Skill UI

A comprehensive skill set for building, deploying, and managing production-grade Machine Learning systems. Expertise spans modern frameworks (PyTorch, TensorFlow), model serving using Kubernetes, advanced feature engineering (Feast, Tecton), and robust MLOps practices (monitoring, A/B testing, CI/CD). Focuses on delivering scalable, reliable, and business-value-driven AI solutions.

Automates guidance for deploying machine learning models with quantization, covering tooling, best practices, and production readiness for inference, MLops, and monitoring tasks.

Automates guidance for model registry manager tasks within ML deployment, covering serving, MLOps pipelines, monitoring, and production optimization whenever that trigger phrase appears.

Provides automated guidance for managing model versions in ML deployment, including serving, monitoring, and production optimization whenever someone requests the model versioning manager.

This skill guides the implementation of comprehensive, real-time monitoring for APIs. It covers collecting key metrics (latency, error rates, request rate), setting up health and readiness endpoints, building detailed Grafana dashboards, and implementing SLO-based alerting (following the RED method). Use this when you need to ensure API reliability, high availability, and performance in a production environment.

Enables Claude to monitor and analyze application CPU usage, detect hotspots, inefficient loops and regexes, and offer optimization strategies such as asynchronous processing or algorithmic improvements to boost performance.

This skill provides comprehensive monitoring and comparative analysis of cross-chain bridges in the DeFi ecosystem. It tracks key metrics such as Total Value Locked (TVL), transaction volume, typical fees, and real-time transfer status across major networks (e.g., Ethereum, Arbitrum, Polygon). Use this tool to research bridge safety, compare transfer routes before depositing funds, or track specific transaction hashes across multiple protocols like Wormhole, LayerZero, and Stargate.

Monitors PostgreSQL and MySQL health with real-time metrics, predictive alerts, and automated remediation, letting you preempt bottlenecks and respond to production issues quickly.

Enables Claude to monitor database transactions with the database-transaction-monitor plugin, detect long-running operations, lock contention, and rollback spikes, and streamline response through the `/txn-monitor` command.

Automates comprehensive monitoring and alerting of HTTP, database, API, background job, and client errors so teams can track, analyze, and resolve reliability issues before they impact users.

Delivers end-to-end monitoring setups—structured logging, Prometheus/Grafana dashboards, alerting rules, distributed tracing, and load/profile testing—so teams can observe services, debug production issues, and plan capacity.

Documents setting up OpenTelemetry tracing/metrics, Prometheus/Grafana monitoring, structured logging, and alerting rules so teams can instrument services, track performance, and respond to incidents.