[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AD8JBTNFAMNEEXQG022CBF":3,"skill-same:01M6AD8JBTNFAMNEEXQG022CBF":61},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":32,"linkOnly":33,"markdownContent":34,"markdownBody":35,"frontMatter":36,"refName":37,"commitSha":38,"skillDirectory":39,"forksCount":40,"repositoryHtmlUrl":41,"repositoryHomepageUrl":42,"ownerHtmlUrl":43,"ownerBlogUrl":44,"ownerDescription":45,"updatedAt":46,"install":47,"resources":60},"01M6AD8JBTNFAMNEEXQG022CBF","azure-resource-health-diagnose",null,"Analyze Azure resource health, diagnose issues from logs and telemetry, and create a remediation plan for identified problems.","github\u002Fawesome-copilot","github","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F9919?v=4","01M6AC83DS133TPXFSP1DHNCC6","GitHub","01M6AD3PBDYPK7NVFJNJ66Y8RS",41046,"MIT","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fazure-resource-health-diagnose\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31],"diagnose","azure","azure resource health diagnose","health","telemetry","create","issues","logs","remediation","plan","analyze","remediation plan","for","2026-11-10 10:12:30",false,"---\nname: azure-resource-health-diagnose\ndescription: 'Analyze Azure resource health, diagnose issues from logs and telemetry, and create a remediation plan for identified problems.'\n---\n\n# Azure Resource Health & Issue Diagnosis\n\nThis workflow analyzes a specific Azure resource to assess its health status, diagnose potential issues using logs and telemetry data, and develop a comprehensive remediation plan for any problems discovered.\n\n## Prerequisites\n- Azure MCP server configured and authenticated\n- Target Azure resource identified (name and optionally resource group\u002Fsubscription)\n- Resource must be deployed and running to generate logs\u002Ftelemetry\n- Prefer Azure MCP tools (`azmcp-*`) over direct Azure CLI when available\n\n## Workflow Steps\n\n### Step 1: Get Azure Best Practices\n**Action**: Retrieve diagnostic and troubleshooting best practices\n**Tools**: Azure MCP best practices tool\n**Process**:\n1. **Load Best Practices**:\n   - Execute Azure best practices tool to get diagnostic guidelines\n   - Focus on health monitoring, log analysis, and issue resolution patterns\n   - Use these practices to inform diagnostic approach and remediation recommendations\n\n### Step 2: Resource Discovery & Identification\n**Action**: Locate and identify the target Azure resource\n**Tools**: Azure MCP tools + Azure CLI fallback\n**Process**:\n1. **Resource Lookup**:\n   - If only resource name provided: Search across subscriptions using `azmcp-subscription-list`\n   - Use `az resource list --name \u003Cresource-name>` to find matching resources\n   - If multiple matches found, prompt user to specify subscription\u002Fresource group\n   - Gather detailed resource information:\n     - Resource type and current status\n     - Location, tags, and configuration\n     - Associated services and dependencies\n\n2. **Resource Type Detection**:\n   - Identify resource type to determine appropriate diagnostic approach:\n     - **Web Apps\u002FFunction Apps**: Application logs, performance metrics, dependency tracking\n     - **Virtual Machines**: System logs, performance counters, boot diagnostics\n     - **Cosmos DB**: Request metrics, throttling, partition statistics\n     - **Storage Accounts**: Access logs, performance metrics, availability\n     - **SQL Database**: Query performance, connection logs, resource utilization\n     - **Application Insights**: Application telemetry, exceptions, dependencies\n     - **Key Vault**: Access logs, certificate status, secret usage\n     - **Service Bus**: Message metrics, dead letter queues, throughput\n\n### Step 3: Health Status Assessment\n**Action**: Evaluate current resource health and availability\n**Tools**: Azure MCP monitoring tools + Azure CLI\n**Process**:\n1. **Basic Health Check**:\n   - Check resource provisioning state and operational status\n   - Verify service availability and responsiveness\n   - Review recent deployment or configuration changes\n   - Assess current resource utilization (CPU, memory, storage, etc.)