Identify and quantify Azure cost savings through resource analysis, utilization metrics, and actionable optimization recommendations.
Works with
Discovers orphaned resources (unattached disks, unused NICs, idle gateways) and over-provisioned services using Azure Quick Review scans
Queries actual costs from Azure Cost Management API and utilization data from Azure Monitor to support rightsizing recommendations
Generates prioritized optimization reports with estimated savings, validated pricing,
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionazure-cost-optimizationExecute the skills CLI command in your project's root directory to begin installation:
Fetches azure-cost-optimization from microsoft/github-copilot-for-azure and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate azure-cost-optimization. Access via /azure-cost-optimization in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
0
total installs
0
this week
180
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
180
stars
Analyze Azure subscriptions to identify cost savings through orphaned resource cleanup, rightsizing, and optimization recommendations based on actual usage data.
Use this skill when the user asks to:
Follow these steps in conversation with the user:
Before starting, verify these tools and permissions are available:
Required Tools:
az login)costmanagement, resource-graphRequired Permissions:
Verification commands:
az --version
az account show
az extension show --name costmanagement
azqr version
Get Azure cost optimization best practices to inform recommendations:
// Use Azure MCP best practices tool
mcp_azure_mcp_get_azure_bestpractices({
intent: "Get cost optimization best practices",
command: "get_bestpractices",
parameters: { resource: "cost-optimization", action: "all" }
})
If the user specifically requests Redis cost optimization, use the specialized Redis skill:
📋 Reference: Azure Redis Cost Optimization
When to use Redis-specific analysis:
Key capabilities:
redis_list commandReport templates available:
Note: For general subscription-wide cost optimization (including Redis), continue with Step 2. For Redis-only focused analysis, follow the instructions in the Redis-specific reference document.
If performing Redis cost optimization, ask the user to select their analysis scope:
Prompt the user with these options:
Wait for user response, then proceed to Step 2.
If the user specifically requests AKS cost optimization, use the specialized AKS reference files:
When to use AKS-specific analysis:
Tool Selection:
mcp_azure_mcp_aks for AKS operations (list clusters, get node pools, inspect configuration) — it provides richer metadata and is consistent with AKS skill conventions in this repoaz aks and kubectl only when the specific operation cannot be performed via the MCP surfaceReference files (load only what is needed for the request):
Note: For general subscription-wide cost optimization (including AKS resource groups), continue with Step 2. For AKS-focused analysis, follow the instructions in the relevant reference file above.
If performing AKS cost optimization, ask the user to select their analysis scope:
Prompt the user with these options:
Wait for user response before proceeding to Step 2.
Run azqr to find orphaned resources (immediate cost savings):
📋 Reference: Azure Quick Review - Detailed instructions for running azqr scans
// Use Azure MCP extension_azqr tool
extension_azqr({
subscription: "<SUBSCRIPTION_ID>",
"resource-group": "<RESOURCE_GROUP>" // optional
})
What to look for in azqr results:
Note: The Azure Quick Review reference document includes instructions for creating filter configurations, saving output to the
output/folder, and interpreting results for cost optimization.
For efficient cross-subscription resource discovery, use Azure Resource Graph. See Azure Resource Graph Queries for orphaned resource detection and cost optimization patterns.
List all resources in the subscription using Azure MCP tools or CLI:
# Get subscription info
az account show
# List all resources
az resource list --subscription "<SUBSCRIPTION_ID>" --resource-group "<RESOURCE_GROUP>"
# Use MCP tools for specific services (preferred):
# - Storage accounts, Cosmos DB, Key Vaults: use Azure MCP tools
# - Redis caches: use mcp_azure_mcp_redis tool (see ./references/azure-redis.md)
# - Web apps, VMs, SQL: use az CLI commands
Get actual cost data from Azure Cost Management API (last 30 days):
Create cost query file:
Create temp/cost-query.json with:
{
"type": "ActualCost",
"timeframe": "Custom",
"timePeriod": {
"from": "<START_DATE>",
"to": "<END_DATE>"
},
"dataset": {
"granularity": "None",
"aggregation": {
"totalCost": {
"name": "Cost",
"function": "Sum"
}
},
"grouping": [
{
"type": "Dimension",
"name": "ResourceId"
}
]
}
}
Action Required: Calculate
<START_DATE>(30 days ago) and<END_DATE>(today) in ISO 8601 format (e.g.,2025-11-03T00:00:00Z).
Execute cost query:
# Create temp folder
New-Item -ItemType Directory -Path "temp" -Force
# Query using REST API (more reliable than az costmanagement query)
az rest --method post `
--url "https://management.azure.com/subscriptions/<SUBSCRIPTION_ID>/resourceGroups/<RESOURCE_GROUP>/providers/Microsoft.CostManagement/query?api-version=2023-11-01" `
--body '@temp/cost-query.json'
Important: Save the query results to output/cost-query-result<timestamp>.json for audit trail.
Fetch current pricing from official Azure pricing pages using fetch_webpage:
// Validate pricing for key services
fetch_webpage({
urls: ["https://azure.microsoft.com/en-us/pricing/details/container-apps/"],
query: "pricing tiers and costs"
})
Key services to validate:
Important: Check for free tier allowances - many Azure services have generous free limits that may explain $0 costs.
Query Azure Monitor for utilization data (last 14 days) to support rightsizing recommendations:
# Calculate dates for last 14 days
$startTime = (Get-Date).AddDays(-14).ToString("yyyy-MM-ddTHH:mm:ssZ")
$endTime = Get-Date -Format "yyyy-MM-ddTHH:mm:ssZ"
# VM CPU utilization
az monitor metrics list `
--resource "<RESOURCE_ID>" `
--metric "Percentage CPU" `
--interval PT1H `
--aggregation Average `
--start-time $startTime `
--end-time $endTime
# App Service Plan utilization
az monitor metrics list `
--resource "<RESOURCE_ID>" `
--metric "CpuTime,Requests" `
--interval PT1H `
--aggregation Total `
--start-time $startTime `
--end-time $endTime
# Storage capacity
az monitor metrics list `
--resource "<RESOURCE_ID>" `
--metric "UsedCapacity,BlobCount" `
--interval PT1H `
--aggregation Average `
--start-time $startTime `
--end-time $endTime
Create a comprehensive cost optimization report in the output/
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
microsoft/github-copilot-for-azure
microsoft/GitHub-Copilot-for-Azure
wshobson/agents
github/awesome-copilot
wshobson/agents
kostja94/marketing-skills
azure-cost-optimization fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added azure-cost-optimization from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend azure-cost-optimization for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for azure-cost-optimization matched our evaluation — installs cleanly and behaves as described in the markdown.
azure-cost-optimization fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: azure-cost-optimization is focused, and the summary matches what you get after install.
We added azure-cost-optimization from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
azure-cost-optimization reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added azure-cost-optimization from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
azure-cost-optimization fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
showing 1-10 of 74