ml-pipeline SKILL.md skillA
ml-pipeline from jeffallan/claude-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add jeffallan/claude-skills/ml-pipeline@v1.1.0Pins v1.1.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- jeffallan/claude-skills
- Path
skills/ml-pipeline/SKILL.md- Versions recorded
- 5
- Latest version
- v1.1.0, committed Oct 3, 2026
- First version recorded
- Mar 6, 2026
- Size
- 7,423 bytes
- Repository stars
- 12,006
- License
- MIT
Designs and implements production-grade ML pipeline infrastructure: configures experiment tracking with MLflow or Weights & Biases, creates Kubeflow or Airflow DAGs for training orchestration, builds feature store schemas with Feast, deploys model registries, and automates retraining and validation workflows. Use when building ML pipelines, orchestrating training workflows, automating model lifecycle, implementing feature stores, managing experiment tracking systems, setting up DVC for data…
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
# ML Pipeline Expert Senior ML pipeline engineer specializing in production-grade machine learning infrastructure, orchestration systems, and automated training workflows. ## Core Workflow 1. **Design pipeline architecture** — Map data flow, identify stages, define interfaces between components 2. **Validate data schema** — Run schema checks and distribution validation before any training begins; halt and report on failures 3. **Implement feature engineering** — Build transformation pipelines, feature stores, and validation checks 4. **Orchestrate training** — Configure distributed training, hyperparameter tuning, and resource allocation 5. **Track experiments** — Log metrics, parameters, and artifacts; enable comparison and reproducibility 6. **Validate and deploy** — Run model evaluation gates; implement A/B testing or shadow deployment before promotion ## Reference Guide Load detailed guidance based on context: | Topic | Reference | Load When | |-------|-----------|-----------| | Feature Engineering | `references/feature-engineering.md` | Feature pipelines, transformations, feature stores, Feast, data validation | …
Read the whole file at its exact version.
How to install
mdr add jeffallan/claude-skills/ml-pipeline@sha256:f32d20c5fbaade8eThe line at the top of this page pins the label v1.1.0, 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_qle24kqkh3lkal4i)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 5 versions of this file, between Mar 6, 2026 and Oct 3, 2026, about one every 53 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.1.0 latest | 2026-10-03 | 958e60f | 7,423 B | A | view · diff |
| v1.1.0 | 2026-10-03 | ec755b7 | 7,341 B | A | view · diff |
| v1.1.0 | 2026-04-29 | efebc44 | 7,247 B | A | view · diff |
| v1.1.0 | 2026-03-06 | c7afefb | 7,160 B | A | view · diff |
| v1.0.0 | 2026-03-06 | cba3273 | 7,160 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 (7423 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
jeffallan/claude-skills · 12,006 stars · license MIT · pushed 2026-10-21 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_qle24kqkh3lkal4i GET https://markdownregistry.com/api/v1/resolve?ref=jeffallan/claude-skills/ml-pipeline GET https://markdownregistry.com/api/v1/blob/f32d20c5fbaade8e7e43fcf756dec9543dd17f38b184f5d100b50bf34dae06a6
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.
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