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 TianGzlab/OmicsClaw --skill sc-fastq-qcgit clone --depth 1 https://github.com/TianGzlab/OmicsClawWrote 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/tiangzlab/omicsclaw/sc-fastq-qc)<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.
<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>- NVIDIA SkillSpector warn
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.
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 | $0.01100 |
| Opus 5.5 | $0.00021 | $0.00440 |
| Sonnet 5.5 | $0.00011 | $0.00220 |
| Haiku 4.5 | $0.00005 | $0.00110 |
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 17d 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.
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sc-fastq-qc
Use from a step
This is CLI_ONLY: it reads FASTQ files and optionally starts FastQC/MultiQC.
from skills._sdk.notebook import run_cli
run_cli("sc-fastq-qc", "--input", "data/sample_R1.fastq.gz",
"--read2", "data/sample_R2.fastq.gz",
inputs=["data/sample_R1.fastq.gz", "data/sample_R2.fastq.gz"])
The demo renders synthetic summary tables; it does not read FASTQ or test
the external tools. There is no _api.py for this skill.
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. Python summaries always run.
FastQC and MultiQC add reports when installed; a tool that is present but
fails is a hard error, not a fallback to a successful Python-only run.
Inputs & Outputs
Inputs
- Input kinds:
file,directory - Modalities: scrna
- File types:
.fastq,.fq, and their.gzvariants - FASTQ structure: valid first record
- Directory layouts (any):
fastq-collection
Outputs
tables/fastq_per_base_quality.csvtables/fastq_per_file_summary.csvtables/fastq_per_sample_summary.csvfigures/fastq_file_quality.pngfigures/fastq_q30_summary.pngfigures/fastq_read_structure.pngfigures/per_base_quality.pngfigures/manifest.json,figure_data/manifest.json, plot-data CSV filesreproducibility/commands.sh,reproducibility/requirements.txt- Optional external reports under
artifacts/fastqc/andartifacts/multiqc/ report.mdresult.json
Flow
- Discover FASTQ files and choose one sample (
--sampledisambiguates a directory). - Summarize the first
--max-readsrecords per file in Python. - Run FastQC when present, then MultiQC when both tools are present.
- Render four figures from the Python summaries; external HTML is separate.
- Write three tables,
report.mdandresult.json.
Gotchas
--max-reads 20000caps Python summaries only.tables/fastq_per_file_summary.csvrecords sampled depth. FastQC processes the full files. This is a prefix sample, not random sampling.--r-enhancedis accepted but produces no R plots. This skill emits Python figures only. Pass freely, expect no R Enhanced output.figures/manifest.jsonrecords per-figure status;result.jsonlists external tool availability and commands underdata.external_tools._lib/upstream.py:choose_fastq_samplerejects ambiguous multi-sample directories. Run once per sample with--sample; one invocation does not batch every sample.
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.
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.
- 17d ago Changed · -2 lines b869c908948a
- 1mo ago First seen · 108 lines · 53 tokens per session scan A 88a59c95dab8
sc-fastq-qc is a skill published in the GitHub repository TianGzlab/OmicsClaw (161 stars, last pushed 17d ago), licensed Apache-2.0. It adds 53 tokens to every session and 1,100 once invoked, about $0.0002 per session on Opus 5.5. 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.
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