Notebook Ml Architect | Agent Skills Atlas

About this skill

Expert guidance for auditing, refactoring, and designing machine learning Jupyter notebooks with production-quality patterns. Use when: (1) Analyzing notebook structure and identifying anti-patterns, (2) Detecting data leakage and reproducibility issues, (3) Refactoring messy notebooks into modular pipelines, (4) Generating templates for ML workflows (EDA, classification, experiments), (5) Adding reproducibility instrumentation (seeding, logging, env capture), (6) Converting notebooks to Python scripts, (7) Generating experiment summary reports. Triggers on: ML notebook, Jupyter audit, notebook refactor, data leakage, experiment template, ipynb best practices, notebook to script, reproducibility.

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0 potential findings · Scanned 11/4/2026 · Scanner 0.2.1

Content SHA-256: e3b3fed2daf5979dc8945216957620765a30567450328e0be5032c8f9025ca82

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Original listing metadata

Original name

notebook-ml-architect

Original description

About this listing

Category: Science & research
Reported license: Not specified
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.