Individual skill

mlflow-data-pipelines

MLflow for data engineering — tracking server setup (PostgreSQL backend + S3 artifacts), experiment tracking (params/metrics/artifacts/autolog), ETL job metadata logging (row counts, DQ metrics, lineage tags), Model Registry (register/alias/promote), model serving (pyfunc/REST API/batch scoring), MLproject files, Airflow integration (MLflowClientHook/XCom/model promotion), Spark integration (mlflow.spark.autolog/log_model/Delta metadata)

skills/mlflow_pipelines/SKILL.md

Source commit 75f49e7bf30c9908a0921911755abb6cc6c01f7b

What was checked

Matches the observed repository HEAD

Yes

Scanner rules are current

Yes

Repository scan complete

No

Skill scan complete

No

Observed behavior

Network or broad shell

Last checked

Nov 11, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.