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memorise8

law-search-mcp

by memorise8

get_precedent_detail

Retrieve full details of a Korean Supreme Court precedent by its serial number, including judgment text, key issues, and references.

Instructions

판례일련번호(precSeq)로 특정 판례의 상세 내용을 조회합니다.

law.go.kr 공식 Open API를 통해 판례 상세 정보를 반환합니다.
판례일련번호는 search_precedents() 검색 결과에서 확인할 수 있습니다.

반환 정보:
- 사건명, 사건번호, 선고일자, 법원 정보
- 판시사항: 법원이 판단한 주요 법률 쟁점
- 판결요지: 판결의 핵심 내용 요약 (없을 수 있음)
- 참조조문: 관련 법령 조문
- 참조판례: 관련 선례 판례
- 판례내용: 판결문 전문

Parameters:
    precedent_id: 판례일련번호 (예: "225429"). search_precedents()로 조회한 번호를 사용합니다.

Returns:
    판례의 상세 정보 (판시사항, 판결요지, 판례내용 등 가용한 모든 섹션 포함)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
precedent_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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 mentions the official API source, lists return sections (including possibility that some may be missing), and implies read-only behavior. It does not disclose rate limits or authentication, but for a read-only detail retrieval tool, this is adequate.

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?

The description is well-structured: a clear purpose sentence, followed by data source, prerequisite (search), return sections, and parameter details. Every sentence serves a purpose, and the most important information is front-loaded.

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 tool with one parameter, no enums, and an output schema, the description provides complete context: how to invoke, what to expect as input and output, and the relationship to its sibling tool. It even notes potential absence of certain return fields.

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?

With 0% schema description coverage, the description compensates by explaining the parameter in detail: its meaning ('판례일련번호'), an example value, and how to obtain it ('search_precedents()로 조회한 번호를 사용합니다'). This adds significant value beyond the bare 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 the verb ('조회합니다' - retrieve), the resource ('특정 판례의 상세 내용' - specific precedent details), and the key parameter (판례일련번호/precedent_id). It also distinguishes from the sibling tool search_precedents by noting that the ID comes from search results.

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 specifies when to use the tool: when a precedent_id is available from search_precedents() results. It explains what it returns but does not explicitly mention when not to use it or provide alternative usage scenarios, though the context with the sibling is clear.

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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