yogsoth-ai 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
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| causal-chain-query | SOP for tracing causal chains — follow edges from cause to effect through intermediate variables. |
| loop-documentation | SOP for documenting a feedback loop — classify, describe dynamics, identify break points. |
| mechanism-edge-creation | SOP for creating a causal mechanism edge — documents how one variable causes changes in another. |