A quality check for raw single-cell RNA sequencing FASTQ files, which contain the sequencing reads before they are converted into gene counts. It summarises read quality, GC content, adapters, and read length.

Use it to inspect individual files or sample collections and generate per-base, per-file, and overall quality reports.

It can reveal poor reads or technical problems before the data is counted and analysed.

sc-fastq-qc — Skill for Claude Code and Codex by TianGzlab

Install

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.

Any agent

npx skills add TianGzlab/OmicsClaw --skill sc-fastq-qc

Clone the repo

git clone --depth 1 https://github.com/TianGzlab/OmicsClaw

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-fastq-qc/github.svg)](https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-fastq-qc)

Your own site

<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-fastq-qc"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-fastq-qc/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-fastq-qc"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-fastq-qc.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,111 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

high Rogue Agent · line 3
Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.

Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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	$0.00053	$0.01111
Opus 5	$0.00026	$0.00556
Sonnet 5	$0.00011	$0.00222
Haiku 4.5	$0.00005	$0.00111

Measured 6d ago against content hash 88a59c95dab8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

sc-fastq-qc 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 6d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (sc_fastq_qc.py, tests/test_sc_fastq_qc.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/singlecell/scrna/sc-fastq-qc/SKILL.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

sc-fastq-qc

When to use

The user has raw scRNA-seq FASTQ files (one or more, or a directory of samples) and wants per-file / per-sample / per-base quality summaries before running sc-count or cellranger. Uses FastQC + MultiQC when those tools are installed; falls back to a stable Python-only summary otherwise so the skill always returns something useful.

Inputs & Outputs

Inputs

Input kinds: file, directory
Modalities: scrna
File types: .fastq, .fq
FASTQ structure: valid first record
Directory layouts (any): fastq-collection

Outputs

tables/Summary.csv
tables/barcodes.tsv
tables/fastq_per_base_quality.csv
tables/fastq_per_file_summary.csv
tables/fastq_per_sample_summary.csv
tables/features.tsv
tables/genes.tsv
tables/metrics_summary.csv
figures/fastq_file_quality.png
figures/fastq_q30_summary.png
figures/fastq_read_structure.png
figures/per_base_quality.png
3M-february-2018.txt
737K-august-2016.txt
Aligned.sortedByCoord.out.bam
multiqc_report.html
possorted_genome_bam.bam
web_summary.html
report.md
result.json

Flow

Discover FASTQ files from --input (single file or directory).
If fastqc is on $PATH, run it; if multiqc is on $PATH, run that too.
In parallel run a Python-only fallback that samples up to --max-reads per FASTQ for Phred / GC / adapter / length.
Merge tool output + fallback into per-file / per-sample / per-base tables.
Render quality + adapter / GC diagnostic figures.
Emit report.md + result.json.

Gotchas

--max-reads 20000 (default) caps the Python-fallback path only. When FastQC is available the full FASTQ is processed; when not, only the first 20K reads per file are sampled. Sampling depth is recorded per file in tables/fastq_per_file_summary.csv; bump --max-reads if a FASTQ has high variance across the file.
--r-enhanced is accepted but produces no R plots. This skill emits Python figures only. Pass freely, expect no R Enhanced output.
Per-figure status: "rendered" is local, not global. The result.json carries a status field per figure (e.g. figures.per_base_quality.status == "rendered"). All four panels are emitted unconditionally (sc_fastq_qc.py:430-433), so absence of an entry typically means upstream tool failure rather than a configuration choice — inspect summary.warnings before assuming a panel was suppressed.

Read the full file on GitHub · 108 lines

Files

What ships with it

7 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.

Changes

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.

6d ago First seen · 108 lines · 53 tokens per session scan A 88a59c95dab8

Subscribe to this mod's changes

sc-fastq-qc is a skill published in the GitHub repository TianGzlab/OmicsClaw (160 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 53 tokens to every session and 1,111 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

FASTQ Scientific Single-Cell bioinformatics knowledge-graph llm-agent multi-agents multi-omics qc read-quality scrna singlecell

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sc-fastq-qc

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

sc-fastq-qc

When to use

Inputs & Outputs

Flow

Gotchas

What ships with it

What this file has done since we first saw it

Other skills, from other repositories

Single-Cell Analysis Skills Index

scanpy

Virtual Embryo — atlas data + knowledge graph

cellxgene-census-query

single-cell-scrna-seq-analysis-scanpy

single-cell-multi-omics-analysis-scvi