Agent skill · Data & Analytics

root-data-analyzer

ROOT/CERN data analysis skill for high-energy physics data processing, histogramming, and statistical analysis

a5c-ai1,642★ · 1 repos on radarProfile →
claude-codecodexcan modify filesMIT
Install
npx skills add a5c-ai/babysitter --skill root-data-analyzer --agent claude-code

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

Facts
Files in the skill folder: 1
SKILL.md size: 1 KB
Bundled scripts: none
Allowed tools: -Bash-Read-Write-Edit-Glob-Grep
Path: library/specializations/domains/science/physics/skills/root-data-analyzer/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,642
Language: JavaScript

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

From the SKILL.md

# ROOT Data Analyzer ## Purpose Provides expert guidance on ROOT data analysis for high-energy physics, including TTree manipulation, histogram fitting, and statistical modeling with RooFit. ## Capabilities - TTree/TChain manipulation - Histogram creation and fitting - RooFit statistical modeling - TCanvas visualization - ROOT macro development - PyROOT integration ## Usage Guidelines 1. **Data Access**: Use TTree and TChain for efficient data access 2. **Histogramming**: Create and fill histograms with proper binning 3. **Fitting**: Use RooFit for advanced statistical modeling 4. **Visualization**: Create publication-quality plots with TCanvas 5. **Python Integration**: Use PyROOT for Python-based analysis ## Tools/Libraries - ROOT - RooFit - RooStats - uproot

What's inside
Steps it walks through
  1. Purpose
  2. Capabilities
  3. Usage Guidelines
  4. Tools/Libraries
More from babysitter
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About this skill
What does the root-data-analyzer skill do?

ROOT/CERN data analysis skill for high-energy physics data processing, histogramming, and statistical analysis

How do I install it?

Run `npx skills add a5c-ai/babysitter --skill root-data-analyzer --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 a5c-ai/babysitter, a repository with 1,642 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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