\n\n2. **Service-Specific Health Indicators**:\n   - **Web Apps**: HTTP response codes, response times, uptime\n   - **Databases**: Connection success rate, query performance, deadlocks\n   - **Storage**: Availability percentage, request success rate, latency\n   - **VMs**: Boot diagnostics, guest OS metrics, network connectivity\n   - **Functions**: Execution success rate, duration, error frequency\n\n### Step 4: Log & Telemetry Analysis\n**Action**: Analyze logs and telemetry to identify issues and patterns\n**Tools**: Azure MCP monitoring tools for Log Analytics queries\n**Process**:\n1. **Find Monitoring Sources**:\n   - Use `azmcp-monitor-workspace-list` to identify Log Analytics workspaces\n   - Locate Application Insights instances associated with the resource\n   - Identify relevant log tables using `azmcp-monitor-table-list`\n\n2. **Execute Diagnostic Queries**:\n   Use `azmcp-monitor-log-query` with targeted KQL queries based on resource type:\n\n   **General Error Analysis**:\n   ```kql\n   \u002F\u002F Recent errors and exceptions\n   union isfuzzy=true \n       AzureDiagnostics,\n       AppServiceHTTPLogs,\n       AppServiceAppLogs,\n       AzureActivity\n   | where TimeGenerated > ago(24h)\n   | where Level == \"Error\" or ResultType != \"Success\"\n   | summarize ErrorCount=count() by Resource, ResultType, bin(TimeGenerated, 1h)\n   | order by TimeGenerated desc\n   ```\n\n   **Performance Analysis**:\n   ```kql\n   \u002F\u002F Performance degradation patterns\n   Perf\n   | where TimeGenerated > ago(7d)\n   | where ObjectName == \"Processor\" and CounterName == \"% Processor Time\"\n   | summarize avg(CounterValue) by Computer, bin(TimeGenerated, 1h)\n   | where avg_CounterValue > 80\n   ```\n\n   **Application-Specific Queries**:\n   ```kql\n   \u002F\u002F Application Insights - Failed requests\n   requests\n   | where timestamp > ago(24h)\n   | where success == false\n   | summarize FailureCount=count() by resultCode, bin(timestamp, 1h)\n   | order by timestamp desc\n   \n   \u002F\u002F Database - Connection failures\n   AzureDiagnostics\n   | where ResourceProvider == \"MICROSOFT.SQL\"\n   | where Category == \"SQLSecurityAuditEvents\"\n   | where action_name_s == \"CONNECTION_FAILED\"\n   | summarize ConnectionFailures=count() by bin(TimeGenerated, 1h)\n   ```\n\n3. **Pattern Recognition**:\n   - Identify recurring error patterns or anomalies\n   - Correlate errors with deployment times or configuration changes\n   - Analyze performance trends and degradation patterns\n   - Look for dependency failures or external service issues\n\n### Step 5: Issue Classification & Root Cause Analysis\n**Action**: Categorize identified issues and determine root causes\n**Process**:\n1. **Issue Classification**:\n   - **Critical**: Service unavailable, data loss, security breaches\n   - **High**: Performance degradation, intermittent failures, high error rates\n   - **Medium**: Warnings, suboptimal configuration, minor performance issues\n   - **Low**: Informational alerts, optimization opportunities\n\n2. **Root Cause Analysis**:\n   - **Configuration Issues**: Incorrect settings, missing dependencies\n   - **Resource Constraints**: CPU\u002Fmemory\u002Fdisk limitations, throttling\n   - **Network Issues**: Connectivity problems, DNS resolution, firewall rules\n   - **Application Issues**: Code bugs, memory leaks, inefficient queries\n   - **External Dependencies**: Third-party service failures, API limits\n   - **Security Issues**: Authentication failures, certificate expiration\n\n3. **Impact Assessment**:\n   - Determine business impact and affected users\u002Fsystems\n   - Evaluate data integrity and security implications\n   - Assess recovery time objectives and priorities\n\n### Step 6: Generate Remediation Plan\n**Action**: Create a comprehensive plan to address identified issues\n**Process**:\n1. **Immediate Actions** (Critical issues):\n   - Emergency fixes to restore service availability\n   - Temporary workarounds to mitigate