Agent skill

interpolation

Problem-solving strategies for interpolation in numerical methods

parcadei3,879★ · 1 repos on radarProfile →
claude-codecan modify filesMIT
Install
npx skills add parcadei/Continuous-Claude-v3 --skill interpolation --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 4 KB
Bundled scripts: none
Allowed tools: BashRead
Path: .claude/skills/math/numerical-methods/interpolation/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 3,879
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Interpolation ## When to Use Use this skill when working on interpolation problems in numerical methods. ## Decision Tree 1. **Assess Data Characteristics** - How many data points? Spacing uniform or non-uniform? - Is data smooth or noisy? - Need derivatives at endpoints? 2. **Select Interpolation Method** - Few points (<10): Polynomial (Lagrange, Newton) - Many points, smooth data: Cubic splines - Noisy data: Smoothing splines or least squares - High dimensions: Use simplex-based (n+1 neighbors vs 2^n) 3. **Implement with SciPy** - `scipy.interpolate.CubicSpline(x, y)` - natural cubic spline - `scipy.interpolate.make_interp_spline(x, y, k=3)` - B-spline - `scipy.interpolate.interp1d(x, y, kind='cubic')` - 1D interpolation 4. **Validate Results** - Check for Runge's phenomenon at boundaries (high-degree polynomials) - Cross-validate: leave-one-out error estimation - Visual inspection of interpolated curve - `sympy_compute.py limit "interp_error" --at boundaries` 5. **High-Dimensional Considerations** - Coxeter-Freudenthal-Kuhn triangulation for O(n log n) point location - Barycentric subdivision for balanced performance ## Tool Commands ### Scipy_Cubic_Spline ```bash uv run pytho

What's inside
Steps it walks through
  1. When to Use
  2. Decision Tree
  3. Tool Commands
  4. ScipyCubicSpline
  5. ScipyBspline
  6. SympyLagrange
  7. Key Techniques
  8. Cognitive Tools Reference
Commands it runs
uv run python -m runtime.harness scripts/sympy_compute.py interpolate "[(0,0),(1,1),(2,4)]" --var x
More from Continuous-Claude-v3
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About this skill
What does the interpolation skill do?

Problem-solving strategies for interpolation in numerical methods

How do I install it?

Run `npx skills add parcadei/Continuous-Claude-v3 --skill interpolation --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 parcadei/Continuous-Claude-v3, a repository with 3,879 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.

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