scikit-hep-analysis
Scikit-HEP toolkit skill for particle physics data analysis with modern Python tools
Profile →npx skills add a5c-ai/babysitter --skill scikit-hep-analysis --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.
# Scikit-HEP Analysis ## Purpose Provides expert guidance on the Scikit-HEP ecosystem for particle physics data analysis with modern Python tools. ## Capabilities - Awkward array manipulation - uproot ROOT file I/O - Histogram operations (hist, boost-histogram) - Particle data access - Vector operations - pyhf statistical modeling ## Usage Guidelines 1. **Data I/O**: Read ROOT files with uproot 2. **Arrays**: Manipulate jagged data with Awkward 3. **Histogramming**: Create and manipulate histograms with hist 4. **Statistics**: Use pyhf for statistical modeling 5. **Analysis**: Build complete analysis workflows ## Tools/Libraries - scikit-hep - awkward - uproot - hist - pyhf
- Purpose
- Capabilities
- Usage Guidelines
- Tools/Libraries
What does the scikit-hep-analysis skill do?
Scikit-HEP toolkit skill for particle physics data analysis with modern Python tools
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill scikit-hep-analysis --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.