skills/43-wentorai-research-plugins/skills/domains/law/legal-agent-skills-guide/SKILL.md
Agent skills collection for legal research and automation
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research legal-agent-skills-guideInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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A curated collection of agent skills for legal research and automation — contract analysis, case law search, regulatory compliance checking, legal document drafting, and citation verification. Each skill provides structured capabilities that AI agents can use to assist with legal workflows. Designed for legal researchers, law firms, and compliance teams.
Legal Agent Skills
├── Research Skills
│ ├── Case law search (by jurisdiction, topic)
│ ├── Statute lookup (federal, state, international)
│ ├── Legal commentary search
│ └── Regulatory tracking
├── Analysis Skills
│ ├── Contract clause extraction
│ ├── Risk assessment
│ ├── Compliance checking
│ └── Legal argument analysis
├── Drafting Skills
│ ├── Contract drafting
│ ├── Legal memo writing
│ ├── Motion drafting
│ └── Compliance reports
├── Citation Skills
│ ├── Bluebook formatting
│ ├── Citation verification
│ ├── Shepard's-style validation
│ └── Cross-reference linking
└── Practice Management
├── Case timeline construction
├── Discovery document review
├── Deposition summary
└── Billing narrative generation
# Search case law databases
from legal_skills import CaseLawSearch
search = CaseLawSearch(jurisdictions=["federal", "california"])
cases = search.find(
query="AI liability product defect",
date_range=("2020-01-01", "2025-12-31"),
court_level="appellate",
max_results=20,
)
for case in cases:
print(f"{case.name} ({case.year})")
print(f" Court: {case.court}")
print(f" Key holding: {case.holding[:100]}...")
print(f" Citation: {case.citation}")
from legal_skills import ContractAnalyzer
analyzer = ContractAnalyzer()
# Analyze contract
analysis = analyzer.analyze("contract.pdf")
print("Risk Assessment:")
for risk in analysis.risks:
print(f" [{risk.severity}] {risk.clause}: {risk.description}")
print("\nKey Terms:")
for term in analysis.key_terms:
print(f" {term.name}: {term.value}")
print("\nMissing Clauses:")
for missing in analysis.missing_clauses:
print(f" - {missing}")
from legal_skills import BluebookFormatter
formatter = BluebookFormatter()
# Format citation
citation = formatter.format(
case_name="Brown v. Board of Education",
volume=347,
reporter="U.S.",
page=483,
year=1954,
)
print(citation)
# Brown v. Board of Education, 347 U.S. 483 (1954).
# Verify citation
valid = formatter.verify("347 U.S. 483")
print(f"Valid: {valid.is_valid}, Case: {valid.case_name}")
development
Conduct rigorous thematic analysis (TA) of qualitative data following Braun and Clarke's (2006) six-phase framework. Use whenever the user mentions 'thematic analysis', 'TA', 'Braun and Clarke', 'qualitative coding', 'identifying themes', or asks for help analysing interviews, focus groups, open-ended survey responses, or transcripts to identify patterns. Also trigger for questions about inductive vs theoretical coding, semantic vs latent themes, essentialist vs constructionist epistemology, building a thematic map, or writing up a qualitative findings section. Covers all six phases, the four upfront analytic decisions, the 15-point quality checklist, and the five common pitfalls. Produces a Word document write-up and an annotated thematic map. Does NOT cover IPA, grounded theory, discourse analysis, conversation analysis, or narrative analysis — use a different method for those.
development
Guide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.
testing
Performs placebo-in-time sensitivity analysis with hierarchical null model and optional Bayesian assurance. Use when checking model robustness, verifying lack of pre-intervention effects, or estimating study power.
data-ai
Fit, summarize, plot, and interpret a chosen CausalPy experiment. Use after the causal method has been selected, including when configuring PyMC/sklearn models and scale-aware custom priors.