| name | feedback-loop-detection |
| description | Tactic for identifying circular causation — detect feedback loops, classify as reinforcing or balancing, document loop structure. |
| execution | tactic |
| used-by | causal-modeling, mechanism-mapping, model-validation |
Feedback Loop Detection
Identify circular causation in the causal graph. Most real systems have feedback loops — they must be documented explicitly.
Available SOPs
- causal-chain-query — trace paths looking for cycles
- loop-documentation — document identified loops
- mechanism-edge-creation — create edges that close loops
Guiding Principles
- Loops are normal. Don't assume acyclicity. Real causal systems almost always have feedback.
- Classify loops. Reinforcing (positive feedback, amplification) vs balancing (negative feedback, homeostasis).
- Time delays matter. A loop with a 10-year delay behaves differently from one with a 10ms delay.
- Dominant loops. In systems with multiple loops, identify which loop dominates behavior.
- Break points. Identify where interventions could break harmful loops.
Minimum Yield
≥1 loop identified and classified (or explicit confirmation that no loops exist in the current subgraph) per invocation.
