datarobot-model-explainability
datarobot-model-explainability is a Model training & evaluation skill for AI agents, published by datarobot-oss in the datarobot-agent-skills repository on GitHub. Skillspace rates datarobot-model-explainability D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Tools and guidance for model explainability, prediction explanations, feature impact analysis, SHAP values, SHAP distributions, anomaly assessment, and model diagnostics. Use when analyzing model explanations, feature impact, SHAP values, SHAP distributions, anomaly assessment, or diagnosing model behavior.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 22
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
- 84 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 1 collections
What the scanner flagged
- mentions secrets in text
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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