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Found 1,228 Skills
Data validation using Great Expectations. Expectation suites, checkpoints, and data docs for pipeline monitoring.
Desktop GUI and CLI app for running and monitoring Quip Network nodes, built with Tauri v2 and Rust
Quota tracking, threshold monitoring, and graceful degradation for rate-limited API services. quota, rate limiting, usage limits, thresholds.
Run automated Lighthouse audits for Core Web Vitals and SEO. Use when: checking page performance; auditing SEO technical issues; monitoring Core Web Vitals; comparing before/after optimization; batch auditing multiple URLs
Prometheus monitoring and alerting for cloud-native observability. USE WHEN: Writing PromQL queries, configuring Prometheus scrape targets, creating alerting rules, setting up recording rules, instrumenting applications with Prometheus metrics, configuring service discovery. DO NOT USE: For building dashboards (use /grafana), for log analysis (use /logging-observability), for general observability architecture (use senior-software-engineer with infrastructure focus). TRIGGERS: metrics, prometheus, promql, counter, gauge, histogram, summary, alert, alertmanager, alerting rule, recording rule, scrape, target, label, service discovery, relabeling, exporter, instrumentation, slo, error budget.
CI/CD: GitHub Actions, GitLab CI, Jenkins, ArgoCD, GitOps, monitoring.
Reporting framework for monitoring trust, sentiment, and regulator-facing KPIs.
Comprehensive MLOps workflows for the complete ML lifecycle - experiment tracking, model registry, deployment patterns, monitoring, A/B testing, and production best practices with MLflow
CI/CD pipeline design, containerization, and infrastructure management. Handles Docker, Kubernetes, monitoring setup (Prometheus/Grafana), and infrastructure-as-code (Terraform/Pulumi).
Quickly set up monitoring for a competitor company. Tracks news, product updates, funding, and public announcements.
Deploy production recommendation systems with feature stores, caching, A/B testing. Use for personalization APIs, low latency serving, or encountering cache invalidation, experiment tracking, quality monitoring issues.
Process management with PM2 — start, stop, restart, monitor long-running processes. Use when: keeping services alive, auto-restart on crash, managing daemon processes, ecosystem configs, log management, startup scripts, process monitoring. Triggers: pm2, process manager, keep alive, daemon, auto-restart, ecosystem config, process monitoring.