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Found 54 Skills
Instrument a Python application with the Elastic Distribution of OpenTelemetry (EDOT) Python agent for automatic tracing, metrics, and logs. Use when adding observability to a Python service that has no existing APM agent.
Create MCP servers using the C# SDK and .NET project templates. Covers scaffolding, tool/prompt/resource implementation, and transport configuration for stdio and HTTP. USE FOR: creating new MCP server projects, scaffolding with dotnet new mcpserver, adding MCP tools/prompts/resources, choosing stdio vs HTTP transport, configuring MCP hosting in Program.cs, setting up ASP.NET Core MCP endpoints with MapMcp. DO NOT USE FOR: debugging or running existing servers (use mcp-csharp-debug), writing tests (use mcp-csharp-test), publishing or deploying (use mcp-csharp-publish), building MCP clients, non-.NET MCP servers.
A skill dedicated to Antom payment integration, helping merchants select the right product and integration approach based on business needs, and build production-grade code. Supported products: One-time Payments, Tokenized Payment (recurring auto-debit), Subscription Payment, Scan to Link. Supported integration modes: Payment Element, Checkout Page (fully hosted / embedded), API-only integration (APM / bank card).
Expert knowledge for Azure Spring Apps development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring ASA networking/security, Tanzu tools, observability/APM, CI/CD deployments, or blue‑green releases, and other Azure Spring Apps related development tasks. Not for Azure App Service (use azure-app-service), Azure Container Apps (use azure-container-apps), Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Functions (use azure-functions).
Query and analyze Datadog logs, metrics, APM traces, and monitors using the Datadog API. Use when debugging production issues, monitoring application performance, or investigating alerts.
Review existing Datadog dashboards for operational readiness. Audits alert threshold markers, threshold proximity to normal traffic, customer-facing section completeness, and zero-knowledge readability. Uses pup CLI to fetch dashboard definitions. Use when auditing dashboards before on-call handoff, after dashboard changes, or during operational reviews. Do not use for: (1) designing new dashboards from scratch, (2) monitor/alert rule design, (3) APM instrumentation or tracing setup, (4) log pipeline configuration.
Error tracking and monitoring integration. Sentry, Datadog RUM, Bugsnag. Source maps, breadcrumbs, release tracking, performance monitoring, and alerting configuration. USE WHEN: user mentions "Sentry", "error tracking", "Bugsnag", "Datadog RUM", "crash reporting", "source maps", "release tracking", "error monitoring" DO NOT USE FOR: application logging - use logging skills; APM/tracing - use `opentelemetry`; structured error responses - use `error-handling`
Apply statistical methods to financial data including descriptive statistics, covariance estimation, regression, hypothesis testing, and resampling. Use when the user asks about return distributions, correlation between assets, building a covariance matrix, running a CAPM regression, testing whether alpha is significant, checking if returns are normal, or estimating confidence intervals. Also trigger when users mention 'volatility', 'how correlated are these', 'fat tails', 'skewness', 'R-squared', 'beta of a fund', 'bootstrap a Sharpe ratio', 'shrinkage estimator', 'Ledoit-Wolf', or ask why their optimizer produces unstable weights.
Production server monitoring stack covering Prometheus, Node Exporter, Grafana, Alertmanager, Loki, and Promtail on bare-metal or VM Linux hosts. USE WHEN: - Setting up monitoring for a new production server or VPS - Configuring Prometheus scrape targets for application or system metrics - Creating Grafana dashboards and datasource provisioning - Writing Alertmanager routing rules with email/Slack notifications - Implementing the PLG stack (Promtail + Loki + Grafana) for log aggregation - Performing live system diagnostics with htop, iotop, nethogs, ss, vmstat, iostat - Setting up uptime monitoring with UptimeRobot or healthchecks.io DO NOT USE FOR: - Kubernetes-native observability (use the kubernetes skill instead) - Application-level APM (distributed tracing with Jaeger/Tempo — use observability skill) - Cloud-managed monitoring (CloudWatch, GCP Monitoring, Azure Monitor) - Windows Server monitoring
Grafana Cloud Database Observability — query-level performance insights for MySQL and PostgreSQL. Covers setup with Grafana Alloy, query samples, visual explain plans, RED metrics, pg_stat_statements and Performance Schema integration, and correlation with application traces. Use when monitoring database performance, diagnosing slow queries, setting up database observability for MySQL or PostgreSQL (self-managed, RDS, Aurora, Azure, Cloud SQL), or correlating DB metrics with APM data.
This skill should be used when the user asks to "investigate an issue", "debug a problem", "find out why something is slow", "check error rates", "analyze user behavior", "understand a production incident", "query telemetry data", "look at logs", "check traces", "examine spans", "analyze RUM data", "check frontend performance", "investigate backend latency", "find transaction data", "check payment metrics", "analyze user journeys", or wants to answer questions using observability data from logs, metrics, traces, RUM, or APM - this is the gateway skill for deciding where to look first.
New Relic integration. Manage Accounts. Use when the user wants to interact with New Relic data.