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skills/decision-matrix/SKILL.md

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+---
+name: decision-matrix
+description: Use when comparing multiple named alternatives across several criteria, need transparent trade-off analysis, making group decisions requiring alignment, choosing between vendors/tools/strategies, stakeholders need to see decision rationale, balancing competing priorities (cost vs quality vs speed), user mentions "which option should we choose", "compare alternatives", "evaluate vendors", "trade-offs", or when decision needs to be defensible and data-driven.
+---
+
+# Decision Matrix
+
+## What Is It?
+
+A decision matrix is a structured tool for comparing multiple alternatives against weighted criteria to make transparent, defensible choices. It forces explicit trade-off analysis by scoring each option on each criterion, making subjective factors visible and comparable.
+
+**Quick example:**
+
+| Option | Cost (30%) | Speed (25%) | Quality (45%) | Weighted Score |
+|--------|-----------|------------|---------------|----------------|
+| Option A | 8 (2.4) | 6 (1.5) | 9 (4.05) | **7.95** ← Winner |
+| Option B | 6 (1.8) | 9 (2.25) | 7 (3.15) | 7.20 |
+| Option C | 9 (2.7) | 4 (1.0) | 6 (2.7) | 6.40 |
+
+The numbers in parentheses show criterion score × weight. Option A wins despite not being fastest or cheapest because quality matters most (45% weight).
+
+## Workflow
+
+Copy this checklist and track your progress:
+
+```
+Decision Matrix Progress:
+- [ ] Step 1: Frame the decision and list alternatives
+- [ ] Step 2: Identify and weight criteria
+- [ ] Step 3: Score each alternative on each criterion
+- [ ] Step 4: Calculate weighted scores and analyze results
+- [ ] Step 5: Validate quality and deliver recommendation
+```
+
+**Step 1: Frame the decision and list alternatives**
+
+Ask user for decision context (what are we choosing and why), list of alternatives (specific named options, not generic categories), constraints or dealbreakers (must-have requirements), and stakeholders (who needs to agree). Understanding must-haves helps filter options before scoring. See [Framing Questions](#framing-questions) for clarification prompts.
+
+**Step 2: Identify and weight criteria**
+
+Collaborate with user to identify criteria (what factors matter for this decision), determine weights (which criteria matter most, as percentages summing to 100%), and validate coverage (do criteria capture all important trade-offs). If user is unsure about weighting → Use [resources/template.md](resources/template.md) for weighting techniques. See [Criterion Types](#criterion-types) for common patterns.
+
+**Step 3: Score each alternative on each criterion**
+
+For each option, score on each criterion using consistent scale (typically 1-10 where 10 = best). Ask user for scores or research objective data (cost, speed metrics) where available. Document assumptions and data sources. For complex scoring → See [resources/methodology.md](resources/methodology.md) for calibration techniques.
+
+**Step 4: Calculate weighted scores and analyze results**
+
+Calculate weighted score for each option (sum of criterion score × weight). Rank options by total score. Identify close calls (options within 5% of each other). Check for sensitivity (would changing one weight flip the decision). See [Sensitivity Analysis](#sensitivity-analysis) for interpretation guidance.
+
+**Step 5: Validate quality and deliver recommendation**
+
+Self-assess using [resources/evaluators/rubric_decision_matrix.json](resources/evaluators/rubric_decision_matrix.json) (minimum score ≥ 3.5). Present decision-matrix.md file with clear recommendation, highlight key trade-offs revealed by analysis, note sensitivity to assumptions, and suggest next steps (gather more data on close calls, validate with stakeholders).
+
+## Framing Questions
+
+**To clarify the decision:**
+- What specific decision are we making? (Choose X from Y alternatives)
+- What happens if we don't decide or choose wrong?
+- When do we need to decide by?
+- Can we choose multiple options or only one?
+
+**To identify alternatives:**
+- What are all the named options we're considering?
+- Are there other alternatives we're ruling out immediately? Why?
+- What's the "do nothing" or status quo option?
+
+**To surface must-haves:**
+- Are there absolute dealbreakers? (Budget cap, timeline requirement, compliance need)
+- Which constraints are flexible vs rigid?
