Agent skill · research science · k-dense-ai
flowio
Read, inspect, and write Flow Cytometry Standard (FCS) 2.0, 3.0, and 3.1 files with FlowIO. Use for low-level FCS metadata and channel inspection, NumPy event extraction, multi-dataset files, table export, and FCS 3.1 creation; use FlowKit for compensation, cytometry transforms, gating, or FlowJo workspaces.
Why this skill is useful
Provides specific commands and workflows for reading and writing Flow Cytometry Standard files that the AI wouldn't reliably generate on its own.
What it needs
Requires flowio, numpy, uv installed locally. About 6k tokens when loaded. Last updated 2026-08-03. 32,849 stars on the source repository.
What this skill does
FlowIO Purpose Use FlowIO as a lightweight, low-level reader and writer for Flow Cytometry Standard files. Examples in this skill target FlowIO 1.4.0, the current stable release verified on 2026-07-23. FlowIO is appropriate for: Reading FCS 2.0, 3.0, and 3.1 files Inspecting HEADER, TEXT, ANALYSIS, and channel metadata Retrieving event data as a two-dimensional NumPy array Reading legacy files that contain multiple datasets Writing list-mode, single-precision FCS 3.1 files Preparing data for pandas, machine-learning, or downstream cytometry tools FlowIO does not perform compensation, logicle/biexponential transforms, gating, clustering, or FlowJo workspace processing. Use FlowKit or another analysis package for those tasks. Install Create or activate a Python environment, then install the verified release: Confirm the runtime version: FlowIO 1.4.0 supports Python 3.9 through 3.13 and depends on NumPy. Operating Workflow 1. Clarify the operation. Distinguish metadata inventory, event extraction, file repair, conversion, and downstream biological analysis. 2. Inspect before loading events. Use onlytext=True for metadata-only work, especially with large or unfamiliar files. 3. Choose event semantics explicitly. Use asarray(preprocess=True) for gain/log/time scaling from FCS metadata, or preprocess=False for values as encoded in the DATA segment. Record the choice. 4. Keep parsing strict by default. Do not automatically suppress offset errors. Relax checks only for a known vendor-format defect, and review the resulting event data. 5. Treat metadata as potentially sensitive. FCS TEXT values can include sample, subject, operator, and instrument identifiers. Export only fields needed for the task. 6. Validate writes by reopening them. Check event/channel counts, labels, metadata, and representative values after any FCS export. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills k-dense-ai/flowio