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 genome-alignment-and-contact-matrix-constructiongit 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/genome-alignment-and-contact-matrix-construction)<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/genome-alignment-and-contact-matrix-construction"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/genome-alignment-and-contact-matrix-construction/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/genome-alignment-and-contact-matrix-construction"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/genome-alignment-and-contact-matrix-construction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Output Handling · line 88 Output size or generation rate is not bounded. Unbounded output enables denial-of-service through resource exhaustion, log flooding, or context-window stuffing.Fix: Set explicit limits on output length, generation count, and rate. Use max_tokens and truncation to prevent unbounded output.
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 | $0.00075 | $0.01660 |
| Opus 5 | $0.00037 | $0.00830 |
| Sonnet 5 | $0.00015 | $0.00332 |
| Haiku 4.5 | $0.00007 | $0.00166 |
Grade A, and why
genome-alignment-and-contact-matrix-construction 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
genome-alignment-and-contact-matrix-construction
Summary
Process raw Hi-C FASTQ sequencing data through read alignment, deduplication, and normalization to generate kilobase-resolution contact matrices in .hic format. This skill is essential when starting from FASTQ reads and needing to construct quantitative genome-wide interaction maps for downstream analysis.
When to use
You have raw Hi-C FASTQ files from a kilobase-resolution Hi-C experiment and need to produce a processed Hi-C contact map (.hic file) for visualization, loop calling, or chromatin structure analysis. This is the entry point for any Hi-C dataset that has not yet been aligned and normalized.
When NOT to use
- Input Hi-C data is already in .hic format or pre-processed contact matrix form — use downstream feature annotation tools instead.
- You have single-end Hi-C reads or non-standard pairing; Juicer is optimized for paired-end sequencing.
- Your restriction enzyme or genome is not supported without custom configuration of the pipeline.
Inputs
- Raw Hi-C FASTQ files (paired-end sequencing reads)
- Reference genome FASTA file
- Chromosome sizes file (chrom.sizes)
- Restriction enzyme recognition site file
Outputs
- .hic file (processed Hi-C contact map with normalized interactions)
- Intermediate alignment files (in aligned/ directory)
- Pipeline statistics and logs
How to apply
Clone the Juicer repository (either stable Juicer 1.6 or development Juicer 2 depending on your requirements) and configure the pipeline with your reference genome, restriction enzyme recognition site, and computational resources (threads and memory allocation). Organize raw FASTQ files in a designated fastq/ subdirectory and run juicer.sh with appropriate flags (e.g., -g for genome ID, -y for restriction site file, -z for reference genome). The pipeline automatically handles read alignment via BWA, contact matrix construction, and normalization, producing a .hic output file. Verify success by confirming the .hic file is generated without errors and contains valid Hi-C contact data.
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 · 108 lines · 75 tokens per session scan A 6d12dbe446b8
genome-alignment-and-contact-matrix-construction is a skill published in the GitHub repository HolobiomicsLab/asb-skill-collections (15 stars, last pushed yesterday), licensed Apache-2.0. It adds 75 tokens to every session and 1,660 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 2026-09-03.
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