geniml
Use Geniml for audited local genomic-interval workflows: validate BED and universe contracts, plan Region2Vec or scEmbed runs, inspect model/tokenizer compatibility, and assess consensus universes.
npx skills add K-Dense-AI/scientific-agent-skills --skill geniml --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 2026-07-23: `geniml==0.8.4` (2026-01-14). - PyPI does not declare `Requires-Python`; its classifiers list Python 3.10-3.14. Prefer Python 3.11 or 3.12 where all native/ML wheels resolve. - `geniml==0.8.4` accepts `gtars>=0.2.5`; the verified base smoke used current `gtars==0.9.2` (2026-06-17, 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
- Verified release snapshot
- Install reproducibly
- Start with the safety gate
- Coordinate and assembly contract
- Current API map
- Region and tokenizer I/O
- Region2Vec
- scEmbed
- BEDspace
- Consensus universes and assessment
- Important 0.8.4 migration notes
- Model and universe compatibility
- BEDbase downloads and caches
- Local audit and planning CLIs
uv venv --python 3.12 uv pip install "geniml==0.8.4" "gtars==0.9.2" uv pip install "geniml[ml]==0.8.4" "gtars==0.9.2" uv add "geniml[ml]==0.8.4" "gtars==0.9.2" uv lock python skills/geniml/scripts/bed_validator.py \ python skills/geniml/scripts/model_artifact_inspector.py \ python skills/geniml/scripts/tokenizer_compatibility.py \ Audit manifest paths, checksums, assemblies, and patient/donor leakage python skills/geniml/scripts/corpus_auditor.py \
What does the geniml skill do?
Use Geniml for audited local genomic-interval workflows: validate BED and universe contracts, plan Region2Vec or scEmbed runs, inspect model/tokenizer compatibility, and assess consensus universes.
How do I install it?
Run `npx skills add K-Dense-AI/scientific-agent-skills --skill geniml --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From K-Dense-AI/scientific-agent-skills, a repository with 32,619 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.