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oldbear-meme

mcp-taiwan-legal-db-integrated

by oldbear-meme

search_interpretations

Search Taiwan's constitutional interpretations by keyword, year, or case number. Retrieve decisions from both old and new systems to find relevant legal precedents.

Instructions

列舉大法官解釋 / 憲法法庭裁判。支援關鍵字全文搜尋(搜爭點 + 理由書)。

每筆結果帶 case_id,可直接傳給 get_interpretation()。

Args: keyword: 關鍵字(標題/字號/爭點/理由書全文匹配) year: 篩選民國年度(0=不篩選,>0 只回新制憲判字) number_from: 起始號次(含),0=不篩選 number_to: 截止號次(含),0=不篩選 include_old: 包含舊制釋字(year=0 時才生效) include_new: 包含新制憲判字 max_results: 回傳筆數上限(預設 30)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordNo
yearNo
number_fromNo
number_toNo
include_oldNo
include_newNo
max_resultsNo
Behavior3/5

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

No annotations exist, so the description carries full burden. It discloses that keyword search covers '爭點 + 理由書', and explains parameter behaviors (e.g., year=0 applies to old system). However, it does not mention side effects, authentication, rate limits, or explicitly state read-only nature, which is acceptable for a search tool but leaves some ambiguity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a short introductory sentence followed by a parameter list. It is slightly verbose due to parameter explanations, but every sentence adds value. Could be more concise by integrating parameter notes into a single paragraph.

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?

The tool has 7 parameters and no output schema. The description explains parameters well but lacks details on return format (e.g., fields beyond case_id, pagination, sorting). It assumes output structure without specifying, leaving some gaps for an agent to infer.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% parameter description coverage, so the description fully compensates by explaining each of the 7 parameters with conditions (e.g., 'include_old only effective when year=0'). This adds essential meaning beyond the schema's default values and titles.

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 the tool enumerates (列舉) interpretations/constitutional court decisions and supports full-text keyword search across issues and reasoning. It specifies the resource (大法官解釋/憲法法庭裁判) and action (搜尋), distinguishing it from sibling 'get' tools like get_interpretation.

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 explains that results include 'case_id' for direct use with get_interpretation(), and details each parameter's effect (e.g., year filtering, max_results). It does not explicitly state when not to use or alternative tools, but the context of siblings implies appropriate usage.

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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