histone-aggregation

A workflow for combining histone-mark peak data from multiple ENCODE experiments, donors, and laboratories into one map. Histone marks are chemical tags on DNA-packaging proteins that help show which parts of the genome are active or regulated.

In plain words
What is it for?
Use it to merge narrowPeak files into a shared set of genomic regions and attach confidence information based on the contributing studies.
Why use it?
It removes the need to compare many separate peak files by hand and helps show where a histone mark consistently appears in a tissue.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/ammawla/encode-toolkit/histone-aggregation
Any agent
npx skills add ammawla/encode-toolkit --skill histone-aggregation
Clone the repo
git clone --depth 1 https://github.com/ammawla/encode-toolkit

Made for: Claude Code, Codex.

Per session 82 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,442 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00082 $0.04442
Opus 5 $0.00041 $0.02221
Sonnet 5 $0.00016 $0.00888
Haiku 4.5 $0.00008 $0.00444

Measured 2d ago against content hash 558250f85c5c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

histone-aggregation 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 2d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate_peaks.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

plugin/skills/histone-aggregation/SKILL.md · 388 lines

The source is not reproduced here

Licensed AGPL-3.0

The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Files

What ships with it

5 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. 2d ago First seen · 388 lines · 82 tokens per session scan A 558250f85c5c

Subscribe to this mod's changes

histone-aggregation is a skill published in the GitHub repository ammawla/encode-toolkit (24 stars, last pushed 1mo ago), licensed AGPL-3.0. It adds 82 tokens to every session and 4,442 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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