ml-adoption-playbook
About ml-adoption-playbook
End-to-end methodology for AI agents and software engineers to add machine learning algorithms to existing non-ML codebases. Covers problem framing, data readiness, architectural decoupling, and baseline model integration. Use when adding a machine learning capability to a codebase that has none, from problem framing through a baseline model.
Install
Copy the command and run it in a terminal.
$
npx skills add https:/After installing, type/ml-adoption-playbookin Claude Code to confirm it loaded.
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