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Building an end-to-end MLOps pipeline v1.0.0

Use this resource to build an MLOps pipeline from data to deployment

New

  • 332 downloads
  • 215 likes
  • 237 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install end-to-end-mlops-pipeline

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent defines the pipeline stages, from ingestion to production monitoring, specifying dependencies between stages and validation points. It provides a DAG template to orchestrate the whole flow.

Mostly picked by

Updated November 2, 2026

Card for the “Building an end-to-end MLOps pipeline” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md: pipeline stages, capabilities and usage
  • SKILL.md: dependency configuration and DAG template

Good fit for

  • You are industrialising a model training run that is done by hand
  • You want a reproducible flow from dataset to deployment

Not for

    Tags

    • mlops
    • pipeline
    • training
    • deployment

    About

    You say

    “Design the MLOps pipeline for our scoring model, from ingestion to deployment.”

    Card for the “Building an end-to-end MLOps pipeline” skill

    Skill published by wshobson under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to build an MLOps pipeline from data to deployment
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md7.2 KB

    Origin and licence

    Listed unmodified

    Author
    wshobson
    Source
    github.com/wshobson/agents/tree/0874a27b17a22e2b7c2e2bcd725768e0803cad06/plugins/machine-learning-ops/skills/ml-pipeline-workflow
    Licence
    MIT

    Notice

    « ml-pipeline-workflow » (wshobson, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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