linear-algebra-applications
Apply linear algebra concepts to research computing and data analysis
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill linear-algebra-applications --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Applied Linear Algebra for Research A skill for applying linear algebra to research computing, data analysis, and scientific modeling. Covers matrix decompositions, eigenvalue problems, least squares, dimensionality reduction, and practical implementation in NumPy/SciPy. ## Essential Operations ### Matrix Multiplication and Solving Systems ```python import numpy as np from scipy import linalg de
What does the linear-algebra-applications skill do?
Apply linear algebra concepts to research computing and data analysis
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill linear-algebra-applications --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.