eigenvalues
Provides tools and strategies for solving linear algebra eigenvalue problems.
Install
mkdir -p .claude/skills/eigenvalues && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/1943" && unzip -o skill.zip -d .claude/skills/eigenvalues && rm skill.zipInstalls to .claude/skills/eigenvalues
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Problem-solving strategies for eigenvalues in linear algebraKey capabilities
- →Compute characteristic polynomials
- →Calculate eigenvalues for matrices
- →Find eigenvectors for given eigenvalues
- →Verify matrix operations using Z3
How it works
The skill utilizes Sympy for symbolic computation of polynomials and eigenvalues, and Z3 for verifying the correctness of the results.
Inputs & outputs
When to use eigenvalues
- →Calculating eigenvalues
- →Finding eigenvectors
- →Verifying matrix operations
About this skill
Eigenvalues
When to Use
Use this skill when working on eigenvalues problems in linear algebra.
Decision Tree
-
Compute Characteristic Polynomial
- det(A - lambda*I) = 0
sympy_compute.py charpoly "[[a,b],[c,d]]" --var lam
-
Find Eigenvalues
- Solve characteristic polynomial
sympy_compute.py eigenvalues "[[1,2],[3,4]]"
-
Find Eigenvectors
- For each eigenvalue lambda: solve (A - lambda*I)v = 0
sympy_compute.py eigenvectors "[[1,2],[3,4]]"
-
Verify
- Check Av = lambda*v with
z3_solve.py prove - Verify algebraic/geometric multiplicity
- Check Av = lambda*v with
Tool Commands
Sympy_Eigenvalues
uv run python -m runtime.harness scripts/sympy_compute.py eigenvalues "[[1,2],[3,4]]"
Sympy_Charpoly
uv run python -m runtime.harness scripts/sympy_compute.py charpoly "[[a,b],[c,d]]" --var lam
Z3_Verify
uv run python -m runtime.harness scripts/z3_solve.py sat "det(A - lambda*I) == 0"
Cognitive Tools Reference
See .claude/skills/math-mode/SKILL.md for full tool documentation.
When not to use it
- →Non-linear algebra mathematical problems
- →Large-scale numerical matrix inversion
Limitations
- →Limited to linear algebra applications
- →Symbolic computation complexity increases with matrix size
How it compares
It provides a programmatic, verifiable approach to linear algebra problems instead of manual calculation.
Compared to similar skills
eigenvalues side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| eigenvalues (this skill) | 2 | 8mo | Review | Intermediate |
| data-engineering | 13 | 9mo | Review | Advanced |
| crawl4ai | 21 | 10mo | Review | Intermediate |
| data-cleaning-pipeline | 13 | 7mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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