, citation extraction, intent routing, and legislative tracking. Each tool has a clear purpose and the count is within the ideal 3-15 range.
Completeness5/5
The tool surface covers the full lifecycle of legal research: finding and retrieving laws, regulations, interpretations, judgments, and bills; obtaining legislative history and versions; converting law names to PCODEs; analyzing user intent; and even extracting citations. No obvious gaps that would block an agent's legal research workflow.