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Get Started Free →Use when ranking backlogs, deciding what to do first based on effort vs impact (quick wins vs big bets), prioritizing feature roadmaps, triaging bugs or technical debt, allocating resources across initiatives, identifying low-hanging fruit, evaluating strategic options with 2x2 matrix, or when user mentions prioritization, quick wins, effort-impact matrix, high-impact low-effort, big bets, or asks "what should we do first?".
.claude/skills/nicepkg-prioritization-effort-impact/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | 287% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 219% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 520% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 160% | 0% |
| case-19 | ✗→✓ | ▲ Improved | 92% | 0% |
Transform overwhelming backlogs and option lists into clear, actionable priorities by mapping items on a 2x2 matrix of effort (cost/complexity) vs impact (value/benefit). Identify quick wins (high impact, low effort) and distinguish them from big bets (high impact, high effort), time sinks (low impact, high effort), and fill-ins (low impact, low effort).
Use this skill when:
Common triggers:
Effort-Impact Matrix (also called Impact-Effort Matrix, Quick Wins Matrix, or 2x2 Prioritization) plots each item on two dimensions:
Four quadrants:
High Impact │
│ Big Bets │ Quick Wins
│ (do 2nd) │ (do 1st!)
│─────────────────┼─────────────
│ Time Sinks │ Fill-Ins
│ (avoid) │ (do last)
Low Impact │
└─────────────────┴─────────────
High Effort Low EffortExample: Feature backlog with 12 items
| Item | Effort | Impact | Quadrant | |------|--------|--------|----------| | Add "Export to CSV" button | Low (2d) | High (many users) | Quick Win ✓ | | Rebuild entire auth system | High (3mo) | High (security) | Big Bet | | Perfect pixel alignment on logo | High (1wk) | Low (aesthetic) | Time Sink ❌ | | Fix typo in footer | Low (5min) | Low (trivial) | Fill-In |
Decision: Do "Export to CSV" first (quick win), schedule auth rebuild next (big bet), skip logo perfection (time sink), batch typo fixes (fill-ins).
Copy this checklist and track your progress:
Prioritization Progress:
- [ ] Step 1: Gather items and clarify scoring
- [ ] Step 2: Score effort and impact
- [ ] Step 3: Plot matrix and identify quadrants
- [ ] Step 4: Create prioritized roadmap
- [ ] Step 5: Validate and communicate decisionsStep 1: Gather items and clarify scoring
Collect all items to prioritize (features, bugs, initiatives, etc.) and define scoring scales for effort and impact. See Scoring Frameworks for effort and impact definitions. Use resources/template.md for structure.
Step 2: Score effort and impact
Rate each item on effort (1-5: trivial to massive) and impact (1-5: negligible to transformative). Involve subject matter experts for accuracy. See resources/methodology.md for advanced scoring techniques like Fibonacci, T-shirt sizes, or RICE.
Step 3: Plot matrix and identify quadrants
Place items on 2x2 matrix and categorize into Quick Wins (high impact, low effort), Big Bets (high impact, high effort), Fill-Ins (low impact, low effort), and Time Sinks (low impact, high effort). See Common Patterns for typical quadrant distributions.
Step 4: Create prioritized roadmap
Sequence items: Quick Wins first, Big Bets second (after quick wins build momentum), Fill-Ins during downtime, avoid Time Sinks unless required. See resources/template.md for roadmap structure.
Step 5: Validate and communicate decisions
Self-check using resources/evaluators/rubric_prioritization_effort_impact.json. Ensure scoring is defensible, stakeholder perspectives included, and decisions clearly explained with rationale.
By domain:
By stakeholder priority:
Typical quadrant distribution:
Red flags:
Effort dimensions (choose relevant ones):
Impact dimensions (choose relevant ones):
Composite scoring:
Example scoring (feature: "Add dark mode"):
Ensure quality:
Resources:
Success criteria:
Common mistakes:
When to use alternatives:
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | pass→pass | 2,945 | 3,051 | +4% | 1 | 1 | 0% | 614 | 3,611 | +488% | 0 | 0 | — |
case-02 | pass→pass | 16,939 | 17,749 | +5% | 1 | 1 | 0% | 2,625 | 5,898 | +125% | 0 | 0 | — |
case-03 | pass→pass | 14,514 | 16,696 | +15% | 1 | 1 | 0% | 2,461 | 6,085 | +147% | 0 | 0 | — |
case-09 | pass→pass | 11,782 | 11,371 | -3% | 1 | 1 | 0% | 1,758 | 4,874 | +177% | 0 | 0 | — |
case-04 | pass→pass | 8,393 | 8,453 | +1% | 1 | 1 | 0% | 1,721 | 4,725 | +175% | 0 | 0 | — |
case-05 | pass→pass | 4,410 | 3,636 | -18% | 1 | 1 | 0% | 719 | 3,604 | +401% | 0 | 0 | — |
case-06 | pass→pass | 7,783 | 4,606 | -41% | 1 | 1 | 0% | 1,222 | 3,755 | +207% | 0 | 0 | — |
case-07 | fail→pass | 6,501 | 5,084 | -22% | 1 | 1 | 0% | 988 | 3,825 | +287% | 0 | 0 | — |
case-08 | fail→pass | 7,624 | 4,031 | -47% | 1 | 1 | 0% | 1,123 | 3,578 | +219% | 0 | 0 | — |
case-10 | fail→pass | 3,978 | 7,355 | +85% | 1 | 1 | 0% | 676 | 4,188 | +520% | 0 | 0 | — |
case-11 | pass→pass | 11,442 | 11,448 | +0% | 1 | 1 | 0% | 1,680 | 4,756 | +183% | 0 | 0 | — |
case-12 | pass→pass | 15,207 | 14,608 | -4% | 1 | 1 | 0% | 2,099 | 5,106 | +143% | 0 | 0 | — |
case-13 | fail→pass | 14,448 | 16,380 | +13% | 1 | 1 | 0% | 2,121 | 5,520 | +160% | 0 | 0 | — |
case-14 | pass→pass | 12,427 | 14,902 | +20% | 1 | 1 | 0% | 1,954 | 5,303 | +171% | 0 | 0 | — |
case-15 | pass→pass | 11,866 | 3,570 | -70% | 1 | 1 | 0% | 1,805 | 3,595 | +99% | 0 | 0 | — |
case-16 | pass→pass | 4,855 | 2,756 | -43% | 1 | 1 | 0% | 770 | 3,506 | +355% | 0 | 0 | — |
case-17 | pass→pass | 9,736 | 4,039 | -59% | 1 | 1 | 0% | 1,363 | 3,710 | +172% | 0 | 0 | — |
case-18 | fail→fail | 11,807 | 13,996 | +19% | 1 | 1 | 0% | 1,752 | 5,120 | +192% | 0 | 0 | — |
case-19 | fail→pass | 11,378 | 3,287 | -71% | 1 | 1 | 0% | 1,859 | 3,569 | +92% | 0 | 0 | — |
case-20 | pass→pass | 8,910 | 4,447 | -50% | 1 | 1 | 0% | 1,589 | 3,778 | +138% | 0 | 0 | — |
case-21 | pass→pass | 8,360 | 8,304 | -1% | 1 | 1 | 0% | 1,225 | 4,245 | +247% | 0 | 0 | — |
case-22 | fail→pass | 11,724 | 10,795 | -8% | 1 | 1 | 0% | 1,713 | 4,628 | +170% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +27 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.