Agent skill · pproenca
mlflow-mlops-migration
Guided workflow for taking any ML codebase — including one with no experiment tracking at all, or one full of MLflow 2-era idioms — to a production-grade open-source MLflow 3 setup with dev/staging/prod environments, registry-based promotion, and served models. Walks seven phases with a developer who may have zero MLflow 3 experience — assess the codebase (scripted read-only audit), model the registry domain (per-environment model names, aliases, gates), stand up tracking per environment, restructure training code to MLflow 3 idioms, wire evaluation-gated promotion, serve and smoke-test, then run the ongoing MLOps loop. Use when asked to set up MLflow, migrate to MLflow 3, productionize model training and serving, or design a dev/staging/prod MLOps cycle. Pairs with the sibling mlflow-3 rule pack for every API decision.
What it needs
About 4k tokens when loaded.
What this skill does
MLflow MLOps Migration A phased, gated workflow that turns an arbitrary ML codebase — however unstructured — into a production-grade open-source MLflow 3 setup covering the full MLOps cycle: tracked experiments, a domain-modelled registry, dev/staging/prod separation, evaluation-gated promotion, and served models. It is written to be driven with a developer who has no MLflow 3 experience: every phase produces a reviewable artifact before anything is changed, and every API decision defers to the sibling mlflow-3 rule pack (which is pinned to mlflow 3.15.1 and names the MLflow 2-era idioms this migration exists to remove). When to Apply Use this skill when: A team wants MLflow (or has a messy/partial MLflow 2 setup) and needs the path to a production-grade MLflow 3 deployment — not just API fixes. Training code exists but experiments are untracked, models are shipped by copying files, or "deployment" means a pickle in a bucket. You are asked to design or review a dev/staging/prod model-promotion story. An MLflow 2 → 3 migration touches infrastructure (stages, ./mlruns file stores, MLServer), not only client code. Don't use it for a single API question — read the relevant mlflow-3 rule directly. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills pproenca/mlflow-mlops-migration