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 thesecondfox/skill --skill bio-workflows-fastq-to-variantsgit clone --depth 1 https://github.com/thesecondfox/skillWrote 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/thesecondfox/skill/bio-workflows-fastq-to-variants)<a href="https://agentmods.dev/skills/thesecondfox/skill/bio-workflows-fastq-to-variants"><img src="https://agentmods.dev/badge/skills/thesecondfox/skill/bio-workflows-fastq-to-variants/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/thesecondfox/skill/bio-workflows-fastq-to-variants"><img src="https://agentmods.dev/badge/skills/thesecondfox/skill/bio-workflows-fastq-to-variants.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 | $0.00059 | $0.03333 |
| Opus 5 | $0.00030 | $0.01666 |
| Sonnet 5 | $0.00012 | $0.00667 |
| Haiku 4.5 | $0.00006 | $0.00333 |
Grade A, and why
bio-workflows-fastq-to-variants 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 5d 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 — 367 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: BWA-MEM2 2.2.1+, Ensembl VEP 111+, GATK 4.5+, bcftools 1.19+, fastp 0.23+, samtools 1.19+
Before using code patterns, verify installed versions match. If versions differ:
- CLI:
<tool> --versionthen<tool> --helpto confirm flags
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
FASTQ to Variants Workflow
"Call variants from my whole-genome or exome FASTQ files" → Orchestrate fastp QC, BWA-MEM2 alignment, duplicate marking, BQSR, GATK HaplotypeCaller variant calling, and VQSR/hard filtering to produce filtered VCF output.
Complete pipeline from raw DNA sequencing FASTQ files to filtered variant calls.
Workflow Overview
FASTQ files
|
v
[1. QC & Trimming] -----> fastp
|
v
[2. Alignment] ---------> bwa-mem2
|
v
[3. BAM Processing] ----> sort, markdup, index
|
v
[4. Variant Calling] ---> bcftools (primary) or GATK
|
v
[5. Filtering] ---------> Quality filters
|
v
Filtered VCF
Primary Path: BWA + bcftools
Step 1: Quality Control with fastp
# Single sample
fastp -i sample_R1.fastq.gz -I sample_R2.fastq.gz \
-o sample_R1.trimmed.fq.gz -O sample_R2.trimmed.fq.gz \
--detect_adapter_for_pe \
--qualified_quality_phred 20 \
--length_required 50 \
--html sample_fastp.html
# Batch processing
for sample in sample1 sample2 sample3; do
fastp -i ${sample}_R1.fastq.gz -I ${sample}_R2.fastq.gz \
-o trimmed/${sample}_R1.fq.gz -O trimmed/${sample}_R2.fq.gz \
--detect_adapter_for_pe \
--html qc/${sample}_fastp.html
done
QC Checkpoint 1: Check fastp reports
- Q30 bases >85% (DNA typically higher quality than RNA)
- Adapter content <1%
- No unusual GC distribution
Step 2: BWA-MEM2 Alignment
# Index reference (once)
bwa-mem2 index reference.fa
# Align with read group info
for sample in sample1 sample2 sample3; do
bwa-mem2 mem -t 8 \
-R "@RG\tID:${sample}\tSM:${sample}\tPL:ILLUMINA\tLB:lib1" \
reference.fa \
trimmed/${sample}_R1.fq.gz \
trimmed/${sample}_R2.fq.gz \
| samtools view -bS - > aligned/${sample}.bam
done
What ships with it
1 file 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.
- 5d ago First seen · 367 lines · 59 tokens per session scan A 663870e2cd64
bio-workflows-fastq-to-variants is a skill published in the GitHub repository thesecondfox/skill (3 stars, last pushed 5mo ago), licensed MIT. It adds 59 tokens to every session and 3,333 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.
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