impact\n   - Escalation procedures for complex issues\n\n2. **Short-term Fixes** (High\u002FMedium issues):\n   - Configuration adjustments and resource scaling\n   - Application updates and patches\n   - Monitoring and alerting improvements\n\n3. **Long-term Improvements** (All issues):\n   - Architectural changes for better resilience\n   - Preventive measures and monitoring enhancements\n   - Documentation and process improvements\n\n4. **Implementation Steps**:\n   - Prioritized action items with specific Azure CLI commands\n   - Testing and validation procedures\n   - Rollback plans for each change\n   - Monitoring to verify issue resolution\n\n### Step 7: User Confirmation & Report Generation\n**Action**: Present findings and get approval for remediation actions\n**Process**:\n1. **Display Health Assessment Summary**:\n   ```\n   ? Azure Resource Health Assessment\n   \n   ? Resource Overview:\n   • Resource: [Name] ([Type])\n   • Status: [Healthy\u002FWarning\u002FCritical]\n   • Location: [Region]\n   • Last Analyzed: [Timestamp]\n   \n   ? Issues Identified:\n   • Critical: X issues requiring immediate attention\n   • High: Y issues affecting performance\u002Freliability  \n   • Medium: Z issues for optimization\n   • Low: N informational items\n   \n   ? Top Issues:\n   1. [Issue Type]: [Description] - Impact: [High\u002FMedium\u002FLow]\n   2. [Issue Type]: [Description] - Impact: [High\u002FMedium\u002FLow]\n   3. [Issue Type]: [Description] - Impact: [High\u002FMedium\u002FLow]\n   \n   ?️ Remediation Plan:\n   • Immediate Actions: X items\n   • Short-term Fixes: Y items  \n   • Long-term Improvements: Z items\n   • Estimated Resolution Time: [Timeline]\n   \n   ❓ Proceed with detailed remediation plan? (y\u002Fn)\n   ```\n\n2. **Generate Detailed Report**:\n   ```markdown\n   # Azure Resource Health Report: [Resource Name]\n   \n   **Generated**: [Timestamp]  \n   **Resource**: [Full Resource ID]  \n   **Overall Health**: [Status with color indicator]\n   \n   ## ? Executive Summary\n   [Brief overview of health status and key findings]\n   \n   ## ? Health Metrics\n   - **Availability**: X% over last 24h\n   - **Performance**: [Average response time\u002Fthroughput]\n   - **Error Rate**: X% over last 24h\n   - **Resource Utilization**: [CPU\u002FMemory\u002FStorage percentages]\n   \n   ## ? Issues Identified\n   \n   ### Critical Issues\n   - **[Issue 1]**: [Description]\n     - **Root Cause**: [Analysis]\n     - **Impact**: [Business impact]\n     - **Immediate Action**: [Required steps]\n   \n   ### High Priority Issues  \n   - **[Issue 2]**: [Description]\n     - **Root Cause**: [Analysis]\n     - **Impact**: [Performance\u002Freliability impact]\n     - **Recommended Fix**: [Solution steps]\n   \n   ## ?️ Remediation Plan\n   \n   ### Phase 1: Immediate Actions (0-2 hours)\n   ```bash\n   # Critical fixes to restore service\n   [Azure CLI commands with explanations]\n   ```\n   \n   ### Phase 2: Short-term Fixes (2-24 hours)\n   ```bash\n   # Performance and reliability improvements\n   [Azure CLI commands with explanations]\n   ```\n   \n   ### Phase 3: Long-term Improvements (1-4 weeks)\n   ```bash\n   # Architectural and preventive measures\n   [Azure CLI commands and configuration changes]\n   ```\n   \n   ## ? Monitoring Recommendations\n   - **Alerts to Configure**: [List of recommended alerts]\n   - **Dashboards to Create**: [Monitoring dashboard suggestions]\n   - **Regular Health Checks**: [Recommended frequency and scope]\n   \n   ## ✅ Validation Steps\n   - [ ] Verify issue resolution through logs\n   - [ ] Confirm performance improvements\n   - [ ] Test application functionality\n   - [ ] Update monitoring and alerting\n   - [ ] Document lessons learned\n   \n   ## ? Prevention Measures\n   - [Recommendations to prevent similar issues]\n   - [Process improvements]\n   - [Monitoring enhancements]\n   ```\n\n## Error Handling\n- **Resource Not Found**: Provide guidance on resource name\u002Flocation specification\n- **Authentication Issues**: Guide user through Azure authentication setup\n- **Insufficient