Skip to main content
Glama

legal_analysis

Read-onlyIdempotent

Verify legal citations, check precedent validity, determine applicable law at a given date, and map legal impacts using Korean national law databases.

Instructions

Korean-law-mcp — [정밀분석] 검증·분석 4종 통합. mode: verify_citations=텍스트 속 법령 조문·판례 인용('민법 제750조', '대법원 2013다61381' 등)이 실존하는지 법제처 DB 교차검증, LLM 환각 방지 — 판례는 실존불가/미확인 구분(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, jo는 '제103조'·'103조'·JO 6자리 코드 '010300' 모두 수용)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
joNo[impact_map 필수, applicable_law 선택] 조문 번호 — 자연어 표기('제103조', '제10조의2')와 6자리 JO 코드('010300', '001002') 모두 수용
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)
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds valuable behavior beyond that: DB cross-verification against the Ministry of Legislation, distinction between impossible and unconfirmed cases, change/repeal detection for case citations, temporal statute versioning, and mermaid graph output.

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 dense but well-organized: it front-loads the tool's general purpose, then uses separators to define each mode with its required inputs. Every segment carries load-bearing information; there is no filler.

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?

Despite having no output schema, the description explains what each mode produces: verified/existence classification, subsequent-case tracing with change/repeal detection, applicable law version with transitional provisions, and reverse citation graph with mermaid code. Together with the fully described 11-parameter schema, this gives an agent enough context to call the tool correctly.

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 the baseline is 3. The description adds meaningful conditional mapping that the schema does not: which parameters are mandatory per mode, how the jo parameter accepts both natural-language phrases and 6-digit codes, and what each mode requires. This is real added value over the schema alone.

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 is explicit and specific: it identifies legal_analysis as an integrated verification/analysis tool with four concrete modes (verify_citations, cite_check, applicable_law, impact_map), each naming its target resource and output. It is clearly distinguishable from sibling search/get/retrieval tools.

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?

Each mode gives a scenario and the required parameters — e.g., verify_citations for existing legal citations in text, cite_check for case-viability, applicable_law for version-at-the-time analysis, and impact_map for reverse citation graphs. What prevents a 5 is that it never explicitly names the sibling alternatives or states when not to use them.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/yunsy84/law_mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server