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 hi-c-fastq-to-contact-map-pipelinegit 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/hi-c-fastq-to-contact-map-pipeline)<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/hi-c-fastq-to-contact-map-pipeline"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/hi-c-fastq-to-contact-map-pipeline/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/hi-c-fastq-to-contact-map-pipeline"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/hi-c-fastq-to-contact-map-pipeline.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 | $0.00044 | $0.01975 |
| Opus 5 | $0.00022 | $0.00988 |
| Sonnet 5 | $0.00009 | $0.00395 |
| Haiku 4.5 | $0.00004 | $0.00198 |
Grade A, and why
hi-c-fastq-to-contact-map-pipeline 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 9d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
hi-c-fastq-to-contact-map-pipeline
Summary
A unified workflow for converting raw Hi-C sequencing reads (FASTQ format) into contact maps (.hic binary files) via alignment, deduplication, and contact matrix construction. This skill enables reproducible Hi-C data processing following ENCODE uniform processing standards using the Juicer platform.
When to use
You have raw Hi-C FASTQ files from a sequencing experiment and need to generate kilobase-resolution Hi-C contact maps conforming to ENCODE reference standards. Use this when you need to validate pipeline reproducibility by comparing output checksums against reference outputs, or when integrating Hi-C processing into a larger genomic analysis workflow.
When NOT to use
- Input is already a processed .hic or contact matrix file; use downstream analysis tools instead.
- FASTQ files are from non-Hi-C protocols (e.g. standard RNA-seq, WGS); this pipeline is specific to Hi-C.
- You require real-time or streaming processing; Juicer is designed for batch processing on clusters or cloud.
Inputs
- Hi-C raw sequencing reads (FASTQ files, paired-end)
- genome reference sequence (FASTA)
- restriction site file (text, enzyme motifs)
- chromosome sizes file (chrom.sizes format)
Outputs
- Hi-C contact map (.hic binary format)
- aligned and deduplicated read pairs (intermediate BAM/SAM files)
- pipeline statistics and QC metrics (text/JSON)
- output file checksum (MD5/SHA hash)
How to apply
Clone the ENCODE Hi-C uniform processing pipeline (encode_hic_pipeline) from ENCODE-DCC/hic-pipeline and configure Caper for your compute environment (local, cluster, or cloud). Prepare FASTQ input files in a designated directory and invoke the pipeline via caper run hic.wdl with a JSON configuration specifying genome ID, restriction enzyme site, and input paths. The pipeline performs read alignment via BWA, chimeric junction handling, deduplication, and contact matrix binning to produce a .hic binary file. Validate output correctness by computing file checksums (MD5 or SHA) and comparing against ENCODE reference checksums to confirm reproducibility.
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.
- 9d ago First seen · 107 lines · 44 tokens per session scan A a7b61c94de56
hi-c-fastq-to-contact-map-pipeline is a skill published in the GitHub repository HolobiomicsLab/asb-skill-collections (15 stars, last pushed yesterday), licensed Apache-2.0. It adds 44 tokens to every session and 1,975 once invoked, about $0.0002 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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