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Found 850 Skills
Senior DevOps Engineer with expertise in CI/CD automation, infrastructure as code, monitoring, and SRE practices. Proficient in cloud platforms, containerization, configuration management, and building scalable DevOps pipelines with focus on automation and operational excellence.
Telegram bot management and monitoring. TRIGGERS - telegram bot, claude-orchestrator, bot status, bot restart.
Expert-level Prometheus monitoring, metrics collection, PromQL queries, alerting, and production operations
DigitalOcean management services for monitoring, uptime checks, and resource organization with Projects. Use when setting up observability, alerts, and operational visibility on DigitalOcean.
Git-centric implementation workflow. Enforces clean checkout, creates a properly named branch, tracks progress in a WIP markdown file, and commits/pushes continuously so remote git logs serve as the primary monitoring channel. Use when starting any plan-based implementation task.
Comprehensive MLOps workflows for the complete ML lifecycle - experiment tracking, model registry, deployment patterns, monitoring, A/B testing, and production best practices with MLflow
Use when you need to choose the right visualization for your data and question, then create a narrated report that highlights insights and recommends actions. Invoke when analyzing data for patterns (trends, comparisons, distributions, relationships, compositions), building dashboards or reports, presenting metrics to stakeholders, monitoring KPIs, exploring datasets for insights, communicating findings from analysis, or when user mentions "visualize this", "what chart should I use", "create a dashboard", "analyze this data", "show trends", "compare these metrics", "report on", "what does this data tell us", or needs to turn data into actionable insights. Apply to business analytics (revenue, growth, churn, funnel, cohort, segmentation), product metrics (usage, adoption, retention, feature performance, A/B tests), marketing analytics (campaign ROI, attribution, funnel, customer acquisition), financial reporting (P&L, budget, forecast, variance), operational metrics (uptime, performance, capacity, SLA), sales analytics (pipeline, forecast, territory, quota attainment), HR metrics (headcount, turnover, engagement, DEI), and any scenario where data needs to become a clear, actionable story with the right visual form.
Autonomous multi-agent task orchestration with dependency analysis, parallel tmux/Codex execution, and self-healing heartbeat monitoring. Use for large projects with multiple issues/tasks that need coordinated parallel execution.
Framework for defining, monitoring, and enforcing guardrail metrics across experiments.
OpenTelemetry observability - use for distributed tracing, metrics, instrumentation, Sentry integration, and monitoring
Production MLOps and ML/LLM/agent security skill for deploying and operating ML systems in production (registry + CI/CD, serving, monitoring/drift, evaluation loops, incident response/runbooks, and governance), including GenAI security (prompt injection, jailbreaks, RAG security, privacy, and supply chain).
Build and maintain digital twins - virtual representations of physical systems that synchronize with real-world counterparts for monitoring, prediction, and optimization. Use when "digital twin, virtual model, real-time synchronization, physical-virtual coupling, predictive maintenance, asset modeling, system replica, live simulation, " mentioned.