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기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/ThomasMoreAI/legal-skills-open --skill legal-research-guide명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Use when retrieving arbitration institutional rules (ICC, LCIA, SCC, SIAC, HKIAC, VIAC, МКАС/МАК при ТПП України, UNCITRAL) — fetching current version, verifying redaction applicable to the date of arbitration agreement, constructing URLs for official rule texts
Use when choosing the Polish legal regime for letters, requests, applications, complaints, petitions, public-information requests, KPA filings, PPSA complaints, RODO access requests, registry extracts, court-file access, tax/ZUS/cudzoziemcy/USC procedures, or professional lawyer letters. Prevents mixing UDIP, KPA, PPSA, RODO, registry, special-procedure, and advocate/radca letter regimes.
Use when preparing applications for recognition and enforcement of foreign arbitral awards in Poland, applications for setting aside arbitral awards under KPC art. 1205–1211, or opposing such applications — mapping Article V of the 1958 New York Convention to art. 1214–1215 of the Polish KPC, identifying grounds for refusal, structuring public policy arguments
SOC 직업 분류 기준
SKILL.md 표시 중
| name | legal-research-guide |
| title | Legal Research Guide |
| description | Legal research methods, case law analysis, and compliance tools |
| author | wentorai |
| author_url | https://github.com/wentorai/research-plugins/tree/main/skills/domains/law/legal-research-guide |
| license | MIT |
| version | 0.1.0 |
| execution_mode | open |
| jurisdiction | general |
| practice | general |
| language | en |
Conduct systematic legal research across jurisdictions, analyze case law, navigate statutory frameworks, and use computational legal tools for academic and practice-oriented research.
The standard analytical framework for legal reasoning:
| Step | Description | Example |
|---|---|---|
| Issue | Identify the legal question | "Does web scraping of public data constitute a CFAA violation?" |
| Rule | State the applicable legal rule | "The CFAA prohibits accessing a computer 'without authorization' or 'exceeding authorized access'" |
| Application | Apply the rule to the facts | "In hiQ v. LinkedIn, the 9th Circuit held that scraping publicly available data does not violate the CFAA..." |
| Conclusion | State the legal conclusion | "Therefore, scraping publicly available academic data likely does not violate the CFAA, though terms-of-service issues remain." |
C - Conclusion (state your thesis)
R - Rule (present the legal rule with authority)
E - Explanation (analyze how courts have interpreted the rule)
A - Application (apply the rule to your specific scenario)
C - Conclusion (restate and refine conclusion)
| Database | Coverage | Cost | Best For |
|---|---|---|---|
| Westlaw (Thomson Reuters) | US, UK, EU, international | Subscription | Comprehensive case law, KeyCite citator |
| LexisNexis | US, UK, international | Subscription | News integration, Shepard's citator |
| Google Scholar (Case Law) | US federal and state courts | Free | Quick case lookup, citation tracking |
| Casetext / CoCounsel | US courts | Subscription | AI-powered legal research |
| CourtListener | US federal courts | Free | PACER alternative, bulk data |
| EUR-Lex | EU law |
| Free |
| EU legislation, CJEU case law |
| BAILII | UK, Ireland | Free | UK case law and legislation |
| Justia | US law | Free | US case law, statutes, regulations |
| HeinOnline | Historical legal materials | Subscription | Law journals, treaties, legislative history |
| Source | Content | Use |
|---|---|---|
| Law reviews / journals | Scholarly analysis | Academic research, policy arguments |
| Restatements | ALI compilations of common law | Authoritative secondary source |
| Treatises | Comprehensive subject coverage | Deep dive into specific areas |
| Legal encyclopedias (AmJur, CJS) | Broad legal summaries | Starting point for unfamiliar areas |
| Practice guides | Practical how-to | Practitioner-oriented research |
# Case citation
Marbury v. Madison, 5 U.S. (1 Cranch) 137 (1803).
Brown v. Board of Education, 347 U.S. 483, 495 (1954).
# Statute citation
42 U.S.C. Section 1983 (2018).
Cal. Civ. Code Section 1798.100 (West 2020). # California statute
# Law review article
Jane Smith, The Future of AI Regulation, 120 Harv. L. Rev. 456 (2024).
# Book
Richard Posner, Economic Analysis of Law 25 (9th ed. 2014).
# Short form citations (after first full citation)
Brown, 347 U.S. at 495.
Smith, supra note 12, at 460.
Id. at 462. # Same source as immediately preceding citation
# Case citation
Donoghue v Stevenson [1932] AC 562 (HL).
R v Brown [1994] 1 AC 212, 237 (HL).
