model-explainability-tool

Model Explainability Tool - Auto-activating skill for ML Training. Triggers on: model explainability tool, model explainability tool Part of the ML Training skill category.

1.00x

Quality

Does it follow best practices?

Impact

100%

1.00x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./planned-skills/generated/07-ml-training/model-explainability-tool/SKILL.md

Evaluation results

100%

Credit Loan Decision Explainability

Tabular model explainability pipeline

Criteria

Without context

With context

Python implementation

100%

pip requirements file

100%

Supported ML framework

100%

Production code structure

100%

Model evaluation metrics

100%

Saved model artifact

100%

Global feature importance

100%

Explanation report JSON

100%

Data preparation step

100%

Reproducibility

100%

Without context: $0.3074 · 1m 25s · 20 turns · 23 in / 4,056 out tokens

With context: $0.7137 · 2m 46s · 39 turns · 85 in / 8,772 out tokens

100%

Customer Churn Prediction with Tracked Experiments

End-to-end ML pipeline with experiment tracking

Criteria

Without context

With context

Python scripts

100%

pip requirements

100%

Supported framework

100%

Data preparation

100%

Model training

100%

Hyperparameter tuning

100%

Experiment tracking log

100%

Best model report

100%

Production code structure

100%

Validation metrics

100%

Without context: $0.3346 · 1m 36s · 20 turns · 23 in / 5,430 out tokens

With context: $0.6462 · 2m 26s · 30 turns · 28 in / 8,794 out tokens

100%

Explaining Sentiment Classifier Predictions

Neural network prediction explanation

Criteria

Without context

With context

Python implementation

100%

pip requirements file

100%

Supported framework usage

100%

Production code structure

100%

Model validation metrics

100%

Global explanation output

100%

Local explanation output

100%

Directional attribution

100%

Data preparation step

100%

Step-by-step structure

100%

Without context: $0.4429 · 2m 3s · 25 turns · 24 in / 6,453 out tokens

With context: $0.6850 · 2m 55s · 36 turns · 38 in / 8,668 out tokens

Repository: jeremylongshore/claude-code-plugins-plus-skills
Commit: f17dd51

Evaluated: 18 days ago
Agent: Claude Code
Model: Claude Sonnet 4.6

Table of Contents

Credit Loan Decision Explainability Customer Churn Prediction with Tracked Experiments Explaining Sentiment Classifier Predictions

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