About this skill
Make AI model decisions interpretable and transparent. Use for: implementing SHAP for feature importance analysis, using LIME for local explanations, creating attention visualizations for deep learning, generating counterfactual explanations, building inherently interpretable models, visualizing decision boundaries and activation maps, explaining predictions to stakeholders, debugging model behavior, ensuring regulatory compliance with explainability requirements, and building trust in AI systems.
Quick start
- Copy the install prompt. Use the green button above this README.
- Send it to your agent. Paste it into your coding agent’s chat and send.
- Review the setup. Your agent checks the skill’s instructions, requirements, and installation scope.
Review, license & listing details
This is an imported listing. We haven’t certified its safety, license, or compatibility. Skills may include executable scripts.
Only SKILL.md was scanned. Supporting files and scripts were not checked. No safety grade has been assigned.
0 potential findings · Scanned 11/4/2026 · Scanner 0.2.1
Content SHA-256: c628b412f8a5cd01c6b1ef0111ff424d124a6b1d4743abf3fc22880dc5d8363f
About this listing
- Category
- Product & design
- Reported license
- MIT
- Listing language (estimated)
- English
- Review status
- Not individually reviewed
- Agent compatibility
- Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.