Assumption Excavation
SkillDev toolsSystematic extraction, challenge, and sensitivity analysis of assumptions
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 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
- Assumption Extraction — Systematically surface all assumptions underlying the decision, with confidence levels
- Assumption Challenge — For each assumption, construct the strongest counter-argument and identify alternatives
- Conclusion Sensitivity — Map which assumptions, if wrong, would change the conclusion
Available SOPs
| SOP | Phase | Purpose |
|---|---|---|
| assumption-extraction | Extract | Surface hidden assumptions with confidence |
| assumption-challenge | Challenge | Attack each assumption adversarially |
| conclusion-sensitivity | Sensitivity | Map 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.
| SOP | When to use |
|---|---|
| conclusion-sensitivity | Map which assumptions are load-bearing by assessing how the conclusion changes if each assumption fails. |
| convergence-assumption-challenge | Construct the strongest counter-argument against a specific assumption and propose alternatives. |
| convergence-assumption-extraction | Systematically 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