Agent skill

Legal Risk Assessment

by aAAaqwq in aAAaqwq/AGI-Super-Team

Structured legal risk assessment with 5x5 Severity x Likelihood matrix.

MITAuto-check passedLegal & Compliance

Install Legal Risk Assessment

skills CLI
$ npx skills add aAAaqwq/AGI-Super-Team --skill legal-risk-assessment -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aAAaqwq/AGI-Super-Team legal-risk-assessment --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/legal-risk-assessment .claude/skills/legal-risk-assessment && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
legal-risk-assessment
GitHub stars
105
Used in
1 other repo
Token cost
~2.6k tokens
SKILL.md length
842 words
Files
1
Skills in repo
167
Repo updated
First seen
Licence
MIT

At a glance

Structured legal risk assessment with 5x5 Severity x Likelihood matrix.

  • Escalation decisions
  • SKILL.md covers Table of Contents, Tools, Reference Guides and Workflows, plus 5 more sections
  • Calls python
  • Tasks that involve Legal risk assessment

What it does

Legal Risk Assessment is an agent skill from aAAaqwq/AGI-Super-Team. Structured legal risk assessment with 5x5 Severity x Likelihood matrix. Use for risk scoring, risk registers, escalation decisions, and risk memos.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Legal & Compliance, covering Legal risk assessment. The repository describes itself as: An installable, cross-framework AI organization: C-suite agents, expert subagents, curated skills, independent review, and one-command setup across 18 AI client/runtime adapters. The licence is MIT.

When your agent uses it

  • Escalation decisions
  • Tasks that involve Legal risk assessment

Example prompts

  • “/legal-risk-assessment”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 7cefd81. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Legal Risk Assessment loads about 2.6k tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 842 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~42
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from aAAaqwq/AGI-Super-Team at commit 7cefd81, republished under its MIT licence (© aAAaqwq). 842 words, ~2,641 tokens.

Download SKILL.mdSave it as .claude/skills/legal-risk-assessment/SKILL.md (or your agent's skills folder).
name
legal-risk-assessment
description
Structured legal risk assessment with 5x5 Severity x Likelihood matrix. Use for risk scoring, risk registers, escalation decisions, and risk memos.
license
MIT + Commons Clause
metadata.version
1.0.0
metadata.author
The Glass Room
metadata.category
legal
metadata.domain
risk-management
metadata.updated
2026-04-10
metadata.tags
legal-risk, risk-matrix, risk-register, escalation, compliance

⚠️ EXPERIMENTAL — This skill is provided for educational and informational purposes only. It does NOT constitute legal advice. All responsibility for usage rests with the user. Consult qualified legal professionals before acting on any output.

Structured legal risk assessment using a quantitative 5x5 Severity x Likelihood matrix. Scores risks, maintains registers, generates assessment memos, and guides escalation decisions.


Table of Contents


Tools

Risk Scorer

Calculates risk scores from severity and likelihood inputs, assigns color-coded risk levels, and generates summary statistics.

bash
# Score a single risk
python scripts/risk_scorer.py --severity 4 --likelihood 3 \
  --category "Contract" --description "Vendor SLA non-compliance"

# JSON output
python scripts/risk_scorer.py --severity 4 --likelihood 3 \
  --category "Contract" --description "Vendor SLA breach" --json

# Batch mode from risk register file
python scripts/risk_scorer.py --input risks.json --json

# Batch mode with human-readable output
python scripts/risk_scorer.py --input risks.json

Input JSON format (batch mode):

json
{
  "risks": [
    {"severity": 4, "likelihood": 3, "category": "Contract", "description": "Vendor SLA breach"},
    {"severity": 2, "likelihood": 2, "category": "Regulatory", "description": "Minor filing delay"}
  ]
}

Output includes:

  • Risk score (Severity x Likelihood)
  • Color-coded level (GREEN / YELLOW / ORANGE / RED)
  • Recommended action (Accept / Monitor / Mitigate / Escalate)
  • Batch summary statistics (count per level, average score)

Risk Report Generator

Generates a formatted risk assessment memo in markdown from a risk register JSON file.

bash
# Generate memo from risk register
python scripts/risk_report_generator.py --input risk_register.json

# Save to file
python scripts/risk_report_generator.py --input risk_register.json --output memo.md

# JSON metadata output
python scripts/risk_report_generator.py --input risk_register.json --json

Report includes:

  • ASCII risk matrix visualization
  • Risk distribution summary (counts and percentages per level)
  • Top risks ranked by score
  • Recommended actions per risk with owner assignments
  • Monitoring plan suggestions
  • Escalation recommendations

Reference Guides

Risk Framework

references/risk_framework.md

Complete Severity x Likelihood matrix reference:

  • Severity levels 1-5 with financial exposure percentages
  • Likelihood levels 1-5 with probability ranges
  • Risk matrix visualization
  • Risk classification (GREEN/YELLOW/ORANGE/RED) with actions
  • Documentation standards for memos and register entries
Escalation Guide

references/escalation_guide.md

When to engage outside counsel:

  • Mandatory engagement triggers (litigation, investigation, criminal)
  • Strongly recommended scenarios (novel issues, material exposure)
  • Consider scenarios (complex disputes, employment, data incidents)
  • Risk category definitions and contributing/mitigating factors

Workflows

Workflow 1: New Risk Assessment
Step 1: Identify risk category and description
        → Use references/risk_framework.md category definitions

Step 2: Score severity (1-5) and likelihood (1-5)
        → python scripts/risk_scorer.py --severity N --likelihood N \
          --category "Category" --description "Description"

Step 3: Review risk level and recommended action
        → GREEN: Accept and document
        → YELLOW: Assign owner and monitor
        → ORANGE: Escalate to senior counsel
        → RED: Immediate escalation, crisis management

Step 4: Determine outside counsel need
        → Consult references/escalation_guide.md

Step 5: Document in risk register
        → Add entry to register JSON file
Workflow 2: Periodic Risk Register Review
Step 1: Load current risk register
        → python scripts/risk_scorer.py --input register.json

Step 2: Generate assessment memo
        → python scripts/risk_report_generator.py --input register.json --output memo.md

Step 3: Review top risks and distribution
        → Focus on ORANGE and RED risks first

Step 4: Update severity/likelihood for changed risks
        → Re-score and regenerate report

Step 5: Distribute memo to stakeholders
Workflow 3: Escalation Decision
Step 1: Score the risk
        → python scripts/risk_scorer.py --severity N --likelihood N \
          --category "Category" --description "Description"

Step 2: Check escalation triggers
        → Mandatory: active litigation, government investigation, criminal exposure
        → Strongly Recommended: novel issues, jurisdictional complexity, material exposure
        → Consider: complex disputes, employment matters, data incidents

Step 3: Document escalation rationale
        → Include risk score, level, and specific trigger in memo

Step 4: Select outside counsel if needed
        → See references/escalation_guide.md criteria

Troubleshooting

ProblemPossible CauseResolution
Risk score seems too low for a serious matterSeverity or likelihood underestimated; qualitative factors not capturedReview severity descriptions in risk_framework.md; consider worst-case financial exposure; add contributing factors to description
Multiple risks in same category but different scoresRisks have different severity/likelihood combinationsThis is expected; each risk is independent; review category-level trends in report
Batch mode fails on input fileMalformed JSON or missing required fieldsVerify JSON structure matches expected format; ensure each risk has severity, likelihood, category, description
Report generator produces empty matrixNo risks in input file or all risks have invalid scoresCheck that input JSON contains valid risks with severity 1-5 and likelihood 1-5
Escalation guide suggests outside counsel but budget is constrainedRisk score indicates material exposureDocument the budget constraint and residual risk acceptance; consider limited-scope engagement
Risk register grows unwieldyRisks not being closed or consolidatedArchive resolved risks; consolidate related risks; review register quarterly

Success Criteria

  • All identified legal risks scored and documented -- every risk has severity, likelihood, category, description, and recommended action in the register
  • Risk distribution reviewed quarterly -- memo generated and distributed to stakeholders with trend analysis
  • ORANGE and RED risks have assigned owners and mitigation plans -- no high-severity risk without accountability
  • Escalation decisions documented with rationale -- outside counsel engagement triggers clearly recorded
  • Risk register maintained as living document -- risks updated, resolved, or archived as status changes

Show full SKILL.md (339 more words)Show less

Scope & Limitations

In Scope:

  • Quantitative risk scoring using 5x5 Severity x Likelihood matrix
  • Risk register management and batch processing
  • Risk assessment memo generation with matrix visualization
  • Escalation guidance for outside counsel engagement
  • Risk categorization (Contract, Regulatory, Litigation, IP, Data Privacy, Employment, Corporate)

Out of Scope:

  • Legal advice on specific risk mitigation strategies -- consult legal counsel
  • Insurance coverage analysis or actuarial calculations
  • Regulatory filing or submission preparation
  • Contract drafting or review
  • Litigation strategy or case management

Anti-Patterns

  • Scoring by committee consensus without criteria -- use the defined severity and likelihood scales consistently; do not negotiate scores to make stakeholders comfortable; a risk scored as 4 severity should match the framework definition
  • Treating the risk register as a one-time exercise -- risk registers are living documents; risks change as circumstances evolve; schedule quarterly reviews and update scores accordingly
  • Escalating everything to outside counsel -- the escalation guide defines specific triggers; not every YELLOW risk needs external counsel; over-escalation wastes budget and creates dependency
  • Ignoring GREEN risks entirely -- GREEN risks still require documentation and periodic monitoring; a GREEN risk can escalate to YELLOW or ORANGE if circumstances change
  • Using risk scores as the sole decision factor -- scores are inputs to judgment, not substitutes; qualitative factors like reputational impact or strategic importance may warrant action beyond what the score suggests

Tool Reference

risk_scorer.py

Calculates risk scores and assigns color-coded risk levels with recommended actions.