Permissions**: List required RBAC roles for resource access\n- **No Logs Available**: Suggest enabling diagnostic settings and waiting for data\n- **Query Timeouts**: Break down analysis into smaller time windows\n- **Service-Specific Issues**: Provide generic health assessment with limitations noted\n\n## Success Criteria\n- ✅ Resource health status accurately assessed\n- ✅ All significant issues identified and categorized\n- ✅ Root cause analysis completed for major problems\n- ✅ Actionable remediation plan with specific steps provided\n- ✅ Monitoring and prevention recommendations included\n- ✅ Clear prioritization of issues by business impact\n- ✅ Implementation steps include validation and rollback procedures\n","# Azure Resource Health & Issue Diagnosis\n\nThis workflow analyzes a specific Azure resource to assess its health status, diagnose potential issues using logs and telemetry data, and develop a comprehensive remediation plan for any problems discovered.\n\n## Prerequisites\n- Azure MCP server configured and authenticated\n- Target Azure resource identified (name and optionally resource group\u002Fsubscription)\n- Resource must be deployed and running to generate logs\u002Ftelemetry\n- Prefer Azure MCP tools (`azmcp-*`) over direct Azure CLI when available\n\n## Workflow Steps\n\n### Step 1: Get Azure Best Practices\n**Action**: Retrieve diagnostic and troubleshooting best practices\n**Tools**: Azure MCP best practices tool\n**Process**:\n1. **Load Best Practices**:\n   - Execute Azure best practices tool to get diagnostic guidelines\n   - Focus on health monitoring, log analysis, and issue resolution patterns\n   - Use these practices to inform diagnostic approach and remediation recommendations\n\n### Step 2: Resource Discovery & Identification\n**Action**: Locate and identify the target Azure resource\n**Tools**: Azure MCP tools + Azure CLI fallback\n**Process**:\n1. **Resource Lookup**:\n   - If only resource name provided: Search across subscriptions using `azmcp-subscription-list`\n   - Use `az resource list --name \u003Cresource-name>` to find matching resources\n   - If multiple matches found, prompt user to specify subscription\u002Fresource group\n   - Gather detailed resource information:\n     - Resource type and current status\n     - Location, tags, and configuration\n     - Associated services and dependencies\n\n2. **Resource Type Detection**:\n   - Identify resource type to determine appropriate diagnostic approach:\n     - **Web Apps\u002FFunction Apps**: Application logs, performance metrics, dependency tracking\n     - **Virtual Machines**: System logs, performance counters, boot diagnostics\n     - **Cosmos DB**: Request metrics, throttling, partition statistics\n     - **Storage Accounts**: Access logs, performance metrics, availability\n     - **SQL Database**: Query performance, connection logs, resource utilization\n     - **Application Insights**: Application telemetry, exceptions, dependencies\n     - **Key Vault**: Access logs, certificate status, secret usage\n     - **Service Bus**: Message metrics, dead letter queues, throughput\n\n### Step 3: Health Status Assessment\n**Action**: Evaluate current resource health and availability\n**Tools**: Azure MCP monitoring tools + Azure CLI\n**Process**:\n1. **Basic Health Check**:\n   - Check resource provisioning state and operational status\n   - Verify service availability and responsiveness\n   - Review recent deployment or configuration changes\n   - Assess current resource utilization (CPU, memory, storage, etc.)