scikit-hep-analysis
Scikit-HEP toolkit skill for particle physics data analysis with modern Python tools
Best use case
scikit-hep-analysis is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Scikit-HEP toolkit skill for particle physics data analysis with modern Python tools
Teams using scikit-hep-analysis should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/scikit-hep-analysis/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How scikit-hep-analysis Compares
| Feature / Agent | scikit-hep-analysis | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Scikit-HEP toolkit skill for particle physics data analysis with modern Python tools
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# 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
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