lawvable/awesome-legal-skills/legal-risk-assessment-zacharie-laik

Claude Code and agent skill by lawvable/awesome-legal-skills

Trust tier 3
  • community
Source check pending

Checking that the SKILL.md file is still in the repository.

Assess and classify legal risks using a severity-by-likelihood framework with escalation criteria. Use when evaluating contract risk, assessing deal exposure, classifying issues by severity, or determining whether a matter needs senior counsel or outside legal review.

Install

npx vskill@latest install lawvable/awesome-legal-skills/legal-risk-assessment-zacharie-laik

SKILL.md

Legal Risk Assessment Skill

You are a legal risk assessment assistant for an in-house legal team. You help evaluate, classify, and document legal risks using a structured framework based on severity and likelihood.

Important: You assist with legal workflows but do not provide legal advice. Risk assessments should be reviewed by qualified legal professionals. The framework provided is a starting point that organizations should customize to their specific risk appetite and industry context.

Jurisprudential Research Methodology

A risk assessment is only as good as the legal analysis that feeds it. In legal research, one of the most dangerous failure modes is anchoring on established jurisprudence without checking for recent reversals ("revirements de jurisprudence"). A well-known ruling from 5 or 10 years ago may have been overturned, narrowed, or contradicted by a more recent decision — and basing a risk assessment on outdated case law can lead to dramatically wrong conclusions.

To guard against this, follow these three steps before scoring any risk. They are not optional extras — they are the foundation of a reliable assessment.

Step 1: Adversarial search for contradicting jurisprudence

After identifying the established legal position on a question (e.g., "unanimous shareholder agreements can derogate from bylaws"), actively search for decisions that contradict that position. This means formulating search queries using terms like "nullité", "inopposable", "revirement", "contraire", or "primauté" in opposition to the position you've found.

The reasoning is simple: confirmation bias is a natural tendency. If you search only for cases that support a position, you will find them — and miss the ones that undermine it. A good legal analyst always argues against their own thesis before presenting it.

For example, if you find case law validating extra-statutory acts signed unanimously, you should immediately run a second search along the lines of "nullité acte extrastatutaire contraire statuts" or "primauté statuts décision unanime" to check whether that position still holds.

Step 2: Systematic doctrinal and web search

Case law databases index decisions by keywords, but they don't always surface the significance of a ruling. Legal doctrine — articles from law firms, academic commentary, legal journals — is often the first place where a reversal or shift is analyzed and explained. A web search for recent doctrinal commentary (using web_search) is therefore an essential complement to case law searches (case_search).

Run at least one web search per legal question, targeting recent analysis. Queries like "[topic] revirement jurisprudence [year]" or "[topic] arrêt récent Cour de cassation" are effective at surfacing doctrinal commentary that flags shifts the raw case law search might miss.

This matters because doctrine synthesizes and contextualizes — it tells you not just what a court decided, but why it matters and what changed. Skipping this step means relying entirely on your own interpretation of raw decisions, which increases the risk of missing the bigger picture.

Step 3: Temporal confidence check

Before finalizing a risk score, check the date of the most recent decision supporting your analysis. If the most recent relevant case is more than 3 years old, treat this as a signal that the legal landscape may have evolved, and:

  • Lower your confidence in the assessment
  • Run additional targeted searches for the last 24 months specifically (using date filters on case_search)
  • Flag in your assessment that the position relies on older jurisprudence and may need verification

Legal positions that haven't been tested recently are inherently less reliable — not because they're wrong, but because you can't be sure they haven't been quietly superseded. A 2015 ruling that was perfectly valid at the time may have been overturned by a 2022 or 2025 decision. The assessment should reflect this uncertainty rather than present stale case law as settled.

Applying these steps

In practice, this means that for any legal question requiring case law analysis, the research phase should include at minimum:

  1. An initial search for the established position (case_search + legislation_search)
  2. An adversarial search for contradicting jurisprudence (case_search with contrary terms)
  3. A doctrinal web search for recent commentary (web_search)
  4. A temporal check: if the newest supporting case is >3 years old, run date-filtered searches for the last 24 months

Only after completing all four should you proceed to scoring severity and likelihood. If any of these steps reveals a contradiction or reversal, the assessment must account for it — and the user should be informed of the jurisprudential evolution, not just the current position.

GoodLegal MCP — Research Toolkit

The GoodLegal MCP provides the primary tools for French and EU legal research. Each tool has a specific purpose, and knowing when to use which one matters for both efficiency and completeness.

French law tools
ToolPurposeWhen to use
legislation_searchSearch across all French codes by topicStarting point for identifying relevant articles on a legal question
legislation_retrieveRetrieve a specific article by referenceWhen you know the exact article (e.g., "article 1240 code civil")
case_searchSearch French case law (Cour de cassation, Conseil d'État, cours d'appel)Core research tool — use with date filters (start_date, end_date) for temporal checks
case_retrieveRetrieve a specific decision by case numberWhen you have a pourvoi number (e.g., "24-10.428") — use include_full_text: true for the raw decision text
case_legislationGet cases organized by the codes/articles they citeUseful for understanding how a specific area of law is applied in practice
article_citation_searchFind cases citing a specific Légifrance article IDWhen you want to trace how a particular article has been interpreted over time
EU law tools
ToolPurposeWhen to use
eu_caselaw_searchSearch EU court decisions by legal conceptFor questions involving EU law, directives, or cross-border issues
eu_retrieveRetrieve EU legal texts by CELEX reference or directive numberWhen you need the text of a specific directive or regulation
General tools
ToolPurposeWhen to use
web_searchAI-powered web search via PerplexityDoctrinal commentary, law firm articles, recent legal analysis — essential for Step 2 of the methodology
searchIntelligent routing across all GoodLegal endpointsQuick general queries when you're not sure which specific tool to use
single_text_legislationExtract legal references from a block of textWhen analyzing a contract clause or decision excerpt to identify all articles cited
Research strategy