\n\n2. **Service-Specific Health Indicators**:\n   - **Web Apps**: HTTP response codes, response times, uptime\n   - **Databases**: Connection success rate, query performance, deadlocks\n   - **Storage**: Availability percentage, request success rate, latency\n   - **VMs**: Boot diagnostics, guest OS metrics, network connectivity\n   - **Functions**: Execution success rate, duration, error frequency\n\n### Step 4: Log & Telemetry Analysis\n**Action**: Analyze logs and telemetry to identify issues and patterns\n**Tools**: Azure MCP monitoring tools for Log Analytics queries\n**Process**:\n1. **Find Monitoring Sources**:\n   - Use `azmcp-monitor-workspace-list` to identify Log Analytics workspaces\n   - Locate Application Insights instances associated with the resource\n   - Identify relevant log tables using `azmcp-monitor-table-list`\n\n2. **Execute Diagnostic Queries**:\n   Use `azmcp-monitor-log-query` with targeted KQL queries based on resource type:\n\n   **General Error Analysis**:\n   ```kql\n   \u002F\u002F Recent errors and exceptions\n   union isfuzzy=true \n       AzureDiagnostics,\n       AppServiceHTTPLogs,\n       AppServiceAppLogs,\n       AzureActivity\n   | where TimeGenerated > ago(24h)\n   | where Level == \"Error\" or ResultType != \"Success\"\n   | summarize ErrorCount=count() by Resource, ResultType, bin(TimeGenerated, 1h)\n   | order by TimeGenerated desc\n   ```\n\n   **Performance Analysis**:\n   ```kql\n   \u002F\u002F Performance degradation patterns\n   Perf\n   | where TimeGenerated > ago(7d)\n   | where ObjectName == \"Processor\" and CounterName == \"% Processor Time\"\n   | summarize avg(CounterValue) by Computer, bin(TimeGenerated, 1h)\n   | where avg_CounterValue > 80\n   ```\n\n   **Application-Specific Queries**:\n   ```kql\n   \u002F\u002F Application Insights - Failed requests\n   requests\n   | where timestamp > ago(24h)\n   | where success == false\n   | summarize FailureCount=count() by resultCode, bin(timestamp, 1h)\n   | order by timestamp desc\n   \n   \u002F\u002F Database - Connection failures\n   AzureDiagnostics\n   | where ResourceProvider == \"MICROSOFT.SQL\"\n   | where Category == \"SQLSecurityAuditEvents\"\n   | where action_name_s == \"CONNECTION_FAILED\"\n   | summarize ConnectionFailures=count() by bin(TimeGenerated, 1h)\n   ```\n\n3. **Pattern Recognition**:\n   - Identify recurring error patterns or anomalies\n   - Correlate errors with deployment times or configuration changes\n   - Analyze performance trends and degradation patterns\n   - Look for dependency failures or external service issues\n\n### Step 5: Issue Classification & Root Cause Analysis\n**Action**: Categorize identified issues and determine root causes\n**Process**:\n1. **Issue Classification**:\n   - **Critical**: Service unavailable, data loss, security breaches\n   - **High**: Performance degradation, intermittent failures, high error rates\n   - **Medium**: Warnings, suboptimal configuration, minor performance issues\n   - **Low**: Informational alerts, optimization opportunities\n\n2. **Root Cause Analysis**:\n   - **Configuration Issues**: Incorrect settings, missing dependencies\n   - **Resource Constraints**: CPU\u002Fmemory\u002Fdisk limitations, throttling\n   - **Network Issues**: Connectivity problems, DNS resolution, firewall rules\n   - **Application Issues**: Code bugs, memory leaks, inefficient queries\n   - **External Dependencies**: Third-party service failures, API limits\n   - **Security Issues**: Authentication failures, certificate expiration\n\n3. **Impact Assessment**:\n   - Determine business impact and affected users\u002Fsystems\n   - Evaluate data integrity and security implications\n   - Assess recovery time objectives and priorities\n\n### Step 6: Generate Remediation Plan\n**Action**: Create a comprehensive plan to address identified issues\n**Process**:\n1. **Immediate Actions** (Critical issues):\n   - Emergency fixes to restore service availability\n   - Temporary workarounds to mitigate impact\n   - Escalation procedures for complex issues\n\n2. **Short-term Fixes** (High\u002FMedium issues):\n   - Configuration adjustments and resource scaling\n   - Application updates and patches\n   - Monitoring and alerting improvements\n\n3. **Long-term Improvements** (All issues):\n   - Architectural changes for better resilience\n   - Preventive measures and monitoring enhancements\n   - Documentation and process improvements\n\n4. **Implementation Steps**:\n   - Prioritized action items with specific Azure CLI commands\n   - Testing and validation procedures\n   - Rollback plans for each change\n   - Monitoring