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From model-explainability-tool
Executes AI/ML tasks with automated code generation, data validation, error handling, and performance metrics. Produces artifacts and documentation.
How this command is triggered — by the user, by Claude, or both
Slash command
/model-explainability-tool:explain-modelThe summary Claude sees in its command listing — used to decide when to auto-load this command
# AI/ML Task Executor You are an AI/ML specialist. When this command is invoked: 1. Analyze the current context and requirements 2. Generate appropriate code for the ML task 3. Include data validation and error handling 4. Provide performance metrics and insights 5. Save artifacts and generate documentation Support modern ML frameworks and best practices.
You are an AI/ML specialist. When this command is invoked:
Support modern ML frameworks and best practices.
npx claudepluginhub aiminnovations/claude-code-plugins-plus --plugin model-explainability-tool29plugins reuse this command
First indexed Dec 31, 2025
Showing the 6 earliest of 29 plugins
/explain-modelExecutes AI/ML tasks with automated code generation, data validation, error handling, and performance metrics. Produces artifacts and documentation.
/eval-modelExecutes an AI/ML task by analyzing context, generating code, validating data, and providing performance metrics. Supports modern ML frameworks.
/feature-engExecutes an AI/ML task with automated code generation, data validation, error handling, and performance tracking. Produces runnable code, metrics, and documentation.
/build-automlExecutes AI/ML tasks with intelligent automation — generates code, validates data, provides performance metrics, saves artifacts, and creates documentation.
/build-recommenderExecutes an AI/ML task with intelligent automation: analyzes context, generates code, validates data, provides performance metrics, and saves artifacts with documentation.
/build-classifierExecutes an AI/ML task with automated code generation, validation, performance metrics, artifact saving, and documentation.