Automate parametric simulation sweeps with variable substitution and output parsing.
npx skills add https://github.com/Funz/fz --skill fz
Please help me install this Agent Skill. Skill: fz Source: https://github.com/Funz/fz/tree/main/skills/fz Command: npx skills add https://github.com/Funz/fz --skill fz
This Skill automates the execution of parametric simulation studies by wrapping existing simulation codes, managing input parameter sweeps, and parsing output files into structured data.
Use the fz skill to run a parametric study on input.txt by defining your variables and executing the simulation across your chosen calculator.
High-intent search queries and answers about installing and using this skill.
Automating parametric simulation studies requires wrapping existing command-line tools to perform variable substitution, parallel execution, and output parsing into structured data. This Skill manages input parameter sweeps and collects results into pandas DataFrames for immediate analysis.
Yes, parametric sweeps can execute locally, via SSH, or on SLURM clusters. Built-in parallelization and retry logic handle high-performance computing environments, managing the input-output file lifecycle across remote execution platforms.
Running a design of experiments requires a configured model definition and a compatible simulation executable. You must define your variables and provide the input files so the automation can manage variable substitution and collect structured outputs.
Simulation output parsing works by collecting results from executed cases and structuring them into pandas DataFrames. This enables immediate sensitivity, optimization, or uncertainty analysis without manual data extraction from individual output files.
Factorial design execution for scientific computing workflows is handled by defining variables and executing the simulation across a chosen calculator. The automation manages parallel execution and input-output file lifecycle for large-scale parametric studies.
Automation for parametric studies eliminates manual variable substitution and file management. It enables parallel execution across local and remote high-performance computing environments, parsing outputs into structured DataFrames for immediate sensitivity and optimization analysis.
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