to verify issue resolution\n\n### Step 7: User Confirmation & Report Generation\n**Action**: Present findings and get approval for remediation actions\n**Process**:\n1. **Display Health Assessment Summary**:\n   ```\n   ? Azure Resource Health Assessment\n   \n   ? Resource Overview:\n   • Resource: [Name] ([Type])\n   • Status: [Healthy\u002FWarning\u002FCritical]\n   • Location: [Region]\n   • Last Analyzed: [Timestamp]\n   \n   ? Issues Identified:\n   • Critical: X issues requiring immediate attention\n   • High: Y issues affecting performance\u002Freliability  \n   • Medium: Z issues for optimization\n   • Low: N informational items\n   \n   ? Top Issues:\n   1. [Issue Type]: [Description] - Impact: [High\u002FMedium\u002FLow]\n   2. [Issue Type]: [Description] - Impact: [High\u002FMedium\u002FLow]\n   3. [Issue Type]: [Description] - Impact: [High\u002FMedium\u002FLow]\n   \n   ?️ Remediation Plan:\n   • Immediate Actions: X items\n   • Short-term Fixes: Y items  \n   • Long-term Improvements: Z items\n   • Estimated Resolution Time: [Timeline]\n   \n   ❓ Proceed with detailed remediation plan? (y\u002Fn)\n   ```\n\n2. **Generate Detailed Report**:\n   ```markdown\n   # Azure Resource Health Report: [Resource Name]\n   \n   **Generated**: [Timestamp]  \n   **Resource**: [Full Resource ID]  \n   **Overall Health**: [Status with color indicator]\n   \n   ## ? Executive Summary\n   [Brief overview of health status and key findings]\n   \n   ## ? Health Metrics\n   - **Availability**: X% over last 24h\n   - **Performance**: [Average response time\u002Fthroughput]\n   - **Error Rate**: X% over last 24h\n   - **Resource Utilization**: [CPU\u002FMemory\u002FStorage percentages]\n   \n   ## ? Issues Identified\n   \n   ### Critical Issues\n   - **[Issue 1]**: [Description]\n     - **Root Cause**: [Analysis]\n     - **Impact**: [Business impact]\n     - **Immediate Action**: [Required steps]\n   \n   ### High Priority Issues  \n   - **[Issue 2]**: [Description]\n     - **Root Cause**: [Analysis]\n     - **Impact**: [Performance\u002Freliability impact]\n     - **Recommended Fix**: [Solution steps]\n   \n   ## ?️ Remediation Plan\n   \n   ### Phase 1: Immediate Actions (0-2 hours)\n   ```bash\n   # Critical fixes to restore service\n   [Azure CLI commands with explanations]\n   ```\n   \n   ### Phase 2: Short-term Fixes (2-24 hours)\n   ```bash\n   # Performance and reliability improvements\n   [Azure CLI commands with explanations]\n   ```\n   \n   ### Phase 3: Long-term Improvements (1-4 weeks)\n   ```bash\n   # Architectural and preventive measures\n   [Azure CLI commands and configuration changes]\n   ```\n   \n   ## ? Monitoring Recommendations\n   - **Alerts to Configure**: [List of recommended alerts]\n   - **Dashboards to Create**: [Monitoring dashboard suggestions]\n   - **Regular Health Checks**: [Recommended frequency and scope]\n   \n   ## ✅ Validation Steps\n   - [ ] Verify issue resolution through logs\n   - [ ] Confirm performance improvements\n   - [ ] Test application functionality\n   - [ ] Update monitoring and alerting\n   - [ ] Document lessons learned\n   \n   ## ? Prevention Measures\n   - [Recommendations to prevent similar issues]\n   - [Process improvements]\n   - [Monitoring enhancements]\n   ```\n\n## Error Handling\n- **Resource Not Found**: Provide guidance on resource name\u002Flocation specification\n- **Authentication Issues**: Guide user through Azure authentication setup\n- **Insufficient Permissions**: List required RBAC roles for resource access\n- **No Logs Available**: Suggest enabling diagnostic settings and waiting for data\n- **Query Timeouts**: Break down analysis into smaller time windows\n- **Service-Specific Issues**: Provide generic health assessment with limitations noted\n\n## Success Criteria\n- ✅ Resource health status accurately assessed\n- ✅ All significant issues identified and categorized\n- ✅ Root cause analysis completed for major problems\n- ✅ Actionable remediation plan with specific steps provided\n- ✅ Monitoring and prevention recommendations included\n- ✅ Clear prioritization