0x-professor/agent-skills-hub/ml-experiment-tracker

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

Install

npx vskill@latest install 0x-professor/agent-skills-hub/ml-experiment-tracker

SKILL.md

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.

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

See the full security report

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

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Source

Popularity

Repository stars
11
Repository forks
2
7-day trend score
12

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