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 positional-distribution-profile-aggregation-and-visualizationgit 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/positional-distribution-profile-aggregation-and-visualization)<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/positional-distribution-profile-aggregation-and-visualization"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/positional-distribution-profile-aggregation-and-visualization/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/positional-distribution-profile-aggregation-and-visualization"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/positional-distribution-profile-aggregation-and-visualization.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 | $0.00066 | $0.01961 |
| Opus 5 | $0.00033 | $0.00981 |
| Sonnet 5 | $0.00013 | $0.00392 |
| Haiku 4.5 | $0.00007 | $0.00196 |
Grade A, and why
positional-distribution-profile-aggregation-and-visualization 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 6d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
positional-distribution-profile-aggregation-and-visualization
Summary
Aggregate and visualize Tn5 insertion counts across fixed-width genomic windows flanking regulatory sites (e.g., transcription factor binding motifs) to reveal characteristic footprint patterns—depletion of insertions at protein-bound sites versus uniform accessibility at unbound sites. This skill is essential for footprinting analysis in ATAC-seq to distinguish bound from unbound regulatory elements.
When to use
Apply this skill when you have ATAC-seq BAM alignments with classified motif sites (bound vs. unbound based on chromatin accessibility or binding thresholds) and wish to detect and visualize the characteristic Tn5 insertion depletion signal (footprints) around transcription factor binding sites. Use it to validate that your binding site classification reflects genuine protein occupancy rather than sequence motif occurrence alone.
When NOT to use
- Input BAM file has not been deduplicated or quality-filtered; raw, uncorrected ATAC-seq data with high technical bias will obscure genuine footprints.
- Motif site classification is based on sequence matching alone without chromatin accessibility or binding evidence; unanchored motif predictions do not reliably partition bound from unbound sites.
- Genomic windows are too narrow (< ±40 bp) to capture the full footprint width, or too wide (> ±200 bp) to resolve the depletion peak clearly.
Inputs
- ATAC-seq BAM file with aligned Tn5 insertion reads (corrected for Tn5 bias if available)
- BED file of motif site coordinates classified as bound or unbound
- Reference genome (FASTA) if performing bias correction beforehand
- Peak coordinates (BED) defining open chromatin regions
Outputs
- Tabular matrix of Tn5 insertion counts by genomic position and site class (bound/unbound)
- Aggregated insertion profile plots (line plots or heatmaps) for bound vs. unbound sites
- Positional statistics (mean, standard deviation) per window position and site class
- Footprint score or depletion depth metrics quantifying the signal difference
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.
- 6d ago First seen · 106 lines · 66 tokens per session scan A 92f166ba9e51
positional-distribution-profile-aggregation-and-visualization is a skill published in the GitHub repository HolobiomicsLab/asb-skill-collections (15 stars, last pushed yesterday), licensed Apache-2.0. It adds 66 tokens to every session and 1,961 once invoked, about $0.0003 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 2026-09-06.
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