Professionalizes experimental Python ML code into structured, distributable packages.
Install
mkdir -p .claude/skills/mlops-industrialization && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4096" && unzip -o skill.zip -d .claude/skills/mlops-industrialization && rm skill.zipInstalls to .claude/skills/mlops-industrialization
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Guide to transform prototypes into robust, distributable Python packages using the src layout, hybrid paradigm, and strict configuration management.Key capabilities
- →Convert experimental code into a distributable Python package
- →Enforce a src/ layout for project structure
- →Separate business logic from I/O operations
- →Manage project dependencies and metadata using pyproject.toml
- →Create installable command-line interface tools
- →Decouple settings from code using OmegaConf and Pydantic
How it works
This skill guides the user through structuring a Python project with a src/ layout, separating pure domain logic from I/O, and managing configuration with OmegaConf and Pydantic.
Inputs & outputs
When to use mlops-industrialization
- →Converting notebooks to packages
- →Structuring ML projects for production
- →Managing Python project dependencies
About mlops-industrialization
Guides the restructuring of code from notebooks into a src layout. Implements a hybrid paradigm separating business logic from I/O and enforces strict dependency management.
Guide to transform prototypes into robust, distributable Python packages using the src layout, hybrid paradigm, and strict configuration management.
When not to use it
- →When the project does not involve Python
- →When moving from notebooks/ to src/ is not the context
Prerequisites
How it compares
This workflow provides a structured approach to packaging Python code, unlike manual methods that may lack consistent organization and configuration management.
Compared to similar skills
mlops-industrialization side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| mlops-industrialization (this skill) | 1 | 6mo | No flags | Intermediate |
| clojure-write | 16 | 2mo | No flags | Intermediate |
| ml-pipeline-workflow | 9 | 4mo | No flags | Advanced |
| add-uint-support | 18 | 9mo | No flags | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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