of issues by business impact\n- ✅ Implementation steps include validation and rollback procedures\n",{"name":5,"description":7},"main","5269f7ea2d6c3a9bfda5ed878b6726cf509121fd","skills\u002Fazure-resource-health-diagnose",5340,"https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot","https:\u002F\u002Fawesome-copilot.github.com\u002F","https:\u002F\u002Fgithub.com\u002Fgithub","https:\u002F\u002Fgithub.com\u002Fabout","How people build software.","2026-11-11 13:41:32",{"source":8,"skillName":5,"commands":48,"prompt":58,"zipAvailable":59},[49,52,55],{"tool":50,"command":51},"npx","npx skills add github\u002Fawesome-copilot --skill azure-resource-health-diagnose",{"tool":53,"command":54},"bunx","bunx skills add github\u002Fawesome-copilot --skill azure-resource-health-diagnose",{"tool":56,"command":57},"pnpm","pnpm dlx skills add github\u002Fawesome-copilot --skill azure-resource-health-diagnose","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fazure-resource-health-diagnose\u002FSKILL.md",true,[],[62,97,124,153,187,204],{"skillNo":63,"name":64,"nameZh":6,"description":65,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":66,"categories":67,"keywords":76,"publishedAt":32},"01M70KXZNX9ES38N2A8M58ZZMZ","supabase-rls-policies","Write, review, and test Supabase Row Level Security (RLS) policies so that one user cannot read or change another user's rows. Use when creating or changing tables, policies, views, or security definer functions in a Supabase project, when reviewing a migration that touches RLS, or when asked to prove user isolation with pgTAP tests that sign in as two users.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fsupabase-rls-policies\u002FSKILL.md",[68,73],{"categoryNo":69,"categoryName":70,"taxonomyType":71,"taxonomyTypeDesc":72},"01JBSEEDCAT000000000000008","测试与质量","SCENARIO","使用场景",{"categoryNo":74,"categoryName":75,"taxonomyType":71,"taxonomyTypeDesc":72},"01JBSEEDCAT000000000000023","Skill与智能体开发",[77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96],"supabase","rls","supabase rls","supabase rls policies","project","when","review","change","read","write","security","isolation","tables","as","tests","prove","use","users","functions","with",{"skillNo":98,"name":99,"nameZh":6,"description":100,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":101,"categories":102,"keywords":104,"publishedAt":32},"01M70KWA5YWXDV6V8DZ19E3T2Y","skill-distribution-audit","Audit a skill collection before release or investigate installer omissions, archived\u002Ftemplate leakage, duplicate identities, and manifest drift. Reconcile the intended public source set, distribution manifest, and actual discovery output for a specified consumer version. Includes a deterministic set-comparison helper.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fskill-distribution-audit\u002FSKILL.md",[103],{"categoryNo":74,"categoryName":75,"taxonomyType":71,"taxonomyTypeDesc":72},[105,106,107,108,109,110,31,111,112,113,114,115,116,117,118,119,120,121,122,123],"distribution","skill distribution audit","audit","SET","deterministic","installer","discovery","comparison","helper","manifest","version","collection","drift","output","investigate","duplicate","template","release","reconcile",{"skillNo":125,"name":126,"nameZh":6,"description":127,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":128,"sourceHtmlUrl":129,"categories":130,"keywords":136,"publishedAt":32},"01M70KCJPFVW7PPQ49CC5R8JGK","logicapps-custom-code-net10-migration","Migrate Azure Logic Apps Standard local-function custom-code projects from .NET 8 to .NET 10. Use for legacy Logic Apps custom-code workspace upgrades, project\u002Fpackage configuration, custom-worker settings, publication, and integrated VS Code debugging. Not for ordinary .NET applications, standalone Azure Functions, Consumption workflows, or cloud deployment.