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 agentmods add skills/thesecondfox/skill/bio-chip-seq-chipseq-visualizationnpx skills add thesecondfox/skill --skill bio-chip-seq-chipseq-visualizationgit clone --depth 1 https://github.com/thesecondfox/skillWhat 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 | $0.00064 | $0.02183 |
| Opus 5 | $0.00032 | $0.01092 |
| Sonnet 5 | $0.00013 | $0.00437 |
| Haiku 4.5 | $0.00006 | $0.00218 |
Grade A, and why
bio-chipseq-visualization 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 2d 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 — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: GenomicRanges 1.54+, deepTools 3.5+
Before using code patterns, verify installed versions match. If versions differ:
- R:
packageVersion('<pkg>')then?function_nameto verify parameters - 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.
ChIP-seq Visualization
"Create a heatmap of ChIP-seq signal around peaks" → Generate signal heatmaps, profile plots, and genome browser tracks showing enrichment patterns around genomic features.
- CLI:
deeptools computeMatrix reference-point→plotHeatmap - R:
Gviz,ChIPseeker::plotAvgProf()
deepTools - Compute Matrix
Goal: Build a signal matrix of ChIP-seq coverage around reference points for downstream heatmaps and profiles.
Approach: Use computeMatrix to extract bigWig signal values in windows around genomic features like TSS.
# Compute signal matrix around TSS
computeMatrix reference-point \
--referencePoint TSS \
-b 3000 -a 3000 \ # 3kb upstream and downstream
-R genes.bed \ # Reference regions
-S sample.bw \ # Signal file (bigWig)
-o matrix.gz \
--outFileSortedRegions sorted_genes.bed
deepTools - Scale-Regions
Goal: Visualize ChIP signal across gene bodies scaled to a uniform length.
Approach: Scale all gene regions to equal size and compute signal with flanking windows.
# Signal across gene bodies
computeMatrix scale-regions \
-R genes.bed \
-S sample1.bw sample2.bw \
-b 3000 -a 3000 \ # Flanking regions
-m 5000 \ # Scaled body length
-o matrix_scaled.gz
deepTools - Heatmap
Goal: Generate a heatmap of ChIP-seq signal intensity across genomic regions.
Approach: Render the precomputed signal matrix as a clustered heatmap with optional profile summary.
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.
- 2d ago First seen · 290 lines · 64 tokens per session scan A fa7b84ccb831
bio-chipseq-visualization is a skill published in the GitHub repository thesecondfox/skill (3 stars, last pushed 5mo ago), licensed MIT. It adds 64 tokens to every session and 2,183 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 2026-08-31.
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