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Found 1,444 Skills
Redis observability guidance — which metrics to monitor (memory, connections, hit ratio, ops/sec, rejected connections), which built-in commands to reach for during incident triage (SLOWLOG, INFO, MEMORY DOCTOR, CLIENT LIST, FT.PROFILE), and when to use the Redis Insight GUI. Use when setting up monitoring or alerts for a Redis instance, diagnosing a performance regression, profiling a slow FT.SEARCH query, or wiring Redis metrics into Prometheus, Datadog, or similar.
Router skill for LLMQuant portfolio workflows. Use when the user needs company profiles, thesis tracking, theme research, watchlist monitoring, or alert management.
Implement distributed tracing with correlation IDs, trace propagation, and span tracking across microservices. Use when debugging distributed systems, monitoring request flows, or implementing observability.
DevOps and Infrastructure expert with comprehensive knowledge of CI/CD pipelines, containerization, orchestration, infrastructure as code, monitoring, security, and performance optimization. Use PROACTIVELY for any DevOps, deployment, infrastructure, or operational issues. If a specialized expert is a better fit, I will recommend switching and stop.
Sentry error monitoring and performance tracing patterns for Next.js applications.
Gathers and filters information systematically. Applies scanning, focusing, filtering, triangulating, monitoring, and synthesizing modes to build accurate situational awareness. Use when researching, verifying claims, monitoring signals, or combining multiple sources. Triggers on "what's happening", "verify this", "monitor for", "gather information", "is this true".
Track Clawdbot AI model usage and estimate costs. Use when reporting daily/weekly costs, analyzing token usage across sessions, or monitoring AI spending. Supports Claude (opus/sonnet), GPT, and Codex models.
Automatically discover observability and monitoring skills when working with Prometheus, Grafana, distributed tracing, structured logging, metrics, alerting, dashboards, or monitoring. Activates for observability development tasks.
Health monitoring knowledge and procedures for infrastructure platforms. Use when assessing system health, running health audits, or setting up monitoring.
Use when "deploying ML models", "MLOps", "model serving", "feature stores", "model monitoring", or asking about "PyTorch deployment", "TensorFlow production", "RAG systems", "LLM integration", "ML infrastructure"
Set up continuous web monitoring with Yutori Scouts. Use when the user wants to track news, competitors, product updates, funding rounds, price changes, or any recurring web information.
Framework for monitoring activation, engagement, and monetization guardrails.