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.
npx skills add K-Dense-AI/scientific-agent-skills --skill flowio --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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: ```bash uv pip install "flowio==1.4.0" ``` Confirm the runtime version: ```bash uv run python -c "import flowio; print(flowio.__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
- Purpose
- Install
- Operating Workflow
- Critical Semantics
- TEXT keys are normalized
- Events have two representations
- Channel numbering uses two conventions
- Writing is intentionally limited
- Quick Start: Read an FCS File
- Quick Start: Read Multiple Datasets
- Quick Start: Create an FCS 3.1 File
- Copy or Rewrite an Existing File
- Bundled Inspector
- References
uv pip install "flowio==1.4.0" uv run python -c "import flowio; print(flowio.__version__)" Metadata and channel inventory uv run --no-project --with "flowio==1.4.0" \ python "$FLOWIO_SKILL_DIR/scripts/inspect_fcs.py" sample.fcs Include all normalized TEXT metadata; review output for identifiers python "$FLOWIO_SKILL_DIR/scripts/inspect_fcs.py" sample.fcs --include-text Load events and compute finite-value statistics using FlowIO preprocessing python "$FLOWIO_SKILL_DIR/scripts/inspect_fcs.py" sample.fcs --stats Compute statistics from encoded values instead
What does the flowio skill do?
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.
How do I install it?
Run `npx skills add K-Dense-AI/scientific-agent-skills --skill flowio --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From K-Dense-AI/scientific-agent-skills, a repository with 32,619 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.