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Found 388 Skills
Configure New Relic observability platform for infrastructure and application monitoring. Set up APM agents, create dashboards, configure alerts, and implement distributed tracing. Use when implementing full-stack observability with New Relic One.
Implement Istio and Linkerd service meshes. Configure mTLS, traffic management, and observability. Use when managing microservices communication.
Configures .NET CI/CD pipelines (GitHub Actions with setup-dotnet, NuGet cache, reusable workflows; Azure DevOps with DotNetCoreCLI, templates, multi-stage), containerization (multi-stage Dockerfiles, Compose, rootless), packaging (NuGet authoring, source generators, MSIX signing), release management (NBGV, SemVer, changelogs, GitHub Releases), and observability (OpenTelemetry, health checks, structured logging, PII). Spans 18 topic areas. Do not use for application-layer API or UI implementation patterns.
This skill should be used when the user asks to "review code", "review my changes", "check effect patterns", "run effect review", "effect review", "review for effect best practices", or wants a comprehensive code review against Effect-TS conventions, branded types, observability, error handling, test coverage, and UI quality.
Use when the user needs CI/CD pipelines, Docker configuration, Kubernetes deployment, infrastructure-as-code, monitoring, or zero-downtime deployment strategies. Triggers: user says "devops", "docker", "kubernetes", "CI/CD", "infrastructure", "monitoring", "deploy to production", "container", "terraform", "observability".
Go implementation guide for PMA-managed service and CLI projects. Covers project layout (cmd/internal), strict linting with golangci-lint v2, database access (sqlc + pgx or GORM), HTTP patterns (stdlib + Chi or Gin), layered config with koanf, structured logging with slog, OpenTelemetry observability, and CI quality gates.
Audit design documents for missing decisions, compatibility risks, rollout gaps, and observability omissions. Use whenever the user asks to review a design doc, architecture proposal, implementation-facing design, plan, or design-adjacent markdown file for completeness, migration strategy, rollback, data handling, or suggested additions without directly editing the document. Also trigger on short requests such as `review <file>.md` or `audit <file>.md` when the target looks like a design, plan, architecture, proposal, or decision document.
Activate when the user asks Claude to talk like a caveman, use caveman mode, say "less tokens please", or invoke "/elastic-caveman". Also activate when the user wants faster, terser responses while still working with Elasticsearch, Kibana, Elastic Security, Elastic Observability, or any part of the Elastic stack. In caveman mode all Elasticsearch-specific technical terms, API names, field names, index patterns, query DSL structures, ESQL syntax, and error messages are preserved verbatim — only filler words and pleasantries are removed. Stop caveman mode when the user says "stop caveman" or "normal mode".
Write implementation-ready project specifications from ideas, plans, architecture discussions, repo research, or high-level requirements. Use when Codex needs to create, refine, audit, or structure a concrete spec with explicit contracts, boundaries, data models, lifecycle behavior, failure handling, observability, and validation criteria.
Implement structured logging with JSON formats, log levels (DEBUG, INFO, WARN, ERROR), contextual logging, PII handling, and centralized logging. Use for logging, observability, log levels, structured logs, or debugging.
Prometheus monitoring and alerting for cloud-native observability. USE WHEN: Writing PromQL queries, configuring Prometheus scrape targets, creating alerting rules, setting up recording rules, instrumenting applications with Prometheus metrics, configuring service discovery. DO NOT USE: For building dashboards (use /grafana), for log analysis (use /logging-observability), for general observability architecture (use senior-software-engineer with infrastructure focus). TRIGGERS: metrics, prometheus, promql, counter, gauge, histogram, summary, alert, alertmanager, alerting rule, recording rule, scrape, target, label, service discovery, relabeling, exporter, instrumentation, slo, error budget.
Use when working with AWS Strands Agents SDK or Amazon Bedrock AgentCore platform for building AI agents. Provides architecture guidance, implementation patterns, deployment strategies, observability, quality evaluations, multi-agent orchestration, and MCP server integration.