feedback-loop-detection

name	feedback-loop-detection
description	Tactic for identifying circular causation — detect feedback loops, classify as reinforcing or balancing, document loop structure.
execution	tactic
dependencies	{"sops":["causal-chain-query","loop-documentation","mechanism-edge-creation"]}

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.

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.