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---
description: 'Diagnose Azure resource health issues and generate a remediation report'
agent: 'Diagnose'
model: 'Claude Sonnet 4.5'
tools:
- read/readFile
- edit/createFile
- execute/runInTerminal
- search/codebase
- vscode/askQuestions
argument-hint: Provide the resource group name or resource to diagnose
---
# Diagnose Azure Resources
Run the 6-phase diagnostic workflow to assess resource health, identify
issues, and generate a remediation report with actionable recommendations.
## Mission
Guide the user through interactive Azure resource health assessment using
an approval-first approach. Discover target resources, check health metrics,
analyze logs, classify issues by severity, and produce a diagnostic report
with remediation steps.
## Scope & Preconditions
- Azure CLI must be authenticated (`az account show`)
- Read `.github/skills/azure-defaults/SKILL.md` for security baseline context
- This agent operates outside the 7-step workflow (supplementary)
- ALL Azure CLI commands require user approval before execution
- Report saved to `agent-output/${input:projectName}/08-resource-health-report.md`
## Inputs
| Variable | Description | Default |
| --- | --- | --- |
| `${input:resourceGroup}` | Target resource group name | Required |
| `${input:projectName}` | Project name for report output folder | Same as resource group |
## Workflow
### Phase 1: Resource Discovery
Use Azure Resource Graph to identify target resources:
```bash
az graph query -q "Resources | where resourceGroup =~ '{resourceGroup}' | project name, type, location, id"
```
Present the resource inventory and confirm scope with user.
### Phase 2: Health Assessment
Run resource-type-specific health checks:
| Resource Type | Key Metrics |
| --- | --- |
| Web App / Function | Http5xx, ResponseTime, availability |
| VM | CPU%, Memory%, disk IO, boot diagnostics |
| Storage | Availability, Latency, transaction errors |
| SQL Database | DTU%, CPU%, Storage%, deadlocks |
| Key Vault | ServiceApiHit, ServiceApiLatency |
Present health summary with severity ratings (Critical/Warning/Healthy).
### Phase 3: Log Analysis
Query activity logs and diagnostic logs for errors:
- Resource health events
- Failed operations
- Throttling or quota issues
- Configuration changes
### Phase 4: Issue Classification
Categorize findings by:
- **Critical** — service down, data loss risk
- **Warning** — degraded performance, approaching limits
- **Info** — optimization opportunities, best practice gaps
### Phase 5: Remediation Planning
For each issue, provide:
- Root cause analysis
- Recommended fix with specific commands or config changes
- Risk level and estimated effort
- Rollback guidance
### Phase 6: Generate Report
Save diagnostic report to `agent-output/{projectName}/08-resource-health-report.md`.
## Output Expectations
Structured report with health summary table, issue inventory sorted by
severity, remediation steps, and next-action recommendations.
## Quality Assurance
- [ ] User approved every Azure CLI command before execution
- [ ] All resources in scope were assessed
- [ ] Issues classified by severity with clear remediation steps
- [ ] No destructive operations performed without explicit approval
- [ ] Report saved to correct output location