explainability
See the main Model Explainability skill for comprehensive XAI coverage.
Installation
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
View source ↗GuidesSkill instructions
Explainability
This skill is covered in detail in the main Model Explainability skill.
Please refer to: 44-ai-governance/model-explainability/SKILL.md
That skill covers:
- What is explainability and why it matters
- Types of explanations (global, local, counterfactual)
- SHAP (SHapley Additive exPlanations)
- LIME (Local Interpretable Model-agnostic Explanations)
- LLM explainability (attention weights, chain-of-thought)
- Presenting explanations to users
- Explainability for different audiences
- Trade-offs (accuracy vs explainability)
- Tools (SHAP, LIME, InterpretML, Captum, Alibi)
- Explainability in production
- Regulatory requirements (GDPR, AI Act)
- Implementation examples
Related Skills
-
44-ai-governance/model-explainability(Main skill) -
44-ai-governance/auditability -
44-ai-governance/human-approval-flows
Examples
Read the usage examples in the source repository.
View source ↗Source history
- Indexed on
- 2026-01-20
- Index updated
- 2026-01-26
- Branch
- main
Index and sync dates describe this directory. View the source repository for code history.
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