If you're working with flow cytometry data and need to parse FCS files without pulling in heavy analysis frameworks, this handles versions 2.0 through 3.1 cleanly. It reads metadata and event data into NumPy arrays, writes modified FCS files back out, and includes practical flags for dealing with broken offset headers that show up in real lab data. The library separates scatter, fluorescence, and time channels automatically, which saves you from parsing channel names yourself. It's deliberately lightweight, so if you need compensation matrices or gating logic, you'll want FlowKit alongside it. Good fit for ETL pipelines or preprocessing steps before handing data off to analysis tools.
npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill flowio