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Found 844 Skills
Setup Sentry in React Native using the wizard CLI. Use when asked to add Sentry to React Native, install @sentry/react-native, or configure error monitoring for React Native or Expo apps.
Strategic guidance for operationalizing machine learning models from experimentation to production. Covers experiment tracking (MLflow, Weights & Biases), model registry and versioning, feature stores (Feast, Tecton), model serving patterns (Seldon, KServe, BentoML), ML pipeline orchestration (Kubeflow, Airflow), and model monitoring (drift detection, observability). Use when designing ML infrastructure, selecting MLOps platforms, implementing continuous training pipelines, or establishing model governance.
Git-centric implementation workflow. Enforces clean checkout, creates a properly named branch, tracks progress in a WIP markdown file, and commits continuously so git logs serve as the primary monitoring channel. Use when starting instructed, offer for any plan-based implementation task.
Redis-backed SSE stream management with stream registry, heartbeat monitoring, completion store for terminal events, and automatic orphan cleanup via background guardian process.
Set up comprehensive observability for Groq integrations with metrics, traces, and alerts. Use when implementing monitoring for Groq operations, setting up dashboards, or configuring alerting for Groq integration health. Trigger with phrases like "groq monitoring", "groq metrics", "groq observability", "monitor groq", "groq alerts", "groq tracing".
Use before launching sequences to validate content, data, compliance, and monitoring.
Monitoring and observability patterns for Prometheus metrics, Grafana dashboards, Langfuse LLM tracing, and drift detection. Use when adding logging, metrics, distributed tracing, LLM cost tracking, or quality drift monitoring.
Deploy ContextVM servers and clients in production environments. Use when setting up production deployments, configuring Docker containers, managing environment variables, choosing relay configurations, or monitoring running services.
Elasticsearch and Elastic APM integration with Serilog structured logging for .NET applications. Use when: (1) Implementing or configuring Serilog with Elasticsearch sink, (2) Setting up Elastic APM with data streams and authentication, (3) Creating logging extension methods in Infrastructure layer, (4) Enriching logs with app-name and app-type properties, (5) Configuring log levels and environment-specific logging, (6) Questions about logging security (PII, credentials), or (7) Troubleshooting observability and monitoring setup.
Use this skill to work with Microsoft Foundry (Azure AI Foundry): deploy AI models from catalog, build RAG applications with knowledge indexes, create and evaluate AI agents. USE FOR: Microsoft Foundry, AI Foundry, deploy model, model catalog, RAG, knowledge index, create agent, evaluate agent, agent monitoring. DO NOT USE FOR: Azure Functions (use azure-functions), App Service (use azure-create-app).
Set up comprehensive observability for Mistral AI integrations with metrics, traces, and alerts. Use when implementing monitoring for Mistral AI operations, setting up dashboards, or configuring alerting for Mistral AI integration health. Trigger with phrases like "mistral monitoring", "mistral metrics", "mistral observability", "monitor mistral", "mistral alerts", "mistral tracing".
Competitive intelligence with positioning analysis, battlecards, and market monitoring. Use for competitor tracking, differentiation strategy, and win/loss analysis. Based on alirezarezvani/claude-skills.