ml-pipeline-automation SKILL.md skillA
ml-pipeline-automation from secondsky/claude-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add secondsky/claude-skills/ml-pipeline-automation@git:20260402.89c5e89Pins git:20260402.89c5e89 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- secondsky/claude-skills
- Path
plugins/ml-pipeline-automation/skills/ml-pipeline-automation/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260402.89c5e89, committed Apr 2, 2026
- First version recorded
- Dec 24, 2025
- Size
- 12,903 bytes
- Repository stars
- 247
- License
- MIT
Automate ML workflows with Airflow, Kubeflow, MLflow. Use for reproducible pipelines, retraining schedules, MLOps, or encountering task failures, dependency errors, experiment tracking issues.
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 Automation Orchestrate end-to-end machine learning workflows from data ingestion to production deployment with production-tested Airflow, Kubeflow, and MLflow patterns. ## When to Use This Skill Load this skill when: - **Building ML Pipelines**: Orchestrating data → train → deploy workflows - **Scheduling Retraining**: Setting up automated model retraining schedules - **Experiment Tracking**: Tracking experiments, parameters, metrics across runs - **MLOps Implementation**: Building reproducible, monitored ML infrastructure - **Workflow Orchestration**: Managing complex multi-step ML workflows - **Model Registry**: Managing model versions and deployment lifecycle ## Quick Start: ML Pipeline in 5 Steps ```bash # 1. Install Airflow and MLflow (check for latest versions at time of use) pip install apache-airflow==3.1.5 mlflow==3.7.0 # Note: These versions are current as of December 2025 # Check PyPI for latest stable releases: https://pypi.org/project/apache-airflow/ # 2. Initialize Airflow database airflow db init # 3. Create DAG file: dags/ml_training_pipeline.py cat > dags/ml_training_pipeline.py << 'EOF' from airflow import DAG …
Read the whole file at its exact version.
How to install
mdr add secondsky/claude-skills/ml-pipeline-automation@sha256:80c31ff172542df1The line at the top of this page pins the label git:20260402.89c5e89, 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_m5pbsydara27wjgm)
5 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 2 versions of this file, between Dec 24, 2025 and Apr 2, 2026, about one every 100 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260402.89c5e89 latest | 2026-04-02 | 89c5e89 | 12,903 B | A | view · diff |
| git:20251224.ba827ce | 2025-12-24 | ba827ce | 12,889 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 (12903 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
secondsky/claude-skills · 247 stars · license MIT · pushed 2026-10-31 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_m5pbsydara27wjgm GET https://markdownregistry.com/api/v1/resolve?ref=secondsky/claude-skills/ml-pipeline-automation GET https://markdownregistry.com/api/v1/blob/80c31ff172542df1e7c083c436d7a186d61f0812dddc2dab2f8c14f0838218cd
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.