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machine-learning-ops

v1.2.2

ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows

CodexClaude Code2 Skills

By Seth HobsonLicense: MIT39.9k GitHub starsUpdated 3 days ago

Directory evidence

Runtimes
Codex and Claude Code
Parsed components
2 skill or MCP entries
Source updated
Sep 21, 2026
Manifest status
Canonical path parsed

The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →

Install machine-learning-ops for Codex and Claude Code

Installs for the current user
codex plugin marketplace add wshobson/agents
codex plugin marketplace upgrade claude-code-workflows
codex plugin add machine-learning-ops@claude-code-workflows

Paste and run these commands in a terminal with Codex. They add and refresh the claude-code-workflows catalog, then install this plugin.

Compatibility: the page URL and API slug “machine-learning-ops” remain stable.

  • Codex: machine-learning-ops@agent-plugin-marketplace → machine-learning-ops@claude-code-workflows

The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.

Get the source manually
git clone https://github.com/wshobson/agents

Clone the source repository, then follow its setup instructions to add the plugin to a compatible client. The plugin root is plugins/machine-learning-ops/.

Plugin files

plugins/machine-learning-ops/
├── .codex-plugin/plugin.json
├── .claude-plugin/plugin.json
├── skills/ml-pipeline-workflow/SKILL.md
└── skills/recsys-pipeline-architect/SKILL.md

Included Skills2

ml-pipeline-workflowskills/ml-pipeline-workflow/SKILL.md

Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.

recsys-pipeline-architectskills/recsys-pipeline-architect/SKILL.md

Design composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework popularized by xAI's open-sourced X For You algorithm. Use when building any system that picks "the top K items for a (user, context)" — content feeds, search ranking, RAG rerankers, task prioritizers, notification triage, ad selection.

Plugin manifests2

plugins/machine-learning-ops/.codex-plugin/plugin.json
{
  "name": "machine-learning-ops",
  "version": "1.2.2",
  "description": "ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows",
  "skills": "./skills/",
  "author": {
    "name": "Seth Hobson",
    "email": "[email protected]"
  },
  "license": "MIT",
  "interface": {
    "displayName": "Machine Learning Ops",
    "shortDescription": "ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps…",
    "category": "Coding"
  }
}
plugins/machine-learning-ops/.claude-plugin/plugin.json
{
  "name": "machine-learning-ops",
  "version": "1.2.2",
  "description": "ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows",
  "author": {
    "name": "Seth Hobson",
    "email": "[email protected]"
  },
  "license": "MIT"
}

For maintainers

If you maintain this plugin, link to this source-backed listing from your README so users can review its manifest and indexed components.

[machine-learning-ops on Agent Plugins Marketplace](https://pluginsmp.com/plugins/machine-learning-ops)