Create a Datadog demo project — scaffold infrastructure, build domain-specific microservices, and generate demo scenarios. Use when the user asks to create a demo, scaffold a project, set up a Datadog environment, or build a sample application.
Verify Datadog telemetry is flowing correctly using MCP tools
Build, deploy, smoke test, and validate a demo project before presenting it. Use after scaffolding or modifying services to ensure everything works end-to-end.
Look up current Datadog documentation via the official LLM-optimized index at docs.datadoghq.com/llms.txt. Use this skill whenever you need accurate, up-to-date Datadog configuration steps, feature details, API references, integration setup, or troubleshooting guidance — even if you think you already know the answer. Datadog docs change frequently and your training data is likely stale. Trigger on any Datadog-related question: agent install, log pipelines, APM setup, DBM, monitors, dashboards, SLOs, integrations, RBAC, cloud cost, synthetics, LLM observability, etc. Also trigger when another dd- prefixed skill needs to reference official documentation.
Generate Terraform for Datadog dashboards tailored to a project's services and active features, enriched with real telemetry data from the Datadog MCP server.
Generate Terraform for Datadog monitors tailored to a project's services and active features, using real telemetry baselines when available.
Configure the Locust traffic generator with domain-specific scenarios that exercise all services, demo golden paths, and trigger failure modes for Datadog visibility.
Generate Terraform for Datadog SLOs tailored to the project's services and active features, either wrapping existing monitors (monitor-based) or querying APM metrics directly (metric-based).