xgb-modeling

xgb-modeling is a Model training & evaluation skill for AI agents, published by aliyun in the qwen-dianjin repository on GitHub. Skillspace rates xgb-modeling C (70/100) and it passed the safety scan; the rating is based on static analysis only.

【XGBoost建模】当用户需要"训练模型"、"跑一个基线"、"建个模型试试"、"对比特征方案效果"、"预测一下"、"跑个xgb"、"看AUC/KS/BCR"时使用。支持多特征方案对比、AUC/KS/BCR/Brier评估、Bootstrap置信区间、概率校准曲线、稳定性分析（Mann-Kendall趋势检验）。前提条件：需要已完成特征分析并确定特征方案。**不做超参数调优，调参请用 xgb-tuning**；不做特征工程。与 auto-experiment 的区别：本 Skill 按用户指定方案训练，auto-experiment 自主探索特征组合。

Grade
C
Quality
70 / 100
Safety
Passed
GitHub stars
571

Unproven: rated by static analysis only, not yet compared head-to-head.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubaliyun/qwen-dianjin

Our review

Architecture
92 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
Not declared. Check the repository before reusing it.
Adoption
Adopted by 0 other repositories, in 0 collections

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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