SkillHub

ml-experiment-tracker

v0.1.0

Plan reproducible ML experiment runs with explicit parameters, metrics, and artifacts. Use before model training to standardize tracking-ready experiment definitions.

Sourced from ClawHub, Authored by Muhammad Mazhar Saeed

Installation

Please help me install the skill `ml-experiment-tracker` from SkillHub official store. npx skills add 0x-Professor/ml-experiment-tracker

ML Experiment Tracker

Overview

Generate structured experiment plans that can be logged consistently in experiment tracking systems.

Workflow

  1. Define dataset, target task, model family, and parameter search space.
  2. Define metrics and acceptance thresholds before training.
  3. Produce run plan with version and artifact expectations.
  4. Export the run plan for execution in tracking tools.

Use Bundled Resources

  • Run scripts/build_experiment_plan.py to generate consistent run plans.
  • Read references/tracking-guide.md for reproducibility checklist.

Guardrails

  • Keep inputs explicit and machine-readable.
  • Always include metrics and baseline criteria.