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 bam-to-fragment-file-conversiongit 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/bam-to-fragment-file-conversion)<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/bam-to-fragment-file-conversion"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/bam-to-fragment-file-conversion/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/bam-to-fragment-file-conversion"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/bam-to-fragment-file-conversion.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 | $0.00072 | $0.01384 |
| Opus 5 | $0.00036 | $0.00692 |
| Sonnet 5 | $0.00014 | $0.00277 |
| Haiku 4.5 | $0.00007 | $0.00138 |
Grade A, and why
bam-to-fragment-file-conversion 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BAM-to-fragment-file conversion
Summary
Convert coordinate-sorted BAM files into compressed fragment files (BED.gz or .zst format) containing fragment coordinates, cell barcodes, and quality metrics. This preprocessing step is essential for downstream single-cell ATAC-seq analysis in SnapATAC2.
When to use
When you have coordinate-sorted BAM files from single-cell ATAC-seq experiments (e.g., 10X Genomics scATAC-seq) and need to generate a compressed fragment file for efficient downstream analysis. Use this step before matrix generation, clustering, or peak calling in SnapATAC2.
When NOT to use
- Input BAM file is not coordinate-sorted; use samtools sort -c to validate or re-sort first.
- Fragment file already exists and has been validated; re-running is redundant unless BAM has been re-aligned.
- Working with RNA-seq or other modalities that do not generate fragment-level data (use pp.import_fragments for pre-existing fragment files instead).
Inputs
- coordinate-sorted BAM file
- BAM file with cell barcode information in header (for 10X or tagged BAM)
Outputs
- compressed fragment file (BED.gz or .zst format)
- fragment coordinates with cell barcodes and quality metrics
How to apply
Load the coordinate-sorted BAM file and invoke pp.make_fragment_file with source='10x' if the input is a 10X BAM file, or with default settings for standard BAM inputs. The function processes alignments, extracts fragment coordinates (chromosome, start, end), assigns cell barcodes from the BAM header, and computes quality metrics including duplication rate. Output is generated in compressed format (BED.gz or zst) with standard BED fields plus barcode and count columns. Validate output by confirming the file is non-empty, contains properly formatted BED columns, and that QC metrics (duplication rate, read counts per cell) are accessible for downstream QC decisions.
Related tools
- SnapATAC2 (Python/Rust framework providing pp.make_fragment_file function for BAM-to-fragment conversion with built-in quality metrics and barcode extraction) — https://github.com/scverse/SnapATAC2
- precellar (Alternative universal preprocessing package that automates BAM-to-fragment conversion for multiple single-cell genomics platforms via alignment and fragment file generation) — https://github.com/regulatory-genomics/precellar
- samtools (Utility for BAM file validation, sorting, and inspection before fragment file conversion)
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 · 98 lines · 72 tokens per session scan A 04405f7d05e9
bam-to-fragment-file-conversion is a skill published in the GitHub repository HolobiomicsLab/asb-skill-collections (15 stars, last pushed yesterday), licensed Apache-2.0. It adds 72 tokens to every session and 1,384 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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