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bioskills-deep-learning-atac

bioskills-deep-learning-atac is a skill for OpenCode from ai4nucleome/BioMaster. It costs 49 tokens per session (279 once invoked), scanned A, original, no licence file.

Sequence-based deep-learning methods for ATAC-seq, an experiment that measures which parts of DNA are accessible to regulatory proteins. They correct Tn5 enzyme bias, predict how variants may affect accessibility, and discover DNA-binding patterns.

In plain words
What is it for?
Use it for Tn5 bias correction, variant-effect prediction, and de novo motif discovery with chromBPNet, tangermeme, or TF-MoDISco.
Why use it?
It helps separate technical effects from biological signals in ATAC-seq data. It can also turn sequence data into predictions about variants and regulatory motifs.

Skill for OpenCode

Written for OpenCode: installed under .opencode/.

not rated 118repo +2 3mo ago A scan 49 tokens no licence

Good fit Use it for Tn5 bias correction, variant-effect prediction, and de novo motif discovery with chromBPNet, tangermeme, or TF-MoDISco.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ai4nucleome/biomaster/bioskills-deep-learning-atac
View source ↗ ai4nucleome/BioMaster
Install

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.

Any agent
npx skills add ai4nucleome/BioMaster --skill bioskills-deep-learning-atac
Clone the repo
git clone --depth 1 https://github.com/ai4nucleome/BioMaster

Made for: OpenCode.

Wrote 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.

agentmods badge for bioskills-deep-learning-atac

README.md
[![agentmods](https://agentmods.dev/badge/skills/ai4nucleome/biomaster/bioskills-deep-learning-atac/github.svg)](https://agentmods.dev/skills/ai4nucleome/biomaster/bioskills-deep-learning-atac)
Your own site
<a href="https://agentmods.dev/skills/ai4nucleome/biomaster/bioskills-deep-learning-atac"><img src="https://agentmods.dev/badge/skills/ai4nucleome/biomaster/bioskills-deep-learning-atac/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.

agentmods 80×15 button for bioskills-deep-learning-atac

Your own site · 80×15
<a href="https://agentmods.dev/skills/ai4nucleome/biomaster/bioskills-deep-learning-atac"><img src="https://agentmods.dev/badge/skills/ai4nucleome/biomaster/bioskills-deep-learning-atac.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 279 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00049 $0.00279
Opus 5.5 $0.00020 $0.00112
Sonnet 5.5 $0.00010 $0.00056
Haiku 4.5 $0.00005 $0.00028

Measured 2mo ago against content hash 7fa20a6e4de0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

bioskills-deep-learning-atac 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 2mo 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.

.opencode/bioskills/bioskills-deep-learning-atac/SKILL.md · 15 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 2mo ago First seen · 15 lines · 49 tokens per session scan A 7fa20a6e4de0

Subscribe to this mod's changes

bioskills-deep-learning-atac is a skill published in the GitHub repository ai4nucleome/BioMaster (118 stars, last pushed 3mo ago), with no licence file. It adds 49 tokens to every session and 279 once invoked, about $0.0002 per session on Opus 5.5. 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.

Data and AIScientific
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