biological-function-mapping

$npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/biological-function-mapping

Maps technical functions to biological systems using a biologization pipeline

  • Solves the task of translating technical problems into biological function needs
  • Uses problem-biologization, organism-discovery, and functional-model-biology SOPs
  • Identifies champion organisms across diverse phyla to model target functions
  • Delivers functional models and biological insights for technical application

SKILL.md

.github/skills/biological-function-mappingView on GitHub ↗
---
name: biological-function-mapping
description: "Map technical functions to biological systems. Orchestrates problem-biologization → organism-discovery → functional-model-biology."
execution: tactic
used-by: biomimicry, biologize-and-discover, functional-analogy, biotriz-resolution
---

# Biological Function Mapping

Map technical functions to biological systems via biologize→discover→model pipeline.

## Stages

### Stage 1: Problem Biologization

Translate the technical problem into a biological function need statement using problem-biologization SOP. Frame in terms of what function nature must achieve, not how.

### Stage 2: Organism Discovery

Search for organisms that solve the biologized problem using organism-discovery SOP. Identify champion organisms across multiple phyla/kingdoms for diversity.

### Stage 3: Functional Modeling

For each promising organism, build a functional model (energy/matter/information flows) using functional-model-biology SOP. Identify the mechanism that achieves the target function.

## Minimum Yield

| Metric | Floor |
|--------|-------|
| Biological function statements | ≥2 |
| Organisms discovered | ≥5 |
| Biological systems mapped to technical functions | ≥3 |
| Functional models completed | ≥3 |

## Available SOPs

| SOP | Role |
|-----|------|
| problem-biologization | Stage 1 — translate technical→biological |
| organism-discovery | Stage 2 — find champion organisms |
| functional-model-biology | Stage 3 — build functional models |
| biological-strategy-extraction | Post — extract transferable strategies |
| web-search | Support — search for biological solutions |
| paper-overview | Support — find academic biology sources |

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-extractionExtract abstract principles from concrete domain cases. Strips domain-specific details to reveal transferable mechanisms.
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.