azure-diagnostics
Skill11 starsChanged 9 months agoMITView on GitHub
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)
7 other projects use a version of this, 6 of them edited.
Adopted by
Most recently taken up by
- microsoft/GitHub-Copilot-for-Azureedited, first seen Oct 13, 2026
- microsoft/skillsedited, first seen Oct 13, 2026
- microsoft/azure-skillsedited, first seen Oct 13, 2026
- microsoft/agent-skillsedited, first seen Oct 8, 2026
- idexal/idexal-skillsedited, first seen Aug 26, 2026
- jorgeasaurus/agent-skillsedited, first seen May 11, 2026
Other versions7 projects use a version of this.
Word for word · 0
None found.
Edited · 6
- microsoft/agent-skills★ 3.2k32% same
- microsoft/skills★ 3.2k32% same
- microsoft/azure-skills★ 1.6k32% same
- microsoft/GitHub-Copilot-for-Azure★ 26232% same
- jorgeasaurus/agent-skills★ 1446% same
- idexal/idexal-skills★ 241% same
Wrote their own version · 1
- sparkedelectrical/claude-skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository73 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .agents/skills/vercel-composition-patterns/AGENTS.mdAGENTS.md
- .agents/skills/vercel-react-best-practices/AGENTS.mdAGENTS.md
- .agents/skills/vercel-react-native-skills/AGENTS.mdAGENTS.md
- appinsights-instrumentationSkill
- azure-aigatewaySkill
- azure-aiSkill
- azure-complianceSkill
- azure-cost-optimizationSkill
- azure-deploySkill
- azure-diagnosticsSkill
- azure-kustoSkill
- azure-networkingSkill
- azure-observabilitySkill
- azure-postgresSkill
- azure-prepareSkill
- azure-resource-visualizerSkill
- azure-role-selectorSkill
- azure-storageSkill
- azure-validateSkill
- entra-app-registrationSkill
- file-test-bugSkill
- markdown-token-optimizerSkill
- microsoft-foundrySkill
- senseiSkill
- skill-authoringSkill
- vercel-composition-patternsSkill
- vercel-react-best-practicesSkill
- vercel-react-native-skillsSkill
- web-design-guidelinesSkill
- appinsights-instrumentationSkill
- azure-aigatewaySkill
- azure-aiSkill
- azure-complianceSkill
- azure-cost-optimizationSkill
- azure-deploySkill
- azure-diagnosticsSkill
- azure-kustoSkill
- azure-networkingSkill
- azure-observabilitySkill
- azure-postgresSkill
- azure-prepareSkill
- azure-resource-visualizerSkill
- azure-role-selectorSkill
- azure-storageSkill
- azure-validateSkill
- entra-app-registrationSkill
- file-test-bugSkill
- markdown-token-optimizerSkill
- microsoft-foundrySkill
- senseiSkill
- skill-authoringSkill
- appinsights-instrumentationSkill
- azure-aigatewaySkill
- azure-aiSkill
- azure-complianceSkill
- azure-cost-optimizationSkill
- azure-deploySkill
- azure-kustoSkill
- azure-networkingSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
4 rules. 4 are common, 0 are distinctive, and 0 are very specific to this project.
4
Common
Most of the 6 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Common: line 27
Start with systematic diagnosis flow
- Common: line 28
Use AppLens (MCP) for AI-powered diagnostics when available
- Common: line 29
Check resource health before deep-diving into logs
- Common: line 31
Document findings and attempted remediation steps
“Common” is measured: kept by at least 6 in 10 of the 6 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Azure Diagnostics
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
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/ |
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 --followAppLens (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 recommendationsAzure 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 20References
- KQL Query Library
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

