matrix-generation

name	matrix-generation
description	Tactic for generating and populating combination matrices — cross dimensions to enumerate the design space.
execution	tactic
dependencies	{"sops":["combination-enumeration","knowledge-structuring-novelty-scoring","matrix-export","question-generation"]}

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

≥1 matrix generated with ≥50% of cells classified (occupied/empty/impossible) per invocation.

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.