+
+## Criterion Types
+
+Common categories for criteria (adapt to your decision):
+
+**Financial Criteria:**
+- Upfront cost, ongoing cost, ROI, payback period, budget impact
+- Typical weight: 20-40% (higher for cost-sensitive decisions)
+
+**Performance Criteria:**
+- Speed, quality, reliability, scalability, capacity, throughput
+- Typical weight: 30-50% (higher for technical decisions)
+
+**Risk Criteria:**
+- Implementation risk, reversibility, vendor lock-in, technical debt, compliance risk
+- Typical weight: 10-25% (higher for enterprise/regulated environments)
+
+**Strategic Criteria:**
+- Alignment with goals, future flexibility, competitive advantage, market positioning
+- Typical weight: 15-30% (higher for long-term decisions)
+
+**Operational Criteria:**
+- Ease of use, maintenance burden, training required, integration complexity
+- Typical weight: 10-20% (higher for internal tools)
+
+**Stakeholder Criteria:**
+- Team preference, user satisfaction, executive alignment, customer impact
+- Typical weight: 5-15% (higher for change management contexts)
+
+## Weighting Approaches
+
+**Method 1: Direct Allocation (simplest)**
+Stakeholders assign percentages totaling 100%. Quick but can be arbitrary.
+
+**Method 2: Pairwise Comparison (more rigorous)**
+Compare each criterion pair: "Is cost more important than speed?" Build ranking, then assign weights.
+
+**Method 3: Must-Have vs Nice-to-Have (filters first)**
+Separate absolute requirements (pass/fail) from weighted criteria. Only evaluate options that pass must-haves.
+
+**Method 4: Stakeholder Averaging (group decisions)**
+Each stakeholder assigns weights independently, then average. Reveals divergence in priorities.
+
+See [resources/methodology.md](resources/methodology.md) for detailed facilitation techniques.
+
+## Sensitivity Analysis
+
+After calculating scores, check robustness:
+
+**1. Close calls:** Options within 5-10% of winner → Need more data or second opinion
+**2. Dominant criteria:** One criterion driving entire decision → Is weight too high?
+**3. Weight sensitivity:** Would swapping two criterion weights flip the winner? → Decision is fragile
+**4. Score sensitivity:** Would adjusting one score by ±1 point flip the winner? → Decision is sensitive to that data point
+
+**Red flags:**
+- Winner changes with small weight adjustments → Need stakeholder alignment on priorities
+- One option wins every criterion → Matrix is overkill, choice is obvious
+- Scores are mostly guesses → Gather more data before deciding
+
+## Common Patterns
+
+**Technology Selection:**
+- Criteria: Cost, performance, ecosystem maturity, team familiarity, vendor support
+- Weight: Performance and maturity typically 50%+
+
+**Vendor Evaluation:**
+- Criteria: Price, features, integration, support, reputation, contract terms
+- Weight: Features and integration typically 40-50%
+
+**Strategic Choices:**
+- Criteria: Market opportunity, resource requirements, risk, alignment, timing
+- Weight: Market opportunity and alignment typically 50%+
+
+**Hiring Decisions:**
+- Criteria: Experience, culture fit, growth potential, compensation expectations, availability
+- Weight: Experience and culture fit typically 50%+
+
+**Feature Prioritization:**
+- Criteria: User impact, effort, strategic value, risk, dependencies
+- Weight: User impact and strategic value typically 50%+
+
+## When NOT to Use This Skill
+
+**Skip decision matrix if:**
+- Only one viable option (no real alternatives to compare)
+- Decision is binary yes/no with single criterion (use simpler analysis)
+- Options differ on only one dimension (just compare that dimension)
+- Decision is urgent and stakes are low (analysis overhead not worth it)
+- Criteria are impossible to define objectively (purely emotional/aesthetic choice)
+- You already know the answer (using matrix to justify pre-made decision is waste)
+
+**Use instead:**
+- Single criterion → Simple ranking or threshold check
+- Binary decision → Pro/con list or expected value calculation
+- Highly uncertain → Scenario planning or decision tree
+- Purely subjective → Gut check or user preference vote
+
+## Quick Reference
+
+**Process:**
+1. Frame decision → List alternatives
+2. Identify criteria → Assign weights (sum to 100%)
+3. Score each option on each criterion (1-10 scale)
+4. Calculate weighted scores → Rank options
+5. Check sensitivity → Deliver recommendation
+
+**Resources:**
+- [resources/template.md](resources/template.md) - Structured matrix format and weighting techniques
+- [resources/methodology.md](resources/methodology.md) - Advanced techniques (group facilitation, calibration, sensitivity analysis)
+- [resources/evaluators/rubric_decision_matrix.json](resources/evaluators/rubric_decision_matrix.json) - Quality checklist before delivering
+
+**Deliverable:** `decision-matrix.md` file with table, rationale, and recommendation