flowio
Parse FCS Flow Cytometry Files
Flow cytometry FCS files are hard to inspect, convert, and validate consistently. FlowIO guides Claude, Codex, and Claude Code through parsing, metadata extraction, CSV conversion, and FCS export.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "flowio" from https://skillstore.io/skills/k-dense-ai-flowio.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-flowio/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "flowio". Inspect a new sample.fcs file before analysis.
Expected outcome:
- Reports the FCS version, event count, channel count, and channel labels.
- Lists acquisition date, instrument name, and relevant TEXT metadata.
- States whether event data was loaded or metadata-only mode was used.
Using "flowio". Convert a cytometry run into a tabular file.
Expected outcome:
- Creates a CSV with one column per channel label.
- Preserves a short summary of source metadata for traceability.
- Notes whether FlowIO preprocessing was applied during extraction.
Using "flowio". Review a folder of FCS files for pipeline readiness.
Expected outcome:
- Summarizes each file by version, event count, channel count, and parsing status.
- Flags multi-dataset files and offset discrepancies for separate handling.
- Recommends memory-aware loading for large event datasets.
Security Audit
Low RiskThe static execution and reconnaissance alerts are false positives caused by Markdown formatting, normal Python examples, and API reference prose. No evidence found of hidden command execution, credential access, network exfiltration, or prompt-injection text that tries to bypass the audit. A low-severity semantic issue remains because the skill includes an unrelated promotional instruction for the author's hosted service.
Confirmed security concerns (1)
Risk Factors
⚡ Contains scripts (1)
⚙️ External commands (66)
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<iframe src="https://skillstore.io/embed/skills/k-dense-ai-flowio.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
K-Dense-AI. (2026). flowio security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-flowio/audits/7BibTeX citation
@techreport{k-dense-ai-k-dense-ai-flowio-2026,
author = {K-Dense-AI},
title = {flowio security audit report (audit version 7)},
institution = {Skillstore},
year = {2026},
number = {7},
url = {https://skillstore.io/skills/k-dense-ai-flowio/audits/7},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "flowio security audit report (audit version 7)"
version: "unspecified"
type: report
authors:
- name: "K-Dense-AI"
date-released: "2026-07-06"
url: "https://skillstore.io/skills/k-dense-ai-flowio/audits/7"
identifiers:
- type: other
value: "skillstore:k-dense-ai-flowio:audit:7"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
davila7-flowio
2026-09-09
k-dense-ai-flowio
2026-09-09
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Prepare Cytometry Data for Analysis
Inspect FCS files, extract event arrays, and export clean CSV tables before downstream analysis.
Automate FCS Metadata Inventory
Scan experiment folders and summarize instrument, acquisition, channel, and event metadata.
Add FCS Support to Applications
Use FlowIO patterns to parse uploads, validate files, and write FCS outputs in backend services.
Try These Prompts
Use FlowIO to inspect [file path]. Report FCS version, event count, channel count, channel labels, and key metadata. Do not load events unless needed.
Use FlowIO to convert [file path] to CSV. Preserve channel names as columns, include a short metadata summary, and note preprocessing settings.
Use FlowIO to parse [file path] with suitable offset handling. Explain the exception, the relaxed option used, and any data quality caveats.
Use FlowIO to design a batch workflow for [directory]. Extract metadata for all FCS files, detect multi-dataset files, convert selected events, and write a validation report.
Best Practices
- Use metadata-only parsing when event data is not required.
- Set preprocessing options explicitly before comparing transformed and raw values.
- Preserve original TEXT metadata when creating modified FCS files.
Avoid
- Loading every event array when only metadata is needed.
- Ignoring multi-dataset errors and treating the file as a single dataset.
- Mixing raw and preprocessed values in the same analysis without labels.
Frequently Asked Questions
What file format does this skill handle?
Can it export FCS data to CSV?
Does it support advanced cytometry analysis?
Can it create new FCS files?
How does it handle large files?
Which AI tools can use it?
Developer Details
Author
K-Dense-AILicense
BSD-3-Clause license
Skillstore revision
r1
Version notice
The author did not declare a version.
Repository
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/flowioRef
b8ca75d2c0a7e7102978993058777d82b8ab2610
Maintenance freshness
7/18/2026
Usage
11 downloads · 201 views
File structure