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 cooler-file-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/cooler-file-format-handling)<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/cooler-file-format-handling"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/cooler-file-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/cooler-file-format-handling"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/cooler-file-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 | $0.00022 | $0.01349 |
| Opus 5 | $0.00011 | $0.00674 |
| Sonnet 5 | $0.00004 | $0.00270 |
| Haiku 4.5 | $0.00002 | $0.00135 |
Grade A, and why
cooler-file-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 12d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
cooler-file-format-handling
Summary
Load, validate, and interact with cooler format files—a hierarchical HDF5-based storage format for high-resolution Hi-C contact matrices—using the cooler Python library. This skill is essential for accessing, inspecting metadata, and preparing contact data for downstream genomic analyses.
When to use
You have a Hi-C dataset stored in cooler format (e.g., from a public repository, GEO, or Zenodo, or generated by a contact-calling pipeline) and need to programmatically load it, inspect its structure (bins, chromosomes, resolution), verify data integrity, or pass it to analysis functions like cooltools.coverage or cooltools.insulation.
When NOT to use
- Input is already loaded as a numpy/scipy sparse matrix or pandas DataFrame and you do not need cooler's metadata or hierarchical access features.
- Your Hi-C data is in a different format (e.g., text-based .hic, Juicer, or raw BAM files); use format conversion tools first.
- You require real-time streaming or random-access queries on datasets larger than available memory and do not have HDF5 infrastructure in place.
Inputs
- cooler file path (.cool or .mcool format)
- genomic region specification (optional; chromosome, start, end)
- resolution level (for .mcool files only)
Outputs
- cooler object (Python cooler.Cooler or cooler.MultiResolutionCooler instance)
- bin table (pandas DataFrame with bin coordinates and metadata)
- contact matrix (sparse or dense array for specified genomic region)
- metadata dictionary (resolution, bin count, chromsome list, balance weights)
How to apply
Use the cooler Python API to open a .cool or .mcool file, inspect bin-level metadata (coordinates, sizes) and matrix properties, and validate that the file structure matches expected schemas. The cooler library provides a Pythonic interface to the hierarchical HDF5 format, allowing you to fetch contact matrices by genomic range and inspect balance weights or other stored annotations. Verify file integrity by checking row counts, coordinate ranges, and the presence of required columns (chrom, start, end, and contact matrix values). For multi-resolution datasets (mcool), specify the desired resolution when loading.
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.
- 12d ago First seen · 102 lines · 22 tokens per session scan A 3c7567b9ecc1
cooler-file-format-handling is a skill published in the GitHub repository HolobiomicsLab/asb-skill-collections (15 stars, last pushed yesterday), licensed Apache-2.0. It adds 22 tokens to every session and 1,349 once invoked, about $0.0001 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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