Best use case
matrices is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Problem-solving strategies for matrices in linear algebra
Teams using matrices should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/matrices/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How matrices Compares
| Feature / Agent | matrices | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Problem-solving strategies for matrices in linear algebra
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Matrices ## When to Use Use this skill when working on matrices problems in linear algebra. ## Decision Tree 1. **Identify Matrix Type** - Square, symmetric, orthogonal, diagonal? - Check properties with `sympy_compute.py matrix_type` 2. **Basic Operations** - Multiplication: `sympy_compute.py matmul "A" "B"` - Inverse: `sympy_compute.py inverse "A"` - Transpose: `sympy_compute.py transpose "A"` 3. **Solve Linear Systems** - Ax = b: `sympy_compute.py linsolve "A" "b"` - Check consistency with `z3_solve.py sat` 4. **Decompositions** - LU: `sympy_compute.py lu "A"` - QR: `sympy_compute.py qr "A"` - SVD: `sympy_compute.py svd "A"` ## Tool Commands ### Sympy_Inverse ```bash uv run python -m runtime.harness scripts/sympy_compute.py inverse "[[1,2],[3,4]]" ``` ### Sympy_Det ```bash uv run python -m runtime.harness scripts/sympy_compute.py det "[[a,b],[c,d]]" ``` ### Sympy_Linsolve ```bash uv run python -m runtime.harness scripts/sympy_compute.py linsolve "[[1,2],[3,4]]" "[5,6]" ``` ## Cognitive Tools Reference See `.claude/skills/math-mode/SKILL.md` for full tool documentation.
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