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 HolobiomicsLab/asb-skill-collections --skill chip-seq-peak-calling-workflowgit clone --depth 1 https://github.com/HolobiomicsLab/asb-skill-collectionsWrote 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/holobiomicslab/asb-skill-collections/chip-seq-peak-calling-workflow)<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/chip-seq-peak-calling-workflow"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/chip-seq-peak-calling-workflow/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/holobiomicslab/asb-skill-collections/chip-seq-peak-calling-workflow"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/chip-seq-peak-calling-workflow.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 | $0.00066 | $0.02463 |
| Opus 5.5 | $0.00026 | $0.00985 |
| Sonnet 5.5 | $0.00013 | $0.00493 |
| Haiku 4.5 | $0.00007 | $0.00246 |
Grade A, and why
chip-seq-peak-calling-workflow 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 2mo 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
chip-seq-peak-calling-workflow
Summary
A complete ChIP-Seq peak calling workflow that decomposes MACS3 callpeak into sequential subcommands (filterdup, predictd, pileup, bdgcmp, bdgopt, bdgpeakcall) to progressively transform aligned reads into peak calls with customizable statistical scoring and filtering.
When to use
When you have aligned ChIP-Seq reads (single-end BED or paired-end BEDPE format) and need to identify enriched genomic regions by comparing ChIP signal against control background, with the ability to customize fragment length estimation, local bias calculation, and peak score thresholds rather than using the monolithic callpeak command.
When NOT to use
- Input reads are already in a pre-processed or normalized format (e.g., pre-computed coverage tracks, counts per genomic bin) — the workflow requires raw aligned reads in BED/BEDPE format.
- You need to call broad peaks (e.g., for histone marks covering large domains) — use macs3 bdgbroadcall instead of bdgpeakcall, or apply a different workflow designed for broad mark analysis.
- You lack a suitable control/input sample — the workflow requires both ChIP and control samples to compute local bias; single-sample peak calling requires alternative statistical approaches.
Inputs
- Aligned ChIP-Seq reads in BED format (single-end) or BEDPE format (paired-end)
- Aligned control/input reads in BED format (single-end) or BEDPE format (paired-end)
- Genome size in base pairs (for genome-wide background calculation)
- Sequencing read length (for gap parameter in peak calling)
Outputs
- Filtered ChIP read count (integer)
- Filtered control read count (integer)
- Estimated fragment length d in base pairs (integer)
- ChIP pileup BEDGRAPH file (bedGraph format)
- Local bias BEDGRAPH file (bedGraph format, combined maximum of d/slocal/llocal backgrounds)
- Score BEDGRAPH file (bedGraph format, q-value or p-value scores per base pair)
- narrowPeak file (BED-like format with peak coordinates, summit positions, and score)
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.
- 2mo ago First seen · 110 lines · 66 tokens per session scan A 1846f373f95c
chip-seq-peak-calling-workflow is a skill published in the GitHub repository HolobiomicsLab/asb-skill-collections (16 stars, last pushed 6d ago), licensed Apache-2.0. It adds 66 tokens to every session and 2,463 once invoked, about $0.0003 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 2026-08-30.
chip-seq-peak-calling-workflow compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| chip-seq-peak-calling-workflowHolobiomicsLab/asb-skill-collections | Skill | 16 | 6d ago | Apache-2.0 | A | 66 | Claude Code, Codex |
| gsva-analysis-and-visualizationaipoch/medical-research-skills | Skill | 2.0k | 1mo ago | MIT | A | 88 | Claude Code, Codex |
| medical-research-literature-reader-proaipoch/medical-research-skills | Skill | 2.0k | 1mo ago | MIT | A | 199 | Claude Code, Codex |
| adverse-event-narrativeaipoch/medical-research-skills | Skill | 2.0k | 1mo ago | MIT | A | 57 | Claude Code, Codex |
| anatomy-quiz-masteraipoch/medical-research-skills | Skill | 2.0k | 1mo ago | MIT | A | 17 | Claude Code, Codex |
| cerna-analysisaipoch/medical-research-skills | Skill | 2.0k | 1mo ago | MIT | A | 68 | Claude Code, Codex |
| cibersort-immune-infiltration-analysisaipoch/medical-research-skills | Skill | 2.0k | 1mo ago | MIT | A | 92 | Claude Code, Codex |