FlagRequiredDescription
--severity <1-5>Yes (single mode)Severity rating: 1=Negligible, 2=Minor, 3=Moderate, 4=Major, 5=Critical
--likelihood <1-5>Yes (single mode)Likelihood rating: 1=Remote, 2=Unlikely, 3=Possible, 4=Likely, 5=Almost Certain
--category <text>Yes (single mode)Risk category: Contract, Regulatory, Litigation, IP, Data Privacy, Employment, Corporate
--description <text>Yes (single mode)Risk description
--input <file>Yes (batch mode)Path to JSON file containing multiple risks
--jsonNoOutput results in JSON format
risk_report_generator.py

Generates formatted risk assessment memo from a risk register JSON file.

FlagRequiredDescription
--input <file>YesPath to risk register JSON file
--output <file>NoSave memo to specified file path (markdown format)
--jsonNoOutput report metadata in JSON format

© aAAaqwq, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/legal-risk-assessment of aAAaqwq/AGI-Super-Team.

Open the folder on GitHubat commit 7cefd81

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in aAAaqwq/AGI-Super-Team, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Legal Risk Assessment this skillaAAaqwq/AGI-Super-Team1051 repos~2.6kAutomated safety check: PassMIT
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Legal Risk Visualizationzh-xx/legal-assistant-skills174—~2.4kAutomated safety check: PassApache-2.0
Contract Renewal Trackeranthropics/claude-for-legal9.6k2 repos~3.1kAutomated safety check: PassApache-2.0
Deep Risk Analysiszubair-trabzada/ai-legal-claude1.8k—~1.9kAutomated safety check: PassNone
Canghe Tianyanchafreestylefly/canghe-skills461—~2.4kAutomated safety check: PassNone

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Questions about Legal Risk Assessment

What does Legal Risk Assessment do?

Structured legal risk assessment with 5x5 Severity x Likelihood matrix. Legal Risk Assessment is an agent skill from aAAaqwq/AGI-Super-Team. Structured legal risk assessment with 5x5 Severity x Likelihood matrix.

When should I use Legal Risk Assessment?

Legal Risk Assessment fits situations like: escalation decisions; tasks that involve Legal risk assessment.

How do I install Legal Risk Assessment in Claude Code?

Run `npx skills add aAAaqwq/AGI-Super-Team --skill legal-risk-assessment -a claude-code`. Or copy the skill folder (skills/legal-risk-assessment in aAAaqwq/AGI-Super-Team) into .claude/skills/legal-risk-assessment in your project. Claude Code loads it when a task matches its description.

How do I install Legal Risk Assessment in Codex?

Run `npx skills add aAAaqwq/AGI-Super-Team --skill legal-risk-assessment -a codex`. Or copy the skill folder (skills/legal-risk-assessment in aAAaqwq/AGI-Super-Team) into .agents/skills/legal-risk-assessment in your project. Codex loads it when a task matches its description.

Can I use Legal Risk Assessment in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aAAaqwq/AGI-Super-Team --skill legal-risk-assessment -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/legal-risk-assessment, .gemini/skills/legal-risk-assessment, .github/skills/legal-risk-assessment and .opencode/skills/legal-risk-assessment in your project.

What does Legal Risk Assessment need to run?

Going by SKILL.md and its folder, Legal Risk Assessment needs the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Legal Risk Assessment access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Legal Risk Assessment safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Legal Risk Assessment use?

Legal Risk Assessment is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Legal Risk Assessment use?

About 2.6k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Legal Risk Assessment?

Skills that share tags, products or a category with Legal Risk Assessment: Product Launch Legal Review (anthropics/claude-for-legal, 9.6k stars), Legal Risk Visualization (zh-xx/legal-assistant-skills, 174 stars), Contract Renewal Tracker (anthropics/claude-for-legal, 9.6k stars) and Deep Risk Analysis (zubair-trabzada/ai-legal-claude, 1.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Legal Risk Assessment?

aAAaqwq (a GitHub user) maintains it in aAAaqwq/AGI-Super-Team, which has 105 GitHub stars. The repository holds 167 skills in this directory. The repository was last updated on October 8, 2026.

Source: aAAaqwq/AGI-Super-Team on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.