yogsoth-ai Matrix Generation
Generate combination matrices by crossing dimensions. Populate cells with existing work, mark empty cells as opportunities, flag impossible combinations.
Available SOPs
- combination-enumeration — systematically enumerate all combinations
- novelty-scoring — score empty cells by novelty potential
- question-generation — generate research questions from promising gaps
- matrix-export — export matrix as readable document
Guiding Principles
- Start 2D. Begin with pairs of dimensions before attempting higher-dimensional matrices.
- Sparse is normal. Most real design spaces are sparsely populated — that's the point.
- Impossible ≠ unexplored. Mark truly impossible combinations (physical constraints, logical contradictions) differently from merely unexplored ones.
- Cluster patterns. Look for patterns in which cells are populated — they reveal community preferences and blind spots.
Minimum Yield
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| combination-enumeration | SOP for systematically enumerating combinations across dimensions. |
| knowledge-structuring-novelty-scoring | SOP for scoring empty cells by novelty potential — how surprising and valuable would this combination be? |
| matrix-export | SOP for exporting the dimensional matrix as a readable document or structured data. |
| question-generation | SOP for generating research questions from promising gaps in the design space. |