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Found 869 Skills
Use when monitoring brand sentiment on Xiaohongshu, tracking public opinion, managing reputation, responding to negative feedback, analyzing brand perception trends, or handling PR crises
Set up comprehensive infrastructure monitoring with Prometheus, Grafana, and alerting systems for metrics, health checks, and performance tracking.
Implement uptime monitoring and status page systems for tracking service availability. Use when monitoring application uptime, creating status pages, or implementing health checks.
Implement synthetic monitoring and automated testing to simulate user behavior and detect issues before users. Use when creating end-to-end test scenarios, monitoring API flows, or validating user workflows.
Web page monitoring, change detection, and availability tracking. Use when tracking content changes, detecting when pages go down, monitoring for updates, preserving content before deletion, or generating feeds for pages without RSS. Covers Visualping, ChangeTower, Distill.io, and self-hosted monitoring solutions.
Application monitoring and observability setup for Python/React projects. Use when configuring logging, metrics collection, health checks, alerting rules, or dashboard creation. Covers structured logging with structlog, Prometheus metrics for FastAPI, health check endpoints, alert threshold design, Grafana dashboard patterns, error tracking with Sentry, and uptime monitoring. Does NOT cover incident response procedures (use incident-response) or deployment (use deployment-pipeline).
Track large cryptocurrency transactions and whale wallet movements in real-time. Use when tracking large holder movements, exchange flows, or wallet activity. Trigger with phrases like "track whales", "monitor large transfers", "check whale activity", "exchange inflows", or "watch wallet".
Tracks competitor page changes over time. Captures snapshots, detects diffs, alerts on significant changes. Supports Tavily site discovery for URL enumeration. Use when monitoring competitive intelligence, pricing changes, or feature tracking.
Know when your AI breaks in production. Use when you need to monitor AI quality, track accuracy over time, detect model degradation, set up alerts for AI failures, log predictions, measure production quality, catch when a model provider changes behavior, build an AI monitoring dashboard, or prove your AI is still working for compliance. Covers DSPy evaluation for ongoing monitoring, prediction logging, drift detection, and alerting.
Use after creating PR - monitor CI pipeline, resolve failures cyclically until green or issue is identified as unresolvable
PostgreSQL monitoring - metrics, alerting, observability
Heartbeat-based health monitoring for background workers with configurable thresholds, rolling duration windows, failure rate calculation, and stuck job detection.