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/assumption-excavation

Systematic extraction, challenge, and sensitivity analysis of assumptions

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de-anthropocentric-research-engine
393200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill assumption-excavation --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/assumption-excavation

Context preview

The summary Claude sees to decide when to auto-load this skill.

Systematic extraction, challenge, and sensitivity analysis of assumptions

SKILL.md

assumption-excavation.SKILL.md
name: assumption-excavation
description: Systematic extraction, challenge, and sensitivity analysis of assumptions
  underlying a decision to identify load-bearing beliefs.
execution: tactic
dependencies:
  sops:
  - conclusion-sensitivity
  - convergence-assumption-challenge
  - convergence-assumption-extraction

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

| 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

<!-- BEGIN available-tables (generated) -->

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. |

<!-- END available-tables (generated) -->

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The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.

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