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yogsoth-aiyogsoth-ai/convergence/skills/assumption-excavation/SKILL.md

assumption-excavation

Skill2 starsChanged 6 months agoApache-2.0View on GitHub

Systematic extraction, challenge, and sensitivity analysis of assumptions underlying a decision to identify load-bearing beliefs.

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SKILL.md

Assumption Excavation

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

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