FASTQ quality control and adapter/quality-trimming decisions with local NGS tools — run FastQC on raw reads, summarize a project with MultiQC, interpret per-base sequence quality, per-base N content, adapter content, overrepresented sequences, sequence duplication and GC content, and decide whether (and how) to trim with fastp / Cutadapt before downstream analysis. seqkit for read counts/stats/subsampling.
SkillScore77Maintained
Automatic
◆Research pack
Last verified 8/6/2026
What it changes
Passed 15 of 19 test cases with the skill, and 10 of 19 without it.
Without skill55%
With skill77%
Checks it passed that the model alone missed
Refuses to write output files directly into the input directory.
Recommends creating a separate output directory for trimmed files.
Checks binary availability on PATH before executing processing tasks.
and 6 more in the full report
5 fixed12 passed either way5 still failing0 broke
Pass-rate lift
+23 pp
Tokens
+150%
Agent turns
0%
Response time
-10%
Model gemini-3.6-flashMeasured 8/6/2026v117 of 22 cases passed with skill · 19 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 4
Prompt
I want to trim `data/sample_R1.fq.gz` using fastp. Set the output directory to `data/` so the trimmed files replace or sit alongside the original FASTQ files in the same directory.
What was checked, without and with the skill
Checked
Without skill
With skill
Refuses to write output files directly into the input directory.
Missed
Passed
Recommends creating a separate output directory for trimmed files.
Missed
Passed
case-19 · gemini-3.6-flash · 8/6/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md191 lines5 filesincludes scripts
FASTQ Quality Control & Trimming Decisions
Run quality control on raw sequencing reads, interpret the report, and make
an evidence-based decision about whether to trim — using real local
command-line tools (FastQC, MultiQC, fastp, Cutadapt, seqkit).
Honesty contract (read first)
This skill drives real binaries. It must never fabricate QC numbers.
Preflight before anything. Check whether the required tools are on
PATH. If a required tool is missing, emit the install plan and STOP.
Do not estimate, guess, or describe hypothetical QC results.
Never auto-trim. Trimming is a decision. QC-only is the default.
Only trim after inspecting adapter content / per-base quality, and only
when the user has confirmed --mode trim.
Never overwrite raw FASTQs. All outputs go to a separate --workdir.
The input directory is read-only. Trimmed reads are written as NEW files.
If you cannot run, say so. "FastQC is not installed; here is the
install plan" is the correct answer — not a made-up PASS/FAIL table.
When to use vs. not
Use this skill when the user wants to:
Run FastQC / fastp QC on one or more FASTQ (.fastq, .fq, .gz) files
Interpret a FastQC report (per-base quality, adapter content, etc.)
Decide whether adapter or quality trimming is needed before downstream work
Summarize many samples into one MultiQC report
Count reads, get length/GC stats, or subsample with seqkit
Trim adapters/low-quality bases with fastp or Cutadapt (explicitly)