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 bedpe-format-handlinggit 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/bedpe-format-handling)<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/bedpe-format-handling"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/bedpe-format-handling/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/bedpe-format-handling"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/bedpe-format-handling.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 | $0.00073 | $0.01489 |
| Opus 5 | $0.00036 | $0.00745 |
| Sonnet 5 | $0.00015 | $0.00298 |
| Haiku 4.5 | $0.00007 | $0.00149 |
Grade A, and why
bedpe-format-handling 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
bedpe-format-handling
Summary
Handle paired-end ChIP-Seq data in BEDPE format to preserve fragment pairing information through peak-calling workflows. BEDPE format encodes both read pairs as six-column tab-separated coordinates, enabling proper fragment length estimation and paired-end-aware pileup.
When to use
Your ChIP-Seq input is paired-end sequencing data stored in BEDPE format (e.g., CTCF_PE_ChIP_chr22_50k.bedpe.gz), and you need to estimate fragment length and call peaks while respecting the paired nature of the reads rather than treating them as independent single-end alignments.
When NOT to use
- Input is single-end ChIP-Seq data (use BED format instead with manual fragment length specification via --extsize)
- Fragment length is already known and fixed across the experiment (use -f BED with explicit --extsize parameter for faster processing)
- BEDPE file contains singletons or unpaired reads (filter or convert to BED first)
Inputs
- BEDPE-format paired-end ChIP-Seq alignment file (gzip-compressed, e.g., .bedpe.gz)
- Control (input) sample in BEDPE format (optional but recommended for peak calling)
Outputs
- Fragment length estimate (d) in base pairs
- narrowPeak file with peak coordinates and summit positions
- bedGraph intermediate pileup tracks
How to apply
Pass the BEDPE file to macs3 predictd with the -f BEDPE flag to estimate average insertion length (fragment length d), which should be reported in base pairs (e.g., ~253 bp for the CTCF test data). Then run macs3 callpeak with -f BEDPE on the ChIP sample without specifying --extsize, allowing the pileup function to automatically handle paired-end fragment extent. Verify that the narrowPeak output file is generated with proper peak coordinates and summit positions. This workflow respects the original fragment boundaries encoded in the BEDPE coordinate pairs rather than requiring manual extension parameters.
Related tools
- macs3 predictd (Estimate average insertion length (fragment length d) from paired-end ChIP sample) — https://github.com/macs3-project/MACS
- macs3 callpeak (Call peaks on paired-end ChIP-Seq data using BEDPE format to automatically extend fragments) — https://github.com/macs3-project/MACS
- macs3 pileup (Generate pileup track for paired-end ChIP sample, handling fragment extent from BEDPE coordinates) — https://github.com/macs3-project/MACS
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 · 95 lines · 73 tokens per session scan A 17ad067ad8f8
bedpe-format-handling is a skill published in the GitHub repository HolobiomicsLab/asb-skill-collections (15 stars, last pushed 4d ago), licensed Apache-2.0. It adds 73 tokens to every session and 1,489 once invoked, about $0.0004 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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