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 AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-deeptoolsgit clone --depth 1 https://github.com/AlterLab-IEU/AlterLab-Academic-SkillsWrote 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/alterlab-ieu/alterlab-academic-skills/alterlab-deeptools)<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-deeptools"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-deeptools/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/alterlab-ieu/alterlab-academic-skills/alterlab-deeptools"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-deeptools.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00173 | $0.03476 |
| Opus 5 | $0.00086 | $0.01738 |
| Sonnet 5 | $0.00035 | $0.00695 |
| Haiku 4.5 | $0.00017 | $0.00348 |
Grade A, and why
alterlab-deeptools 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 10d 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 — 360 lines — stays where its author put it; the contents beside it link to each section on GitHub.
deepTools: NGS Data Analysis Toolkit
Overview
deepTools is a comprehensive suite of Python command-line tools designed for processing and analyzing high-throughput sequencing data. Use deepTools to perform quality control, normalize data, compare samples, and generate publication-quality visualizations for ChIP-seq, RNA-seq, ATAC-seq, MNase-seq, and other NGS experiments.
Core capabilities:
- Convert BAM alignments to normalized coverage tracks (bigWig/bedGraph)
- Quality control assessment (fingerprint, correlation, coverage)
- Sample comparison and correlation analysis
- Heatmap and profile plot generation around genomic features
- Enrichment analysis and peak region visualization
When to Use This Skill
This skill should be used when:
- File conversion: "Convert BAM to bigWig", "generate coverage tracks", "normalize ChIP-seq data"
- Quality control: "check ChIP quality", "compare replicates", "assess sequencing depth", "QC analysis"
- Visualization: "create heatmap around TSS", "plot ChIP signal", "visualize enrichment", "generate profile plot"
- Sample comparison: "compare treatment vs control", "correlate samples", "PCA analysis"
- Analysis workflows: "analyze ChIP-seq data", "RNA-seq coverage", "ATAC-seq analysis", "complete workflow"
- Working with specific file types: BAM files, bigWig files, BED region files in genomics context
Quick Start
For users new to deepTools, start with file validation and common workflows:
1. Validate Input Files
Before running any analysis, validate BAM, bigWig, and BED files using the validation script:
python scripts/validate_files.py --bam sample1.bam sample2.bam --bed regions.bed
This checks file existence, BAM indices, and format correctness.
2. Generate Workflow Template
For standard analyses, use the workflow generator to create customized scripts:
# List available workflows
python scripts/workflow_generator.py --list
# Generate ChIP-seq QC workflow
python scripts/workflow_generator.py chipseq_qc -o qc_workflow.sh \
--input-bam Input.bam --chip-bams "ChIP1.bam ChIP2.bam" \
--genome-size 2913022398
# Make executable and run
chmod +x qc_workflow.sh
./qc_workflow.sh
What ships with it
9 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.
- assets/quick_reference.md 1.5 KB
- evals/evals.json 4.2 KB
- references/effective_genome_sizes.md 3.8 KB
- references/normalization_methods.md 11 KB
- references/tools_reference.md 18 KB
- references/usage_playbook.md 5.1 KB
- references/workflows.md 11 KB
- scripts/validate_files.py 6.0 KB runs code
- scripts/workflow_generator.py 14 KB runs code
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.
- 10d ago First seen · 360 lines · 173 tokens per session scan A ec1564a23cb0
alterlab-deeptools is a skill published in the GitHub repository AlterLab-IEU/AlterLab-Academic-Skills (66 stars, last pushed 5d ago), licensed MIT. It adds 173 tokens to every session and 3,476 once invoked, about $0.0009 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 2026-08-30.
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