get_taiwan_interpretation取得釋字（第 1-813 號）或憲判字（111 年起）內容，來自官方公告文書的本地快照，即時回應。預設回傳字號/日期/爭點/解釋文等精簡層；理由書與意見書需 opt-in：優先用 reasoning_keyword / opinions_keyword 取關鍵字片段（省 token），確有需要才用 include_* 取全文（超過 15000 字會截斷並警告）。
| Name | Required | Description | Default |
|---|---|---|---|
| case_id | Yes | 字號，例如：釋字第748號、釋字748、111年憲判字第1號、111憲判1 | |
| include_opinions | No | 回傳意見書全文 | |
| opinions_keyword | No | 在意見書中搜尋關鍵字並回片段 | |
| include_reasoning | No | 回傳理由書全文 | |
| reasoning_keyword | No | 在理由書中搜尋關鍵字並回片段（優先於 include_reasoning） |
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 discloses data source (local snapshot of official documents), response default, opt-in behaviors, token-saving rationale, and a 15000-character truncation warning, offering substantial behavioral context beyond the schema.
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 two sentences that efficiently front-load purpose and then detail usage nuances. Every clause adds value—no filler or redundancy.
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?
Despite lacking an output schema, the description explains default response fields (字號/日期/爭點/解釋文), opt-in reasoning/opinions, and truncation warning. It covers the tool's full behavior adequately for an agent to use correctly.
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%, but the description adds critical semantics: the priority relationship between keyword and include parameters, why to prefer keywords (省 token), and full-text truncation behavior. This significantly enriches the bare schema 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 function: 取得釋字 or 憲判字 content, with specific scope (第 1-813 號, 111 年起) and resource type. It also lists default return fields, distinguishing it from sibling search/citation tools.
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 provides clear context: this is for direct retrieval of specific interpretations, with parameter-level usage guidance (prefer keyword snippets, use include_* only when necessary). However, it doesn't explicitly mention alternatives or exclusions relative to sibling tools like search_taiwan_interpretations or get_taiwan_interpretation_citations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.