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legal_analysis

Read-onlyIdempotent

Verify legal citations against Korean statutes, check precedent validity by case number, identify laws applicable at a specific date, and map judicial references to a given article.

Instructions

Korean-law-mcp — [정밀분석] 검증·분석 4종 통합. mode: verify_citations=텍스트 속 조문 인용('민법 제750조' 등)이 실존하는지 법제처 DB 교차검증, LLM 환각 방지(text 필수) | cite_check=판례 생사 확인 — 사건번호로 후속 인용 역추적+변경·폐기 감지, 한국형 Citator(caseNumber 필수) | applicable_law=사건 시점에 시행되던 법령 버전+그 시점 조문+부칙 경과조치, 행위시법 판단(lawName+date 필수, jo 선택) | impact_map=한 조문을 인용한 판례·헌재·해석례·행심·조례 역방향 그래프+mermaid(lawName+jo 필수)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
joNo[impact_map 필수, applicable_law 선택] 조문 번호 (예: '제103조', '제10조의2')
dateNo[applicable_law 필수] 기준일 — 행위·계약·처분 시점 (예: '2023-05-10', '20230510')
modeYes분석 유형 (도구 설명의 mode 표 참조)
textNo[verify_citations 필수] 검증할 법률 텍스트 (LLM 답변/계약서 등 조문 인용 포함 문자열)
displayNo[cite_check] 후속 인용 판례 최대 표시 수 (기본 20)
lawNameNo[applicable_law·impact_map 필수] 법령명 (예: '민법', '도로교통법')
deepScanNo[cite_check] 후속 인용 상위 판례 본문 정밀 스캔 (기본 true, false면 빠르지만 변경·폐기 감지 생략)
caseNumberNo[cite_check 필수] 사건번호 (예: '2013다61381', 문장 포함 가능)
maxCitationsNo[verify_citations] 검증할 최대 인용 개수 (기본 15, 많을수록 느림)
includeMermaidNo[impact_map] mermaid 그래프 코드 출력 (기본 true)
includeOrdinancesNo[impact_map] 자치법규 인용 검색 포함 (기본 true, false면 전국 조례 팬아웃 생략)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv4.9.1

TDQS

A4/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds significant behavioral context: it accesses external databases (법제처 DB), performs cross-validation, reverse-tracks citations, and generates graphs. No contradiction is present.

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 dense but well-structured: it leads with the tool identity, then a compact table of modes with roles and required fields. Every sentence adds value, though it could benefit from line breaks for readability.

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?

Given the tool's complexity (4 modes, 11 parameters, no output schema), the description covers mode definitions and required parameters but leaves output format largely unspecified. For example, verify_citations returns verification results but the structure is not described. Impact_map hints at mermaid output, others do not. Sufficient for basic use, incomplete for full invocation.

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?

Schema coverage is 100%, so baseline is 3. The description adds cross-reference tables linking each mode to required/optional parameters (e.g., 'mode=verify_citations: text 필수'), clarifying conditional requirements beyond schema descriptions. This helps the agent understand parameter dependencies.

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 is an integrated analysis tool ('검증·분석 4종 통합') and enumerates four specific modes (verify_citations, cite_check, applicable_law, impact_map) with distinct purposes. This differentiates it from sibling tools which are primarily search/retrieval focused.

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 does not explicitly contrast this tool with siblings. Each mode is described with its use case (e.g., 'LLM 환각 방지' for verify_citations), implying when it should be used, but without direct comparison to alternatives like search_law or get_law_text.

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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