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Found 776 Skills
Debug and troubleshoot production issues on Azure. Covers Container Apps diagnostics, log analysis with KQL, health checks, and common issue resolution for image pulls, cold starts, and health probes. USE FOR: debug production issues, troubleshoot container apps, analyze logs with KQL, fix image pull failures, resolve cold start issues, investigate health probe failures, check resource health, view application logs, find root cause of errors DO NOT USE FOR: deploying applications (use azure-deploy), creating new resources (use azure-prepare), setting up monitoring (use azure-observability), cost optimization (use azure-cost-optimization)
Instrument web applications to send telemetry data to Azure Application Insights for observability and monitoring. USE FOR: instrument app with app insights, add appinsights instrumentation, configure application insights, set up telemetry monitoring, enable app insights auto-instrumentation, add observability to azure web app, instrument webapp to send data to app insights, configure telemetry for app service. DO NOT USE FOR: non-Azure monitoring (use CloudWatch for AWS, Datadog for third-party), log analysis (use azure-kusto), cost monitoring (use azure-cost-optimization), security monitoring (use azure-security).
Comprehensive Azure compliance and security auditing capabilities including best practices assessment, Key Vault expiration monitoring, and resource configuration validation. USE FOR: compliance scan, security audit, azqr, Azure best practices, Key Vault expiration check, compliance assessment, resource review, configuration validation, expired certificates, expiring secrets, orphaned resources, policy compliance, security posture evaluation. DO NOT USE FOR: deploying resources (use azure-deploy), cost analysis alone (use azure-cost-optimization), active security hardening (use azure-security-hardening), general Azure Advisor queries (use azure-observability).
Use this skill to work with Microsoft Foundry (Azure AI Foundry): deploy AI models from catalog, build RAG applications with knowledge indexes, create and evaluate AI agents, manage RBAC permissions and role assignments, manage quotas and capacity, create Foundry resources. USE FOR: Microsoft Foundry, AI Foundry, deploy model, model catalog, RAG, knowledge index, create agent, evaluate agent, agent monitoring, create Foundry project, new Foundry project, set up Foundry, onboard to Foundry, provision Foundry infrastructure, create Foundry resource, create AI Services, multi-service resource, AIServices kind, register resource provider, enable Cognitive Services, setup AI Services account, create resource group for Foundry, RBAC, role assignment, managed identity, service principal, permissions, quota, capacity, TPM, deployment failure, QuotaExceeded. DO NOT USE FOR: Azure Functions (use azure-functions), App Service (use azure-create-app), generic Azure resource creation (use azure-create-app).
Troubleshoot and resolve issues with Azure Messaging SDKs for Event Hubs and Service Bus. Covers connection failures, authentication errors, message processing issues, and SDK configuration problems. USE FOR: event hub SDK error, service bus SDK issue, messaging connection failure, AMQP error, event processor host issue, message lock lost, send timeout, receiver disconnected, SDK troubleshooting, azure messaging SDK, event hub consumer, service bus queue issue, topic subscription error, enable logging event hub, service bus logging, eventhub python, servicebus java, eventhub javascript, servicebus dotnet, event hub checkpoint, event hub not receiving messages, service bus dead letter DO NOT USE FOR: creating Event Hub or Service Bus resources (use azure-prepare), monitoring metrics (use azure-observability), cost analysis (use azure-cost-optimization)
When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' or 'zero-click search.' This skill covers content optimization for AI answer engines, monitoring AI visibility, and getting cited as a source. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema-markup.
This skill should be used when the user wants to "set up tracing", "monitor my ADK agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring deployed ADK (Agent Development Kit) agents. Covers Cloud Trace, prompt-response logging, BigQuery Agent Analytics, third-party integrations (AgentOps, Phoenix, MLflow, etc.), and troubleshooting. Part of the Google ADK (Agent Development Kit) skills suite. Do NOT use for deployment setup (use google-agents-cli-deploy) or API code patterns (use google-agents-cli-adk-code).
Golang everyday observability — the always-on signals in production. Covers structured logging with slog, Prometheus metrics, OpenTelemetry distributed tracing, continuous profiling with pprof/Pyroscope, server-side RUM event tracking, alerting, and Grafana dashboards. Apply when instrumenting Go services for production monitoring, setting up metrics or alerting, adding OpenTelemetry tracing, correlating logs with traces, migrating legacy loggers (zap/logrus/zerolog) to slog, adding observability to new features, or implementing GDPR/CCPA-compliant tracking with Customer Data Platforms (CDP). Not for temporary deep-dive performance investigation (→ See golang-benchmark and golang-performance skills).
Set up monitoring, logging, and observability for applications and infrastructure. Use when implementing health checks, metrics collection, log aggregation, or alerting systems. Handles Prometheus, Grafana, ELK Stack, Datadog, and monitoring best practices.
Analyze application logs to identify errors, performance issues, and security anomalies. Use when debugging issues, monitoring system health, or investigating incidents. Handles various log formats including Apache, Nginx, application logs, and JSON logs.
Build automated AI workflows combining multiple models and services. Patterns: batch processing, scheduled tasks, event-driven pipelines, agent loops. Tools: inference.sh CLI, bash scripting, Python SDK, webhook integration. Use for: content automation, data processing, monitoring, scheduled generation. Triggers: ai automation, workflow automation, batch processing, ai pipeline, automated content, scheduled ai, ai cron, ai batch job, automated generation, ai workflow, content at scale, automation script, ai orchestration
Universal scraper for any OpenWeb Ninja API. Scrape jobs, business listings, products, reviews, news, social profiles, finance data, and more. Use for lead generation, market research, competitor analysis, content monitoring, price tracking, or any structured data extraction task.