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/assumption-constraint

Which assumptions are most fragile? — Vulnerability ranking + impact

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

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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-constraint

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Which assumptions are most fragile? — Vulnerability ranking + impact

SKILL.md

assumption-constraint.SKILL.md
name: assumption-constraint
description: Which assumptions are most fragile? — Vulnerability ranking + impact
  assessment of experiment assumptions
version: 1.0.0
category: experiment-execution
type: strategy
sops:
- assumption-challenging
- resource-quantification
tactics:
- sensitivity-ranking
dependencies:
  sops:
  - assumption-challenging
  - resource-quantification
  tactics:
  - sensitivity-ranking

Strategy: Assumption Constraint

Methodology

Systematic assumption vulnerability analysis:

  • **Extraction**: Surface all implicit and explicit assumptions
  • **Scoring**: Quantify vulnerability (confidence × evidence / testability)
  • **Impact assessment**: Blast radius × recovery cost
  • **Prioritization**: Vulnerability × Impact = Priority
  • **Validation planning**: Cheapest test that resolves uncertainty

Assumption categories: | Category | Examples | |----------|----------| | Technical | Method convergence, architecture suitability | | Data | Availability, quality, representativeness | | Resource | Sufficiency of compute, time, expertise | | Environmental | Tool stability, API access, policy | | Theoretical | Effect existence, measurability, magnitude |

Execution Flow

1. **Challenge Assumptions** → call `assumption-challenging` SOP

  • Input: experiment plan, hypothesis
  • Output: assumption inventory with validity assessment

2. **Quantify Validation Cost** → call `resource-quantification` SOP

  • Input: validation experiments for top assumptions
  • Output: cost to validate each assumption

3. **Rank Sensitivity** → invoke `sensitivity-ranking` tactic

  • Determine which assumptions are most binding

4. **Report** → synthesize vulnerability assessment

  • Top-5 fragile assumptions with validation paths
  • Binding assumption constraint identification

Budget Gate

| Resource | Budget | Notes | |----------|--------|-------| | Subagent calls | ≤5 | 2 SOPs + synthesis | | Iterations | ≤2 | Re-rank if new assumptions surface | | Output size | ≤3000 tokens | Ranked table + validation plan |

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

Available Tactics

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

| Tactic | When to use | | --- | --- | | sensitivity-ranking | Rank constraints by sensitivity — which ones most impact the outcome if they shift |

Available SOPs

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

| SOP | When to use | | --- | --- | | assumption-challenging | Challenge each assumption's validity — shared cross-repo SOP | | resource-quantification | Quantify resource demand vs supply vs gap for each resource category |

<!-- 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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