Azure Diagnostics
SkillCloud & infraazure-diagnostics gives your AI ready-made skills for working with Microsoft Azure cloud services. Once added, your AI can help diagnose issues and handle common Azure scenarios instead of you working out each step yourself. It comes from Microsoft's official azure-skills collection.
Available today. Use it from your connected AI after setup.
No other account needed.
After adding it, ask your AI to help with an Azure task or to look into a problem you are seeing in your Azure environment.
Then ask your AI: use the Azure Diagnostics skill
What your AI can do with it
- Work with Microsoft Azure cloud services
- Diagnose problems in your Azure environment
- Use ready-made skills for common Azure scenarios
- Handle Azure tasks without building each step from scratch
What this skill tells your AI
The instructions your AI receives, as published by microsoft/azure-skills in skills/azure-diagnostics/SKILL.md and read by ahel’s review.
AUTHORITATIVE GUIDANCE — MANDATORY COMPLIANCE
This document is the official source for debugging and troubleshooting Azure production issues. Follow these instructions to diagnose and resolve common Azure service problems systematically.
Triggers
Activate this skill when user wants to:
- Debug or troubleshoot production issues
- Diagnose errors in Azure services
- Analyze application logs or metrics
- Fix image pull, cold start, or health probe issues
- Investigate why Azure resources are failing
- Find root cause of application errors
- Troubleshoot Azure Function Apps (invocation failures, timeouts, binding errors)
- Find the App Insights or Log Analytics workspace linked to a Function App
Rules
- Start with systematic diagnosis flow
- Use AppLens (MCP) for AI-powered diagnostics when available
- Check resource health before deep-diving into logs
- Select appropriate troubleshooting guide based on service type
- Document findings and attempted remediation steps
Quick Diagnosis Flow
- Identify symptoms - What's failing?
- Check resource health - Is Azure healthy?
- Review logs - What do logs show?
- Analyze metrics - Performance patterns?
- Investigate recent changes - What changed?
Troubleshooting Guides by Service
| Service | Common Issues | Reference |
|---|---|---|
| Container Apps | Image pull failures, cold starts, health probes, port mismatches | container-apps/ |
| Function Apps | App details, invocation failures, timeouts, binding errors, cold starts, missing app settings | functions/ |
Quick Reference
Common Diagnostic Commands
# Check resource health
az resource show --ids RESOURCE_ID
# View activity log
az monitor activity-log list -g RG --max-events 20
# Container Apps logs
az containerapp logs show --name APP -g RG --follow
# Function App logs (query App Insights traces)
az monitor app-insights query --apps APP-INSIGHTS -g RG \
--analytics-query "traces | where timestamp > ago(1h) | order by timestamp desc | take 50"
AppLens (MCP Tools)
For AI-powered diagnostics, use:
mcp_azure_mcp_applens
intent: "diagnose issues with <resource-name>"
command: "diagnose"
parameters:
resourceId: "<resource-id>"
Provides:
- Automated issue detection
- Root cause analysis
- Remediation recommendations
Azure Monitor (MCP Tools)
For querying logs and metrics:
mcp_azure_mcp_monitor
intent: "query logs for <resource-name>"
command: "logs_query"
parameters:
workspaceId: "<workspace-id>"
query: "<KQL-query>"
See kql-queries.md for common diagnostic queries.
Check Azure Resource Health
Using MCP
mcp_azure_mcp_resourcehealth
intent: "check health status of <resource-name>"
command: "get"
parameters:
resourceId: "<resource-id>"
Using CLI
# Check specific resource health
az resource show --ids RESOURCE_ID
# Check recent activity
az monitor activity-log list -g RG --max-events 20
References
Signals
- GitHub stars
- 1k
- Forks
- 245
- Last commit
- Sep 2026
- Installs
- 578k installs
Advanced
- Catalog kind
- skill
- Gateway key
azure-diagnostics- Source
- github.com/microsoft/azure-skills