Cortex - ML Pipeline Builder — Agent Skill | MCP App Store

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Cortex - ML Pipeline Builder

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Guided ML pipeline builder that walks an agent through data validation, feature engineering, training, evaluation, and serving endpoints for classification or r

triggers:build ml modeltrain a modelprediction pipelineclassificationregression

GitHub SKILL.md

What it does\n\nCortex provides a step-by-step playbook for building production-ready machine learning pipelines. It guides the agent through environment detection, defining success metrics, simple baseline modeling, data validation, feature engineering, training, evaluation, and deploying a serving endpoint with monitoring and instrumentation. The instructions emphasize reproducibility, experiment tracking, and avoiding premature complexity (start with logistic regression or gradient boosting).\n\n## When to use it\n\nUse Cortex when asked to build or improve a machine learning model or prediction pipeline - e.g., "build ML model", "train a model", "prediction pipeline", "classification", or "regression". It's appropriate for projects needing a practical path from raw data to a served model and monitoring plan.\n\n## What's included\n\n- Scripts: none bundled in the repo path (has_scripts=false) - the SKILL outlines canonical script names to create (data_validation.py, features.py, train.py, evaluate.py, serve.py).\n- References: none included in this skill.\n- Instructions: detailed procedural steps covering environment detection, metric selection, baseline modeling, data validation, feature pipeline design, training best practices, evaluation, serving setup (FastAPI/Flask), and production monitoring.\n\n## Compatible agents\n\nCompatible with Claude Code-style agent runtimes and general LLM-driven developer agents that can run shell commands and generate code (e.g., Claude Code, Copilot-style assistants, or other code-focused agents).

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