# Statute citation
Human Rights Act 1998, s 3.
Data Protection Act 2018, s 170(1).
# Journal article
Jane Smith, 'The Future of AI Regulation' (2024) 120 Modern Law Review 456.
# Book
Richard Posner, Economic Analysis of Law (9th edn, Aspen 2014) 25.
import requests
import json
# Using the CourtListener API (free, open-source)
BASE_URL = "https://www.courtlistener.com/api/rest/v3"
def search_opinions(query, court="scotus", page_size=20):
"""Search case opinions via CourtListener API."""
response = requests.get(
f"{BASE_URL}/search/",
params={
"q": query,
"type": "o", # opinions
"court": court,
"page_size": page_size,
"order_by": "score desc"
},
headers={"Authorization": "Token YOUR_API_TOKEN"}
)
results = response.json()
for case in results.get("results", []):
print(f"[{case.get('dateFiled', 'N/A')}] {case.get('caseName', 'N/A')}")
print(f" Court: {case.get('court', 'N/A')}")
print(f" Citation: {case.get('citation', ['N/A'])[0] if case.get('citation') else 'N/A'}")
print(f" URL: https://www.courtlistener.com{case.get('absolute_url', '')}")
return results
# Search for AI-related Supreme Court cases
results = search_opinions("artificial intelligence", court="scotus")
import networkx as nx
def build_citation_network(seed_case_ids, depth=2):
"""Build a citation network starting from seed cases."""
G = nx.DiGraph()
visited = set()
queue = [(cid, 0) for cid in seed_case_ids]
while queue:
case_id, level = queue.pop(0)
if case_id in visited or level > depth:
continue
visited.add(case_id)
# Get case metadata and citations
resp = requests.get(f"{BASE_URL}/opinions/{case_id}/",
headers={"Authorization": "Token YOUR_API_TOKEN"})
if resp.status_code != 200:
continue
case = resp.json()
case_name = case.get("case_name", f"Case {case_id}")
G.add_node(case_id, name=case_name, date=case.get("date_filed"))
# Get citing opinions (who cites this case)
for cited_id in case.get("opinions_cited", []):
G.add_edge(case_id, cited_id)
if level < depth:
queue.append((cited_id, level + 1))
return G
# Analyze: which cases are most cited (highest in-degree)?
# These are the most authoritative precedents
# Analyzing legislative text complexity
import re
from textstat import textstat
def analyze_statute(text):
"""Compute readability metrics for statutory text."""
return {
"flesch_reading_ease": textstat.flesch_reading_ease(text),
"flesch_kincaid_grade": textstat.flesch_kincaid_grade(text),
"gunning_fog": textstat.gunning_fog(text),
"word_count": textstat.lexicon_count(text),
"sentence_count": textstat.sentence_count(text),
"avg_sentence_length": textstat.avg_sentence_length(text),
"defined_terms": len(re.findall(r'"[A-Z][^"]*"', text)),
"cross_references": len(re.findall(r'[Ss]ection \d+', text))
}
# Example: Analyze a section of the GDPR
gdpr_article_5 = """
Personal data shall be processed lawfully, fairly and in a transparent
manner in relation to the data subject; collected for specified, explicit
and legitimate purposes and not further processed in a manner that is
incompatible with those purposes; adequate, relevant and limited to what
is necessary in relation to the purposes for which they are processed.
"""
print(analyze_statute(gdpr_article_5))
| Area | Key Topics | Interdisciplinary Connections |
|---|---|---|
| AI & Law | Algorithmic fairness, liability for autonomous systems, AI regulation | CS, philosophy |
| IP Law | Patent, copyright, trade secret, open source licensing | Engineering, business |
| Privacy Law | GDPR, CCPA, surveillance, data protection | CS, political science |
| Law & Economics | Efficiency analysis of legal rules, behavioral law & economics | Economics |
| Comparative Law | Cross-jurisdictional analysis, legal transplants | Political science |
| International Law | Treaties, humanitarian law, trade law | International relations |
| Environmental Law | Climate litigation, ESG regulation, environmental justice | Environmental science |
| Health Law | Clinical trial regulation, health data, bioethics | Medicine, public health |
| Journal | Rank | Focus |
|---|---|---|
| Harvard Law Review | T1 | General |
| Yale Law Journal | T1 | General |
| Stanford Law Review | T1 | General, tech law |
| Columbia Law Review | T1 | General |
| Journal of Legal Studies | T1 | Law & economics |
| Journal of Empirical Legal Studies | T1 | Empirical methods |
| Computer Law & Security Review | Field | Technology law |
| Berkeley Technology Law Journal | Field | Tech, IP |