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meta-scenario-planning
About meta-scenario-planning
meta-scenario-planning is a scenario planning skill for teams testing strategies against multiple plausible futures. It uses two critical uncertainties to build four scenarios and evaluates whether options remain robust across them rather than treating scenarios as predictions.
Key features
- 01Identify and rate driving forces
- 02Select two critical uncertainties
- 03Build a 2×2 scenario matrix
- 04Describe four plausible futures
- 05Test strategy options across scenarios
- 06Identify early warning signals
Use cases
- 01Explore multiple futures for long-term strategy
- 02Check whether a strategy relies on one scenario
- 03Assess effects of regulatory or technological shifts
- 04Choose indicators to monitor emerging scenarios
Install
Copy the command and run it in a terminal.
$
npx skills add https:/ / github.com/ asgard-ai-platform/ skills --skill meta-scenario-planningAfter installing, type/meta-scenario-planningin Claude Code to confirm it loaded.
Bundled filesexamples/sample_scenario.mdreferences/shell-method.md
Details
From the project READMEScenario Planning
Framework
IRON LAW: Scenarios Are Not Predictions
Scenarios are PLAUSIBLE futures, not forecasts. The goal is NOT to predict
which future will happen, but to prepare strategies that work across
MULTIPLE possible futures. A strategy that only works in one scenario
is fragile.
The 2×2 Scenario Matrix Method
- Identify driving forces: What macro-forces will most shape the future? (technology, regulation, economy, demographics, competition)
- Select two critical uncertainties: The two most impactful forces with the most uncertain outcomes
- Build the 2×2 matrix: Each axis is one uncertainty with two endpoints (e.g., "regulation: strict vs lax")
- Name and describe four scenarios: Each quadrant is a distinct plausible future
- Test strategies against all four: Which strategies work in most/all scenarios? Which only work in one?
Process
Step 1: Driving Forces (brainstorm 10-15)
- Political, economic, social, technological, environmental, competitive
- Rate each on: Impact (H/M/L) × Uncertainty (H/M/L)
- High Impact + High Uncertainty → candidate for axes
Step 2: Select Two Axes
- Choose two forces that are both high-impact AND high-uncertainty
- They should be independent of each other (not correlated)
Step 3: Build Four Scenarios
- Give each scenario a memorable name (not "Scenario 1")
- Write a 1-paragraph narrative for each: what does this world look like in 5-10 years?
Step 4: Strategy Testing
- For each strategy option, assess: does it work in this scenario? (Yes / Partial / No)
- Robust strategies work in 3-4 scenarios. Fragile strategies work in only 1.
Output Format
# Scenario Planning: {Context}
## Driving Forces
| Force | Impact | Uncertainty | Selected? |
|-------|--------|------------|-----------|
| {force} | H/M/L | H/M/L | ✓/— |
## Scenario Matrix
- Axis 1: {Uncertainty A} — {endpoint 1} vs {endpoint 2}
- Axis 2: {Uncertainty B} — {endpoint 1} vs {endpoint 2}
| | {A: endpoint 1} | {A: endpoint 2} |
|---|---|---|
| **{B: endpoint 1}** | **"{Scenario Name}"**: {narrative} | **"{Scenario Name}"**: {narrative} |
| **{B: endpoint 2}** | **"{Scenario Name}"**: {narrative} | **"{Scenario Name}"**: {narrative} |
## Strategy Robustness Test
| Strategy | Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 |
|----------|-----------|-----------|-----------|-----------|
| {strategy A} | ✓/△/✗ | ✓/△/✗ | ✓/△/✗ | ✓/△/✗ |
## Robust Strategies
{Strategies that work in most scenarios}
## Contingency Triggers
- If {early signal}, activate {contingency plan for scenario X}
Gotchas
- Scenarios should be uncomfortable: If all four scenarios are comfortable, you haven't explored enough uncertainty. Include at least one scenario you'd rather not think about.
- Avoid "good/bad" framing: Scenarios aren't optimistic vs pessimistic. Each scenario has opportunities AND threats. A "strict regulation" world is bad for some and good for others.
- Early warning signals: Identify observable indicators that signal which scenario is unfolding. This converts scenarios into actionable intelligence.
- Two axes is a simplification: Reality has many uncertainties. The 2×2 is a tool for clarity, not completeness. Consider additional driving forces as variations within scenarios.
References
- For Shell's original scenario planning methodology, see
references/shell-method.md
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