abstraction-extraction

$npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/abstraction-extraction

Extract abstract principles from concrete domain cases to reveal transferable mechanisms

  • Identifies and isolates key features of a given problem instance.
  • Deploys natural language processing (NLP) and machine learning models for case analysis.
  • Utilizes pattern recognition algorithms to identify commonalities across different domains.
  • Generates concise, high-level descriptions that highlight universal patterns and principles.

SKILL.md

.github/skills/abstraction-extractionView on GitHub ↗
---
name: abstraction-extraction
description: Extract abstract principles from concrete domain cases. Strips domain-specific details to reveal transferable mechanisms.
execution: subagent
prompt: ./prompt.md
input: source_domain_case (string)
used-by: cross-domain-discovery, facet-bisociation, analogical-transfer, forced-bridge-construction, design-by-analogy, domain-divergence
---

# Abstraction Extraction

Extract abstract principles from concrete domain cases.

## Execution

Subagent — spawned via subagent-spawning/spawn-agent skill.

## Why Subagent

Abstraction requires careful layered reasoning — moving from concrete details through functional description to pure relational structure. Benefits from dedicated attention to avoid premature abstraction or under-abstraction.

More from yogsoth-ai/de-anthropocentric-research-engine

SkillDescription
abductive-hypothesis-generationStrategy: 面对异常的最佳解释推理
ablation-brainstormRemove components one by one, observe system changes to reveal hidden dependencies and generate ideas from structural gaps.
ablation-component-mappingMap system architecture to ablatable units for ablation studies
ablation-designDesign ablation studies to isolate component contributions in ML systems
ablation-executionRemove components one by one from a system, record the response/impact of each removal.
abp-vulnerability-classificationClassify assumptions on 2 axes — load-bearing (how much conclusion depends on it) × vulnerable (how likely to be false). Focuses attention on High-Load × High-Vulnerable quadrant.
abstraction-ladderPerform bisociation at multiple abstraction levels
abstraction-ladderingMove between concrete and abstract framings — 3 levels up (Why?) and 3 levels down (How?) to find the most productive research level.
abstraction-to-designAbstract biological principle to design principle. Bridge from biology to engineering.
action-priority-matrixCompute Risk Priority Number (RPN = S x O x D), classify failure modes into H/M/L action priority per AIAG-VDA tables.