Causal Necessity Testing Tactic
SkillDev tools'Tactic: Extract causal claims, evaluate probability of necessity (PN)
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Causal Necessity Testing Tactic skill
What this skill tells your AI
The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/causal-necessity-testing/SKILL.md and read by ahel’s review.
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? |
Signals
- GitHub stars
- 469
- Forks
- 37
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
causal-necessity-testing- Source
- github.com/yogsoth-ai/de-anthropocentric-research-engine