Use when problems involve interconnected components with feedback loops (reinforcing or balancing), delays, or emergent behavior where simple cause-effect thinking fails. Invoke when identifying leverage points for intervention (where to push for maximum effect with minimum effort), understanding why past solutions failed or had unintended consequences, analyzing system archetypes (fixes that fail, shifting the burden, tragedy of the commons, limits to growth, escalation), mapping stocks and flows (accumulations and rates of change), discovering feedback loop dynamics, finding root causes in complex adaptive systems, designing interventions that work with system structure rather than against it, or when user mentions systems thinking, leverage points, feedback loops, unintended consequences, system dynamics, causal loop diagrams, or complex systems. Apply to organizational systems (employee engagement, scaling challenges, productivity decline), product/technical systems (technical debt accumulation, performance degradation, adoption barriers), social systems (polarization, misinformation spread, community issues), environmental systems (climate, resource depletion, pollution), personal systems (habit formation, burnout, skill development), and anywhere simple linear interventions repeatedly fail while systemic patterns persist.
Analyze complex systems with feedback loops, delays, and unintended consequences to identify high-leverage intervention points. Use when simple fixes fail, past solutions backfired, or you need to understand why systemic patterns persist.
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resources/evaluators/rubric_systems_thinking_leverage.jsonresources/methodology.mdresources/template.mdFind high-leverage intervention points in complex systems by mapping feedback loops, identifying system archetypes, and understanding where small changes can produce large effects.
Invoke this skill when:
Don't use when:
Systems thinking analyzes how interconnected components create emergent behavior through feedback loops, stocks/flows, and delays. Leverage points (Donella Meadows) are places to intervene in a system ranked by effectiveness:
Low leverage (easy but weak): Parameters (numbers, rates, constants) Medium leverage: Buffers, stock structures, delays, feedback loop strength High leverage (hard but powerful): Information flows, rules, self-organization, goals, paradigms
Example: Company with high employee turnover (problem).
Low leverage: Increase salaries 10% (parameter) → Temporary effect, competitors match Medium leverage: Improve manager-employee feedback frequency (balancing loop) → Some improvement High leverage: Change goal from "minimize cost per employee" to "maximize team capability" → Shifts hiring, training, retention decisions system-wide
Quick example of feedback loops:
Copy this checklist and track your progress:
Systems Thinking & Leverage Progress:
- [ ] Step 1: Define system and problem
- [ ] Step 2: Map system structure
- [ ] Step 3: Identify leverage points
- [ ] Step 4: Validate and test interventions
- [ ] Step 5: Design high-leverage strategy
Step 1: Define system and problem
Clarify system boundaries (what's in/out of system), key variables (stocks that accumulate, flows that change them), and problem symptom vs. underlying pattern. Use System Definition section below.
Step 2: Map system structure
For simple cases → Use resources/template.md for quick causal loop diagram and stock-flow identification. For complex cases → Study resources/methodology.md for system archetypes, multi-loop analysis, and time delays.
Step 3: Identify leverage points
Apply Meadows' leverage hierarchy (parameters < buffers < structure < delays < balancing loops < reinforcing loops < information < rules < self-organization < goals < paradigms). See Leverage Points Analysis below and resources/methodology.md for techniques.
Step 4: Validate and test interventions
Self-assess using resources/evaluators/rubric_systems_thinking_leverage.json. Test mental models: what happens if we push here? What are second-order effects? What delays might undermine intervention? See Validation section.
Step 5: Design high-leverage strategy
Create systems-thinking-leverage.md with system map, leverage point ranking, recommended interventions, and predicted outcomes. See Delivery Format section.
Before mapping, clarify:
1. System Boundary
2. Key Variables
3. Time Horizon
4. Problem Statement
Meadows' 12 Leverage Points (ascending order of effectiveness):
12. Parameters (weak) - Constants, numbers (tax rates, salaries, prices)
11. Buffers - Stock sizes relative to flows (reserves, inventories)
10. Stock-and-Flow Structures - Physical system design
9. Delays - Time lags in information flows
8. Balancing Feedback Loops - Strength of stabilizing forces
7. Reinforcing Feedback Loops - Strength of amplifying forces
6. Information Flows - Who has access to what information
5. Rules - Incentives, constraints, punishments
4. Self-Organization - Power to add/change/evolve structure
3. Goals - Purpose the system serves
2. Paradigms - Mindset from which the system arises
1. Transcending Paradigms (strongest) - Ability to shift between paradigms
How to Use This Hierarchy:
Before finalizing, check:
System Map Quality:
Leverage Point Analysis:
Archetype Recognition (if applicable):
Mental Model Testing:
Minimum Standard: Use rubric (resources/evaluators/rubric_systems_thinking_leverage.json). Average score ≥ 3.5/5 before delivering.
Create systems-thinking-leverage.md with:
1. System Overview
2. System Map
3. Leverage Point Analysis
4. Intervention Strategy
5. Implementation Considerations
If system matches these patterns, leverage points are well-known:
Fixes That Fail
Shifting the Burden
Tragedy of the Commons
Limits to Growth
For more archetypes, see resources/methodology.md.
Resources:
Key Concepts:
Red Flags:
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