Assumption Excavation

SkillDev tools

Systematic extraction, challenge, and sensitivity analysis of assumptions

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Assumption Excavation skill

What this skill tells your AI

The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/assumption-excavation/SKILL.md and read by ahel’s review.

A three-phase tactic that surfaces hidden assumptions, challenges each one adversarially, and maps which assumptions are load-bearing for the conclusion. Decisions often rest on unstated beliefs — this tactic makes them explicit and tests their strength.

Stages

  1. Assumption Extraction — Systematically surface all assumptions underlying the decision, with confidence levels
  2. Assumption Challenge — For each assumption, construct the strongest counter-argument and identify alternatives
  3. Conclusion Sensitivity — Map which assumptions, if wrong, would change the conclusion

Available SOPs

SOPPhasePurpose
assumption-extractionExtractSurface hidden assumptions with confidence
assumption-challengeChallengeAttack each assumption adversarially
conclusion-sensitivitySensitivityMap load-bearing assumptions

Execution Guidance

  • Extract minimum 5 assumptions per decision
  • Challenge ALL assumptions, not just obvious ones
  • Confidence levels: HIGH (>80%), MEDIUM (50-80%), LOW (<50%)
  • Critical assumption = conclusion changes if assumption is wrong
  • Focus mitigation efforts on critical + low-confidence assumptions

Minimum Yield

  • = 5 assumptions extracted with confidence levels

  • Challenge argument for each assumption
  • Alternative assumption for each (what if the opposite is true?)
  • Sensitivity map showing which assumptions are critical
  • List of critical assumptions requiring mitigation

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

SOPWhen to use
conclusion-sensitivityMap which assumptions are load-bearing by assessing how the conclusion changes if each assumption fails.
convergence-assumption-challengeConstruct the strongest counter-argument against a specific assumption and propose alternatives.
convergence-assumption-extractionSystematically surface hidden assumptions underlying a decision with confidence levels.

Signals

GitHub stars
469
Forks
37
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
assumption-excavation
Source
github.com/yogsoth-ai/de-anthropocentric-research-engine