yogsoth-ai Causal Necessity Testing Tactic
PNS evaluation: for each causal claim, determine whether the cause is necessary, sufficient, both, or neither.
Orchestration
- causal-claim-extraction extracts all X→Y causal claims from the artifact
- necessity-evaluation asks: if X had NOT occurred, would Y still hold? (PN)
- sufficiency-evaluation asks: if X occurred in isolation, would Y follow? (PS)
- Classify each claim into quadrant:
- PN high + PS high → INUS condition (load-bearing)
- PN high + PS low → necessary but not sufficient
- PN low + PS high → sufficient but redundant
- PN low + PS low → spurious or decorative
- load-bearing-identification synthesizes quadrant assignments
Scoring
- PN and PS scored 0.0–1.0 (probability estimates)
- Threshold for "high": >= 0.7
- Threshold for "low": < 0.3
- Middle range (0.3–0.7): uncertain, flag for deeper investigation
Subagents Dispatched
- causal-claim-extraction (claim identification)
- necessity-evaluation (PN scoring per claim)
- sufficiency-evaluation (PS scoring per claim)
- load-bearing-identification (quadrant synthesis)
Termination Conditions
- All extracted claims evaluated within budget
- Early termination if INUS condition found and budget is S
- All claims score PN < 0.3 (no necessary factors found — conclusion may be overdetermined)
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| causal-claim-extraction | Extract all causal claims (X causes Y, X leads to Y, X enables Y) from an artifact, producing a structured list of cause-effect pairs. |
| load-bearing-identification | Identify which factors are "load-bearing walls" — factors whose removal would collapse the conclusion. |
| necessity-evaluation | Evaluate the probability of necessity (PN) for a causal factor — would the conclusion fail if this factor were absent? |
| sufficiency-evaluation | Evaluate the probability of sufficiency (PS) for a causal factor — would this factor alone be enough to produce the conclusion? |