Analyze QFT RunHistory results to calibrate parameters and validate against Standard Model constants.
npx skills add https://github.com/FragileTech/fragile --skill qft-analysis
Please help me install this Agent Skill. Skill: qft-analysis Source: https://github.com/FragileTech/fragile/tree/main/.claude/skills/qft-analysis Command: npx skills add https://github.com/FragileTech/fragile --skill qft-analysis
The QFT Analysis Skill orchestrates a complete workflow to parse RunHistory data, calibrate algorithmic parameters, and validate results against Standard Model constants, enabling reproducible QA for QFT simulations.
Run an analysis on a RunHistory file to trigger calibration, analysis, and reporting, then review outputs in the specified directories.
High-intent search queries and answers about installing and using this skill.
Yes, you can analyze multiple RunHistory files to perform multi-run comparisons and quality assessments. The Skill orchestrates calibration and reporting across different anchors and histories, generating structured comparison reports for reproducible QA.
You need existing QFT RunHistory data files containing particle masses and field correlations. The Skill orchestrates existing Python scripts to load these results, perform multi-anchor calibration, and produce structured reports with quality assessments in specified output directories.
The Skill supports custom mass-scale anchors alongside the default electron, Z boson, and tau references. You can calibrate algorithmic parameters and validate field correlations using your specific anchor choices to suit your QFT simulation requirements.
The Skill validates QFT simulation results by applying multiple mass-scale anchors to calibrate algorithmic parameters and comparing the resulting particle masses against Standard Model constants. It then generates comprehensive reports with quality assessments for reproducible QA.
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