agentleFS
Sign inStart free
yogsoth-aiyogsoth-ai/knowledge-structuring/skills/matrix-generation/SKILL.md

matrix-generation

Skill2 starsChanged 6 months agoApache-2.0View on GitHub

Tactic for generating and populating combination matrices — cross dimensions to enumerate the design space.

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Cluster patterns: Look for patterns in which cells are populated — they reveal community preferences and blind spots.

    line 24

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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

<HARD-GATE> ≥1 matrix generated with ≥50% of cells classified (occupied/empty/impossible) per invocation. </HARD-GATE>

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free