技能详情（站内镜像，无评论）
作者：Muhammad Mazhar Saeed @0x-professor
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v0.1.0
统计：⭐ 0 · 381 · 4 current installs · 4 all-time installs
⭐ 0
安装量（当前） 4
🛡 VirusTotal ：可疑 · OpenClaw ：良性
Package：0x-professor/ml-experiment-tracker
安全扫描（ClawHub）
- VirusTotal ：可疑
- OpenClaw ：良性
OpenClaw 评估
The skill's files, instructions, and small Python helper are coherent with its stated purpose of producing reproducible ML experiment plans and do not request unrelated credentials or perform unexpected network or system access.
目的
Name/description match the provided script and docs: the skill generates structured experiment plans and suggests logging to trackers. There are no unexpected required binaries, env vars, or services.
说明范围
SKILL.md directs the agent to run the bundled script and read the local tracking guide. The script only reads an optional JSON input, validates size, and writes an output file in json/md/csv formats — it does not access external endpoints or arbitrary system credentials.
安装机制
No install spec — instruction-only plus a small Python script. This is low-risk; the script uses only Python stdlib and writes local output files.
证书
The skill requests no environment variables or secrets. Recommendations to log to MLflow are advisory only and do not require embedded credentials in the skill.
持久
Skill is not forced always-on and does not modify agent/system configurations. It is user-invocable and may be invoked by the model (normal behavior).
综合结论
This skill appears coherent and low-risk: it only generates experiment plans and writes them to a user-specified output path. Before running, (1) choose a safe output path to avoid overwriting important files, (2) inspect the included script if you have concerns — it's short and uses only standard libraries, (3) if you plan to integrate the plan with an external tracker (e.g., MLflow), provide credentials to that tracker separately and review …
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Ml Experiment Tracker」。简介：Plan reproducible ML experiment runs with explicit parameters, metrics, and art…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/0x-professor/ml-experiment-tracker/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
name: ml-experiment-tracker
description: Plan reproducible ML experiment runs with explicit parameters, metrics, and artifacts. Use before model training to standardize tracking-ready experiment definitions.
---
# 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.