Overview
- Skill Key
- 0x-professor/ml-experiment-tracker
- Author
- 0x-professor
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/0x-professor/ml-experiment-tracker
- Latest Commit SHA
- e35e314163a86a0c680a4b67047a4af977e56078
Official OpenClaw
rules
15%
ml-experiment-tracker
Plan reproducible ML experiment runs with explicit parameters, metrics, and artifacts. Use before model training to standardize tracking-ready experiment definitions.
Stars
0
Installs
0
Status
ACTIVE
Visibility
PUBLIC
安装方式
直接复制以下提示词，发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店，若未安装，请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店，然后安装 ml-experiment-tracker 技能。 若已安装，则直接安装 ml-experiment-tracker 技能。
Extracted Content
SKILL.md excerpt
# 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.
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