Implement model drift monitoring using Evidently AI, statistical tests (PSI, KS), and custom metrics to detect data drift and concept drift in production ML systems. Set up automated alerting and reporting workflows to catch degradation before it impacts business metrics.
安装
npx skills add pjt222/agent-almanac --skill monitor-model-driftnpx skills add pjt222/agent-almanac --skill monitor-model-drift -a claude-code -gnpx skills add pjt222/agent-almanac --skill monitor-model-drift -a codex -ggemini skills install https://github.com/pjt222/agent-almanac.git --path i18n/caveman-lite/skills/monitor-model-driftgh skill install pjt222/agent-almanac monitor-model-driftgit clone --depth 1 https://github.com/pjt222/agent-almanac /tmp/pjt222__agent-almanac
mkdir -p ~/.claude/skills ~/.agents/skills
cp -R /tmp/pjt222__agent-almanac/i18n/caveman-lite/skills/monitor-model-drift ~/.claude/skills/monitor-model-drift # Claude Code
cp -R /tmp/pjt222__agent-almanac/i18n/caveman-lite/skills/monitor-model-drift ~/.agents/skills/monitor-model-drift # Codex, Cursor, Gemini CLI, Copilot, OpenCode