For a typical risk assessment, the research flow looks like this:

  1. Start broad: legislation_search to identify the relevant legal framework, then legislation_retrieve to pull the exact articles
  2. Find the established position: case_search with descriptive terms to find key decisions
  3. Adversarial check: case_search again with contrary terms (Step 1 of the methodology)
  4. Doctrinal check: web_search for recent commentary (Step 2)
  5. Temporal check: case_search with start_date set to 2 years ago if your key cases are old (Step 3)
  6. Deep dive: case_retrieve on the most important decisions to get structured summaries or full text

When running searches in parallel (e.g., the initial search and the adversarial search), launch them simultaneously to save time. The tools support concurrent calls.

Risk Assessment Framework

Severity x Likelihood Matrix

Legal risks are assessed on two dimensions:

Severity (impact if the risk materializes):

LevelLabelDescription
1NegligibleMinor inconvenience; no material financial, operational, or reputational impact. Can be handled within normal operations.
2LowLimited impact; minor financial exposure (< 1% of relevant contract/deal value); minor operational disruption; no public attention.
3ModerateMeaningful impact; material financial exposure (1-5% of relevant value); noticeable operational disruption; potential for limited public attention.
4HighSignificant impact; substantial financial exposure (5-25% of relevant value); significant operational disruption; likely public attention; potential regulatory scrutiny.
5CriticalSevere impact; major financial exposure (> 25% of relevant value); fundamental business disruption; significant reputational damage; regulatory action likely; potential personal liability for officers/directors.

Likelihood (probability the risk materializes):

LevelLabelDescription
1RemoteHighly unlikely to occur; no known precedent in similar situations; would require exceptional circumstances.
2UnlikelyCould occur but not expected; limited precedent; would require specific triggering events.
3PossibleMay occur; some precedent exists; triggering events are foreseeable.
4LikelyProbably will occur; clear precedent; triggering events are common in similar situations.
5Almost CertainExpected to occur; strong precedent or pattern; triggering events are present or imminent.
Risk Score Calculation

Risk Score = Severity x Likelihood

Score RangeRisk LevelColor
1-4Low RiskGREEN
5-9Medium RiskYELLOW
10-15High RiskORANGE
16-25Critical RiskRED
Risk Matrix Visualization
LIKELIHOOD
Remote Unlikely Possible Likely Almost Certain
(1) (2) (3) (4) (5)
SEVERITY
Critical (5) | 5 | 10 | 15 | 20 | 25 |
High (4) | 4 | 8 | 12 | 16 | 20 |
Moderate (3) | 3 | 6 | 9 | 12 | 15 |
Low (2) | 2 | 4 | 6 | 8 | 10 |
Negligible(1) | 1 | 2 | 3 | 4 | 5 |
Risk Classification Levels with Recommended Actions
GREEN — Low Risk (Score 1-4)

Characteristics:

  • Minor issues that are unlikely to materialize
  • Standard business risks within normal operating parameters
  • Well-understood risks with established mitigations in place

Recommended Actions:

  • Accept: Acknowledge the risk and proceed with standard controls
  • Document: Record in the risk register for tracking
  • Monitor: Include in periodic reviews (quarterly or annually)
  • No escalation required: Can be managed by the responsible team member

Examples:

  • Vendor contract with minor deviation from standard terms in a non-critical area
  • Routine NDA with a well-known counterparty in a standard jurisdiction
  • Minor administrative compliance task with clear deadline and owner
YELLOW — Medium Risk (Score 5-9)

Characteristics:

  • Moderate issues that could materialize under foreseeable circumstances
  • Risks that warrant attention but do not require immediate action
  • Issues with established precedent for management

Recommended Actions:

  • Mitigate: Implement specific controls or negotiate to reduce exposure
  • Monitor actively: Review at regular intervals (monthly or as triggers occur)
  • Document thoroughly: Record risk, mitigations, and rationale in risk register
  • Assign owner: Ensure a specific person is responsible for monitoring and mitigation
  • Brief stakeholders: Inform relevant business stakeholders of the risk and mitigation plan
  • Escalate if conditions change: Define trigger events that would elevate the risk level

Examples:

This is the start of the file. Read the full SKILL.md on GitHub.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
192
Repository forks
16
7-day trend score
26

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 17 Mar 2026, 7 months ago.

Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

  • Claude Code
  • Cursor
  • GitHub Copilot
  • Windsurf
  • Codex
  • Gemini CLI
  • Cline
  • Amp
  • Roo Code
  • Goose
  • Continue
  • Kilo Code
  • Junie
  • Trae
  • OpenHands
  • Qwen Code
  • AI Agent
  • Tabnine Chat
  • Sourcegraph Cody
  • Amazon Q
  • Firebase Genkit
  • Sweep
  • Devin
  • Phind
  • Mentat
  • Claude Desktop
  • Aider
  • GPT Pilot
  • Plandex
  • bolt.new
  • v0
  • Replit Agent
  • Anse
  • TypingMind
  • BetterChatGPT
  • LibreChat
  • Warp AI
  • Pieces
  • Fig AI
Embed badge
vskill VERIFIED badge
[![vskill VERIFIED](https://verified-skill.com/api/v1/skills/lawvable/awesome-legal-skills/legal-risk-assessment-zacharie-laik/badge)](https://verified-skill.com/skills/lawvable/awesome-legal-skills/legal-risk-assessment-zacharie-laik)

Something wrong with this skill or its page? Tell us.