Loading...
Loading...
Found 667 Skills
This skill should be used when the user asks to "fetch Sentry issues", "check Sentry errors", "triage Sentry", "categorize Sentry issues", "resolve Sentry issue", "mute Sentry issue", "unresolve Sentry issue", "sentry-cli", or mentions Sentry API, Sentry project issues, error monitoring, issue triage, Sentry stack traces, or browser extension errors in Sentry.
Expert-level precision agriculture, farm management systems, crop monitoring, and agtech
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.
PostgreSQL monitoring - metrics, alerting, observability
Implement consistent error handling with custom error classes, error boundaries, and structured error responses. Covers logging, monitoring, and user-friendly messages.
Operate the Prelude Security platform CLI for continuous security testing (Detect) and endpoint posture monitoring (SCM). Manages endpoints, schedules tests, evaluates security control policies, integrates with EDR/XDR partners, and generates reports. Use when working with the `prelude` CLI or managing security infrastructure.
Implement health check endpoints for load balancers, Kubernetes, and monitoring. Covers liveness, readiness, and dependency checks.
Manage concurrent background workers with scheduling, dependencies, health monitoring, and automatic disabling of failing workers.
Enables autonomous context management for codebases through claude.md files. Use when creating, maintaining, or synchronizing AI agent context. Provides tools and workflows for monitoring context health, detecting staleness, and updating intelligently. Helps Claude work proactively as a context manager.
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.
Use when establishing tests, monitoring, and incident response for analytics models.
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"