model-explanation
model-explanation is a Model training & evaluation skill for AI agents, published by aliyun in the qwen-dianjin repository on GitHub. Skillspace rates model-explanation D (65/100) and it passed the safety scan; the rating is based on static analysis only.
【模型解释】当用户问"为什么模型这样预测"、"哪些特征最重要"、"解释一下这个样本"、"模型怎么做的决策"、"feature importance"、"为什么给这个分数"时使用。基于SHAP的模型解释，支持全局特征重要性、单样本预测解释、特征交互分析。前提条件：需要已训练好的XGBoost模型。不做模型训练，不做特征筛选。与 feature-analysis 的区别：本 Skill 解释"已训练模型的决策逻辑"，feature-analysis 分析"建模前的特征质量"。
- Grade
- D
- Quality
- 65 / 100
- Safety
- Passed
- GitHub stars
- 612
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.
Our review
- Architecture
- 94 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Not checked yet
- Category is a classifier prediction; no model has read this skill 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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