| name | four-risks |
| description | Run Marty Cagan's Four Risks assessment on an issue (value, usability, feasibility, viability). Use when evaluating features before building. |
Four Risks Assessment
Apply Marty Cagan's Four Risks Framework to assess an issue before building.
Works with:
- Linear MCP - Reads issue details and adds assessment as comment
- GitHub MCP - Reads issue details and adds assessment as comment
- Manual - Describe the feature directly
Entry Point
When this skill is invoked, start with:
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FOUR RISKS ASSESSMENT
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What are you assessing?
1. Specific issue/feature
→ Provide issue ID or describe the feature
2. Current sprint issues
→ Assess all issues in current sprint
3. Quick risk check
→ Fast assessment on something you're considering
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What This Does
Evaluates a feature/project against the four critical risks:
- Value: Will customers use/buy this?
- Usability: Can users figure it out?
- Feasibility: Can we build it?
- Viability: Does it work for our business?
Usage
/four-risks [issue-id]
Examples:
/four-risks ENG-245 - Assess specific issue/four-risks --current-sprint - Assess all current sprint issues/four-risks --add-comment - Add assessment as Linear comment
What Happens
- Fetches issue details from Linear or GitHub (if MCPs configured)
- Applies Four Risks framework:
- Analyzes issue description
- Asks clarifying questions if needed
- Assesses each risk dimension
- Returns risk assessment with:
- Risk level for each dimension (High/Medium/Low)
- Key questions to de-risk
- Recommended discovery activities
- Optionally adds comment to source issue with assessment (if using Linear)
Example Output
🎯 Four Risks Assessment: [ENG-245] AI-powered email composer
📊 RISK SUMMARY
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1️⃣ VALUE RISK: 🔴 HIGH
Will customers use/buy this?
⚠️ Concerns:
- No customer interviews validating demand
- Competitive AI email tools exist (Grammarly, Jasper)
- Unclear differentiation
✅ To de-risk:
- Run 10 customer interviews about email pain points
- Test prototype with 5 users
- Validate willingness to pay
2️⃣ USABILITY RISK: 🟡 MEDIUM
Can users figure it out?
⚠️ Concerns:
- AI output needs review UX
- Tone/voice customization complexity
✅ To de-risk:
- Create clickable prototype
- Run usability tests with 5 users
- Test with non-technical users
3️⃣ FEASIBILITY RISK: 🟢 LOW
Can we build it?
✅ Confidence:
- Team has AI integration experience
- OpenAI API well-documented
- Spike completed successfully
⚠️ Minor concerns:
- Inference costs at scale (needs modeling)
4️⃣ VIABILITY RISK: 🟡 MEDIUM
Does it work for our business?
⚠️ Concerns:
- Unit economics unclear (AI costs)
- Legal review needed for AI-generated content
- Competitive differentiation weak
✅ To de-risk:
- Model costs at 10K, 100K, 1M emails/month
- Legal review of AI content liability
- Define unique value prop
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🎯 RECOMMENDATION: DO NOT BUILD YET
Highest risk: VALUE (customers may not want/pay for this)
📋 Discovery Plan:
Week 1: Customer interviews (10 users)
Week 2: Build throwaway prototype
Week 3: Usability testing (5 users)
Week 4: Unit economics modeling
Only proceed if:
✓ 60%+ of interviews validate strong need
✓ Prototype test shows clear value
✓ Unit economics support freemium model
Integration Options
With Linear MCP:
Automatically fetches Linear issue details and can add assessment as comment.
With GitHub MCP:
Automatically fetches GitHub issue details and can add assessment as comment.
Manual mode:
Describe the feature and the command will assess it:
Run a four risks assessment on this feature: [describe feature]
Learn More
See the full Four Risks framework at:
frameworks/discovery/four-risks.md
Framework: Marty Cagan (SVPG)
Best for: Pre-build validation, discovery planning, reducing waste
AI-era adaptation: Prototype to test risks in hours, not weeks
