Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add agentlas-ai/agentlas-desktop --skill flowiogit clone --depth 1 https://github.com/agentlas-ai/agentlas-desktopWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/flowio)<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/flowio"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/flowio/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/flowio"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/flowio.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00088 | $0.02920 |
| Opus 5.5 | $0.00035 | $0.01168 |
| Sonnet 5.5 | $0.00018 | $0.00584 |
| Haiku 4.5 | $0.00009 | $0.00292 |
Grade A, and why
flowio scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
89% identical to flowio — 47 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 328 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
uv pip install "flowio==1.4.0"
Confirm the runtime version:
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
- Clarify the operation. Distinguish metadata inventory, event extraction, file repair, conversion, and downstream biological analysis.
- Inspect before loading events. Use
only_text=Truefor metadata-only work, especially with large or unfamiliar files. - Choose event semantics explicitly. Use
as_array(preprocess=True)for gain/log/time scaling from FCS metadata, orpreprocess=Falsefor values as encoded in the DATA segment. Record the choice. - 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.
- Treat metadata as potentially sensitive. FCS TEXT values can include sample, subject, operator, and instrument identifiers. Export only fields needed for the task.
- Validate writes by reopening them. Check event/channel counts, labels, metadata, and representative values after any FCS export.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 328 lines · 88 tokens per session scan A 69e87a334078
flowio is a skill published in the GitHub repository agentlas-ai/agentlas-desktop (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 88 tokens to every session and 2,920 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to flowio, differing in 47 lines, and is treated as a copy.
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