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geniml

geniml is a skill for Claude Code from K-Dense-AI/scientific-agent-skills. It costs 42 tokens per session (4,035 once invoked), scanned A, original, MIT.

A guide for Geniml, a toolkit for machine learning and statistical work on sets of genomic regions. It focuses on checking input contracts and planning Region2Vec or scEmbed analyses rather than running training itself.

In plain words
What is it for?
Use it to validate BED files and reference-region rules, review model and tokenizer compatibility, plan genomic-interval embedding workflows, and assess whether region sets can be compared fairly.
Why use it?
It catches mismatches in coordinates, genome assemblies, model vocabularies, and sample groups before they undermine an analysis. Its helpers validate or plan without contacting services or loading model files.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

not rated 55krepo +1.7k changed 24d ago A scan Socket: passSnyk: passSkillSpector: warn 42 tokens original MIT

Good fit Use it to validate BED files and reference-region rules, review model and tokenizer compatibility, plan genomic-interval embedding workflows, and assess whether region sets can be compared fairly.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/k-dense-ai/scientific-agent-skills/geniml
View source ↗ K-Dense-AI/scientific-agent-skills arxiv.org
About the project

Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.

K-Dense-AI/scientific-agent-skills · 54,587 stars · on GitHub · arxiv.org

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 K-Dense-AI/scientific-agent-skills --skill geniml
Clone the repo
git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills

Made for: Claude Code.

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 geniml

README.md
[![agentmods](https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/geniml/github.svg)](https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/geniml)
Your own site
<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/geniml"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/geniml/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 geniml

Your own site · 80×15
<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/geniml"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/geniml.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,035 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. Third-party audits
  • Socket pass 2 Oct 2026
  • Snyk pass 2 Oct 2026
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Rogue Agent · line 6
    Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
    Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
How audits are shown
Origin original 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 $0.00042 $0.04035
Opus 5.5 $0.00017 $0.01614
Sonnet 5.5 $0.00008 $0.00807
Haiku 4.5 $0.00004 $0.00404

Measured 24d ago against content hash 7fb9ad57657b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

geniml 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 24d ago.

The scan reads SKILL.md. This mod also ships 8 executable files (scripts/__init__.py, scripts/_common.py, scripts/bed_validator.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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • geniml — 86% identical, 81 lines differ
skills/geniml/SKILL.md · 355 lines

How it starts

The opening of the file, as written. The whole thing — 355 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Geniml

Use Geniml for machine learning and statistical workflows over genomic interval sets. Treat coordinates, assemblies, token vocabularies, model artifacts, and sample grouping as explicit contracts. The bundled scripts validate or plan; they do not import Geniml, contact services, deserialize models, or execute training.

Bash is declared only for explicit, user-approved uv, Python, Geniml, Gtars, Git, and native CLI commands shown in this guide; bundled Python helpers do not spawn subprocesses. Example paths under data/, refs/, work/, and models/ are user-provided project placeholders, not missing bundled files.

Verified release snapshot

  • Latest stable PyPI release on 2026-10-01: geniml==0.8.4 (2026-01-14).
  • PyPI does not declare Requires-Python; its classifiers list Python 3.10-3.14. The current recipes below were tested on Python 3.12.
  • geniml==0.8.4 accepts gtars>=0.2.5; the verified base smoke used current gtars==0.10.0 (2026-09-05, Python >=3.10).
  • Extras are ml and test. The base install omits Torch, Gensim, Scanpy, Hugging Face Hub, pyBigWig, and HMM dependencies.
  • Upstream documentation contains stale examples. Release source and installed --help output take precedence where they conflict.

Install reproducibly

Use a separate project environment. The tested CPU stack uses Python 3.12:

uv venv --python 3.12
uv pip install "geniml==0.8.4" "gtars==0.10.0"

For the Region2Vec/scEmbed recipes tested here, add only their required libraries:

uv pip install "torch==2.14.1" "gensim==4.4.0" "huggingface-hub==2.0.0" \
  "scanpy==1.12.4" "anndata==0.12.19" "zarr==2.18.7"

For the consensus recipes, also install pyBigWig==0.3.26 and hmmlearn==0.3.3. For a durable project, use the same requirements with uv add and retain uv.lock.

Geniml requires Zarr <3. AnnData 0.13 requires Zarr >=3, so current AnnData cannot share this environment. Keep AnnData 0.12.19 here; transfer H5AD files between separate environments when newer AnnData features are needed. Never force an incompatible installation with --no-deps.

Read the full file on GitHub · 355 lines

Files

What ships with it

13 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. 24d ago Changed · +22 lines · -1 tokens per session 7fb9ad57657b
  2. 25d ago Changed · +5 lines 8d62070efdc6
  3. 1mo ago Changed · +17 lines 76f648f9e6e7
  4. 1mo ago First seen · 311 lines · 43 tokens per session scan A 937fa40113f3

Subscribe to this mod's changes

geniml is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (54,587 stars, last pushed 7d ago), licensed MIT. It adds 42 tokens to every session and 4,035 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 AIScientificai-scientistbioinformaticschemoinformaticsclaudeclaude-skillsclaudecode
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