model monitoring
✓Monitor model performance, detect data drift, concept drift, and anomalies in production using Prometheus, Grafana, and MLflow
Installation
SKILL.md
Monitoring deployed machine learning models ensures they continue to perform well in production, detecting data drift, concept drift, and performance degradation.
Monitor model performance, detect data drift, concept drift, and anomalies in production using Prometheus, Grafana, and MLflow Source: aj-geddes/useful-ai-prompts.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill model monitoring Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor
Security certified for safe and reliable code One-click installation with simplified configuration Compatible with Claude Code, Cursor, and more
Facts (cite-ready)
Stable fields and commands for AI/search citations.
- Install command
npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill model monitoring- Category
- </>Dev Tools
- Verified
- ✓
- First Seen
- 2026-02-01
- Updated
- 2026-02-18
Quick answers
What is model monitoring?
Monitor model performance, detect data drift, concept drift, and anomalies in production using Prometheus, Grafana, and MLflow Source: aj-geddes/useful-ai-prompts.
How do I install model monitoring?
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill model monitoring Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor
Where is the source repository?
https://github.com/aj-geddes/useful-ai-prompts
Details
- Category
- </>Dev Tools
- Source
- skills.sh
- First Seen
- 2026-02-01