Model Monitoring
Monitor model performance, detect data drift, concept drift, and anomalies in production using Prometheus, Grafana, and MLflow
npx skills add majiayu000/claude-skill-registry --skill model-monitoring-aj-geddes-useful-ai-prompts --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Model Monitoring ## Overview Monitoring deployed machine learning models ensures they continue to perform well in production, detecting data drift, concept drift, and performance degradation. ## When to Use - When models are deployed in production environments serving real users - When detecting data drift or concept drift in input features - When tracking model performance metrics over time - When ensuring model reliability, accuracy, and operational health - When implementing ML observability and alerting systems - When establishing thresholds for model retraining or intervention ## Monitoring Components - **Performance Metrics**: Accuracy, latency, throughput - **Data Drift**: Distribution changes in input features - **Concept Drift**: Changes in target variable relationships - **Output Drift**: Changes in prediction distribution - **Feature Drift**: Individual feature distribution changes - **Anomaly Detection**: Unusual samples in production ## Monitoring Tools - **Prometheus**: Metrics collection and storage - **Grafana**: Visualization and dashboarding - **MLflow**: Model tracking and registry - **TensorFlow Data Validation**: Data statistics - **Evidently**: Drift detecti
- Overview
- When to Use
- Monitoring Components
- Monitoring Tools
- Python Implementation
- Drift Detection Techniques
- Alert Thresholds
- Deliverables
What does the Model Monitoring skill do?
Monitor model performance, detect data drift, concept drift, and anomalies in production using Prometheus, Grafana, and MLflow
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill model-monitoring-aj-geddes-useful-ai-prompts --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.