hep-workflow
NewA skill-based agent workflow for high-energy physics phenomenology: from model proposal through symbolic calculation to numerical scans and publication-oriented exclusion plots.
Summary
This skill automates the end-to-end workflow of high-energy physics phenomenology, from proposing a new model and performing symbolic calculations to running numerical scans and generating publication-ready exclusion plots.
- It helps developers and researchers streamline repetitive tasks and maintain reproducibility across the analysis pipeline.
Install & Usage
mkdir -p .claude/agentsAdd the configuration to .claude/agents/hep-workflow.md
@hep-workflowUse Cases
Usage Examples
/hep-workflow propose model 'SUSY with RPV' and generate Lagrangian
/hep-workflow scan parameters m0=100..1000, m12=200..2000 and produce exclusion plot against LHC data
/hep-workflow compute cross-section for pp -> stop stop at 13 TeV using model file model.ufo
Security Audits
Frequently Asked Questions
What is hep-workflow?
This skill automates the end-to-end workflow of high-energy physics phenomenology, from proposing a new model and performing symbolic calculations to running numerical scans and generating publication-ready exclusion plots. It helps developers and researchers streamline repetitive tasks and maintain reproducibility across the analysis pipeline.
How to install hep-workflow?
To install hep-workflow: create the agents directory (mkdir -p .claude/agents), then add the config to .claude/agents/hep-workflow.md. Finally, @hep-workflow in Claude Code.
What is hep-workflow best for?
hep-workflow is a agent categorized under General. It is designed for: agent. Created by huangzhonglv.
What can I use hep-workflow for?
hep-workflow is useful for: Propose a new BSM model and automatically generate its Lagrangian and Feynman rules.; Perform symbolic cross-section calculations for a given process using FeynArts and FormCalc.; Run a numerical parameter scan over a model's parameter space and compute observables.; Generate an exclusion plot comparing model predictions against experimental limits.; Automate the workflow from model definition to final plot for a specific benchmark scenario.; Validate a model by checking unitarity and perturbativity constraints across the parameter space..