raman-fitting
This skill provides guidance for fitting peaks in Raman spectroscopy data, particularly for materials like graphene. Use this skill when tasks involve Raman spectrum analysis, peak fitting (G peak, 2D peak, D peak), or spectroscopic curve fitting using Lorentzian, Gaussian, or Voigt functions.
npx skills add majiayu000/claude-skill-registry --skill raman-fitting-letta-ai-skills-2 --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.
# Raman Spectrum Peak Fitting ## Overview This skill provides procedural knowledge for fitting peaks in Raman spectroscopy data. Raman spectroscopy is commonly used to characterize materials like graphene, carbon nanotubes, and other crystalline structures. Proper peak fitting requires understanding both the physics of Raman scattering and robust numerical fitting techniques. ## Critical First Step: Data Exploration Before any fitting attempts, perform comprehensive data exploration to avoid fundamental misinterpretations: ### 1. Verify Data Format - Examine file structure carefully (delimiters, column separators, row numbering) - Check for locale-specific number formats (e.g., `47183,554644` may use comma as decimal separator) - Identify whether columns represent wavenumber, wavelength, or require conversion - Look for header rows or metadata that may affect parsing ### 2. Assess Data Range and Quality - Determine the wavenumber range covered by the dataset - Check if expected peak positions fall within the data range - Identify noise levels and baseline characteristics - Plot the entire spectrum before attempting any fits ### 3. Compare Against Expected Values For graphene Raman
- Overview
- Critical First Step: Data Exploration
- 1. Verify Data Format
- 2. Assess Data Range and Quality
- 3. Compare Against Expected Values
- Peak Fitting Workflow
- Step 1: Background Subtraction
- Step 2: Select Appropriate Peak Function
- Step 3: Define Fitting Region
- Step 4: Set Physical Constraints
- Step 5: Execute Fit and Validate
- Fit Quality Validation
- Metrics to Check
- Warning Signs of Fit Failure
What does the raman-fitting skill do?
This skill provides guidance for fitting peaks in Raman spectroscopy data, particularly for materials like graphene. Use this skill when tasks involve Raman spectrum analysis, peak fitting (G peak, 2D peak, D peak), or spectroscopic curve fitting using Lorentzian, Gaussian, or Voigt functions.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill raman-fitting-letta-ai-skills-2 --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 majiayu000/claude-skill-registry, a repository with 534 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.