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Flogicapps-custom-code-net10-migration\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Flogicapps-custom-code-net10-migration\u002FSKILL.md",[131],{"categoryNo":132,"categoryName":133,"taxonomyType":134,"taxonomyTypeDesc":135},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[137,138,139,140,141,142,31,81,143,144,145,20,146,147,148,93,149,150,151,152],"custom","code","logicapps custom code net10 migration","migration","projects","standalone","deployment","applications","local","worker","upgrades","package","apps","Legacy","debugging","workflows",{"skillNo":154,"name":155,"nameZh":6,"description":156,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":157,"sourceHtmlUrl":158,"categories":159,"keywords":164,"publishedAt":32},"01M6AEBN37RQMXJ3298PEY7PG1","winmd-api-search","Find and explore Windows desktop APIs. Use when building features that need platform capabilities — camera, file access, notifications, UI controls, AI\u002FML, sensors, networking, etc. Discovers the right API for a task and retrieves full type details (methods, properties, events, enumeration values).","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fwinmd-api-search\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fwinmd-api-search\u002FSKILL.md",[160,163],{"categoryNo":161,"categoryName":162,"taxonomyType":71,"taxonomyTypeDesc":72},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":132,"categoryName":133,"taxonomyType":134,"taxonomyTypeDesc":135},[165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,82,180,181,182,183,184,31,185,186],"winmd api search","search","api","windows","desktop","file access","enumeration","ui","ml","file","networking","capabilities","notifications","explore","access","features","full","camera","events","platform","methods","controls",{"skillNo":188,"name":189,"nameZh":6,"description":190,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":191,"licenseFileUrl":192,"sourceHtmlUrl":193,"categories":194,"keywords":200,"publishedAt":32},"01M6AE571R3SC1ZGE202B3NB5S","resemble-detect","Deepfake detection and media safety — detect AI-generated audio, images, video, and text, trace synthesis sources, apply watermarks, verify speaker identity, and analyze media intelligence using Resemble AI","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fresemble-detect\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fresemble-detect\u002FSKILL.md",[195,196,199],{"categoryNo":161,"categoryName":162,"taxonomyType":71,"taxonomyTypeDesc":72},{"categoryNo":197,"categoryName":198,"taxonomyType":71,"taxonomyTypeDesc":72},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":74,"categoryName":75,"taxonomyType":71,"taxonomyTypeDesc":72},[201,108,174,202,203],"resemble detect","https","identity",{"skillNo":205,"name":206,"nameZh":6,"description":207,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":191,"licenseFileUrl":208,"sourceHtmlUrl":209,"categories":210,"keywords":215,"publishedAt":32},"01M6AE30BSK2HCY4TQQ22Z8JRD","quality-playbook","Run a complete quality engineering audit on any codebase. Derives behavioral requirements from the code, generates spec-traced functional tests, runs a three-pass code review with regression tests, executes a multi-model spec audit (Council of Three), and produces a consolidated bug report with TDD-verified patches. Finds the 35% of real defects that structural code review alone cannot catch. Works with any language. Trigger on 'quality playbook', 'spec audit', 'Council of Three', 'fitness-to-purpose', or 'coverage theater'.","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fquality-playbook\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fgithub\u002Fawesome-copilot\u002Fblob\u002Fmain\u002Fskills\u002Fquality-playbook\u002FSKILL.md",[211,214],{"categoryNo":212,"categoryName":213,"taxonomyType":71,"taxonomyTypeDesc":72},"01JBSEEDCAT000000000000007","代码审查",{"categoryNo":74,"categoryName":75,"taxonomyType":71,"taxonomyTypeDesc":72},[216,217,218,219,138,83,9,107,220,221,202,222,223,224,225,226,227,228,229,230,231,232,91,233,234,235,236],"playbook","quality playbook","quality","code review","tdd","run","report","spec","bug report","council","engineering","functional","spec audit","bug","verified","multi-model","three","coverage","model","regression","structural"]