bio-stats-ml-reporting SKILL.md skillA
bio-stats-ml-reporting from fmschulz/omics-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add fmschulz/omics-skills/bio-stats-ml-reporting@git:20261001.bf5afd6Pins git:20261001.bf5afd6 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- fmschulz/omics-skills
- Path
skills/bio-stats-ml-reporting/SKILL.md- Versions recorded
- 6
- Latest version
- git:20261001.bf5afd6, committed Oct 1, 2026
- First version recorded
- Jul 11, 2026
- Size
- 5,169 bytes
- Repository stars
- 11
- License
- MIT
Run statistics or machine learning on biological results and write a validated report. Use when testing hypotheses, training classifiers or rolling up discovery evidence.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Bio Stats ML Reporting
Aggregate results, train ML models, and produce reports with validated references.
## Instructions
1. Join outputs in DuckDB and build feature tables. Hand large tables to ML code as Arrow (`.arrow()`, `.pl()`, or `.df()` on a DuckDB result) instead of writing intermediate CSVs.
2. Train baseline models and evaluate with cross-validation. Versions checked for this skill are in [docs/README.md](docs/README.md); pin the ones you use in the project's `pixi.toml`.
- CPU baseline: scikit-learn for linear, tree, and clustering baselines; XGBoost for gradient boosting.
- GPU node available (CUDA): set `device="cuda"` on XGBoost (supported since v2.0). For scikit-learn-style estimators (random forest, k-means, PCA, UMAP), RAPIDS cuML provides GPU equivalents; record the device in the run log.
- On HPC, train through the scheduler (`sbatch`) and set explicit thread limits (`n_jobs`, `nthread`, `OMP_NUM_THREADS`) to match the allocation.
3. Generate reports and validate references.
- Validate the prediction table with
`scripts/validate_predictions.py`. Keep group identifiers and confounder
…Read the whole file at its exact version.
How to install
mdr add fmschulz/omics-skills/bio-stats-ml-reporting@sha256:2160b70f4cff63bcThe line at the top of this page pins the label git:20261001.bf5afd6, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_erglzlf542mizdlk)
3 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 6 versions of this file, between Jul 11, 2026 and Oct 1, 2026, about one every 16 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20261001.bf5afd6 latest | 2026-10-01 | bf5afd6 | 5,169 B | A | view · diff |
| git:20260905.3e49039 | 2026-09-05 | 3e49039 | 4,783 B | A | view · diff |
| git:20260825.978bb0a | 2026-08-25 | 978bb0a | 4,619 B | A | view · diff |
| git:20260825.bd47e68 | 2026-08-25 | bd47e68 | 5,192 B | A | view · diff |
| git:20260712.3675171 | 2026-07-12 | 3675171 | 5,203 B | A | view · diff |
| git:20260711.5ae6f6f | 2026-07-11 | 5ae6f6f | 4,482 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (5169 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
fmschulz/omics-skills · 11 stars · license MIT · pushed 2026-10-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_erglzlf542mizdlk GET https://markdownregistry.com/api/v1/resolve?ref=fmschulz/omics-skills/bio-stats-ml-reporting GET https://markdownregistry.com/api/v1/blob/2160b70f4cff63bc485a5deab30536dada6109584858b84591820fa22a0942be
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.