Blend Construction
SkillDev toolsConstruct complete 4-space blends with emergent structure. Orchestrates
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Blend Construction skill
What this skill tells your AI
The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/blend-construction/SKILL.md and read by ahel’s review.
Construct complete 4-space blends with emergent structure following the Fauconnier-Turner conceptual integration network model.
Stages
Stage 1: Input Space Construction
Build rich input spaces for both source concepts using input-space-construction SOP. Each space must include elements, relations, attributes, and internal logic.
Stage 2: Generic Space Extraction
Extract the shared abstract structure from both input spaces using generic-space-extraction SOP. The generic space captures what the two inputs have in common at the most abstract level.
Stage 3: Blend Composition
Compose the blended space by selectively projecting structure from both inputs and creating new connections using blend-composition SOP. The blend must develop emergent structure not present in either input.
Minimum Yield
| Metric | Floor |
|---|---|
| Complete 4-space blends | ≥2 |
| Emergent structures per blend | ≥1 |
| Vital relations compressed | ≥3 per blend |
| Novel connections in blend | ≥2 per blend |
Available SOPs
| SOP | Role |
|---|---|
| input-space-construction | Stage 1 — build input spaces |
| generic-space-extraction | Stage 2 — extract shared structure |
| blend-composition | Stage 3 — compose blended space |
| blend-completion | Post-Stage 3 — recruit background knowledge |
| vital-relation-mapping | Pre-Stage 1 — map vital relations to guide projection |
Signals
- GitHub stars
- 469
- Forks
- 37
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
blend-construction- Source
- github.com/yogsoth-ai/de-anthropocentric-research-engine