four-risks

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

1. Fetches issue details from Linear or GitHub (if MCPs configured)
2. Applies Four Risks framework:
   • Analyzes issue description
   • Asks clarifying questions if needed
   • Assesses each risk dimension
3. Returns risk assessment with:
   • Risk level for each dimension (High/Medium/Low)
   • Key questions to de-risk
   • Recommended discovery activities
4. 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

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Framework: Marty Cagan (SVPG) Best for: Pre-build validation, discovery planning, reducing waste AI-era adaptation: Prototype to test risks in hours, not weeks