azure-pricing skill
Fetches real-time Azure retail pricing using the Azure Retail Prices API (prices.azure.com) and estimates Copilot Studio agent credit consumption. Use when the user asks about the cost of any Azure service, wants to compare SKU prices, needs pricing data for a cost estimate, mentions Azure pricing, Azure costs, Azure billing, or asks about Copilot Studio pricing, Copilot Credits, or agent usage estimation. Covers compute, storage, networking, databases, AI, Copilot Studio, and all other Azure service families.
Is the azure-pricing skill safe?
Clean: nothing in its files matched our rules. We read 5 files in the folder on 2026-09-28.
No findings.
Install the azure-pricing skill
A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.
git clone --depth 1 https://github.com/github/awesome-copilot.git /tmp/awesome-copilot mkdir -p ~/.claude/skills cp -r /tmp/awesome-copilot/skills/azure-pricing ~/.claude/skills/azure-pricing
In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub
The instructions your agent would load
SKILL.md as published, without the frontmatter. Read it on GitHub
Azure Pricing Skill
Use this skill to retrieve real-time Azure retail pricing data from the public Azure Retail Prices API. No authentication is required.
When to Use This Skill
- User asks about the cost of an Azure service (e.g., "How much does a D4s v5 VM cost?")
- User wants to compare pricing across regions or SKUs
- User needs a cost estimate for a workload or architecture
- User mentions Azure pricing, Azure costs, or Azure billing
- User asks about reserved instance vs. pay-as-you-go pricing
- User wants to know about savings plans or spot pricing
API Endpoint
GET https://prices.azure.com/api/retail/prices?api-version=2023-01-01-previewAppend $filter as a query parameter using OData filter syntax. Always use api-version=2023-01-01-preview to ensure savings plan data is included.
Step-by-step Instructions
If anything is unclear about the user's request, ask clarifying questions to identify the correct filter fields and values before calling the API.
- Identify filter fields from the user's request (service name, region, SKU, price type).
- Resolve the region: the API requires armRegionName values in lowercase with no spaces (e.g. "East US" → eastus, "West Europe" → westeurope, "Southeast Asia" → southeastasia). See references/REGIONS.md for a complete list.
- Build the filter string using the fields below and fetch the URL.
- Parse the Items array from the JSON response. Each item contains price and metadata.
- Follow pagination via NextPageLink if you need more than the first 1000 results (rarely needed).
- Calculate cost estimates using the formulas in references/COST-ESTIMATOR.md to produce monthly/annual estimates.
- Present results in a clear summary table with service, SKU, region, unit price, and monthly/annual estimates.
Filterable Fields
Use eq for equality, and to combine, and contains(field, 'value') for partial matches.
Example Filter Strings
# All consumption prices for Functions in East US
serviceName eq 'Functions' and armRegionName eq 'eastus' and priceType eq 'Consumption'
# D4s v5 VMs in West Europe (consumption only)
armSkuName eq 'Standard_D4s_v5' and armRegionName eq 'westeurope' and priceType eq 'Consumption'
# All storage prices in a region
serviceName eq 'Storage' and armRegionName eq 'eastus'
# Spot pricing for a specific SKU
armSkuName eq 'Standard_D4s_v5' and contains(meterName, 'Spot') and armRegionName eq 'eastus'
# 1-year reservation pricing
serviceName eq 'Virtual Machines' and priceType eq 'Reservation' and armRegionName eq 'eastus'
# Azure AI / OpenAI pricing (now under Foundry Models)
serviceName eq 'Foundry Models' and armRegionName eq 'eastus' and priceType eq 'Consumption'
# Azure Cosmos DB pricing
serviceName eq 'Azure Cosmos DB' and armRegionName eq 'eastus' and priceType eq 'Consumption'Full Example Fetch URL
https://prices.azure.com/api/retail/prices?api-version=2023-01-01-preview&$filter=serviceName eq 'Functions' and armRegionName eq 'eastus' and priceType eq 'Consumption'URL-encode spaces as %20 and quotes as %27 when constructing the URL.
Key Response Fields
{
"Items": [
{
"retailPrice": 0.000016,
"unitPrice": 0.000016,
"currencyCode": "USD",
"unitOfMeasure": "1 Execution",
"serviceName": "Functions",
"skuName": "Premium",
"armRegionName": "eastus",
"meterName": "vCPU Duration",
"productName": "Functions",
"priceType": "Consumption",
"isPrimaryMeterRegion": true,
"savingsPlan": [
{ "unitPrice": 0.000012, "term": "1 Year" },
{ "unitPrice": 0.000010, "term": "3 Years" }
]
}
],
"NextPageLink": null,
"Count": 1
}Only use items where isPrimaryMeterRegion is true unless the user specifically asks for non-primary meters.
Supported serviceFamily Values
Analytics, Compute, Containers, Data, Databases, Developer Tools, Integration, Internet of Things, Management and Governance, Networking, Security, Storage, Web, AI + Machine Learning
Tips
- serviceName values are case-sensitive. When unsure, filter by serviceFamily first to discover valid serviceName values in the results.
- If results are empty, try broadening the filter (e.g., remove priceType or region constraints first).
- Prices are always in USD unless currencyCode is specified in the request.
- For savings plan prices, look for the savingsPlan array on each item (only in 2023-01-01-preview).
- See references/SERVICE-NAMES.md for a catalog of common service names and their correct casing.
- See references/COST-ESTIMATOR.md for cost estimation formulas and patterns.
- See references/COPILOT-STUDIO-RATES.md for Copilot Studio billing rates and estimation formulas.
Troubleshooting
Copilot Studio Agent Usage Estimation
Use this section when the user asks about Copilot Studio pricing, Copilot Credits, or agent usage costs.
When to Use This Section
- User asks about Copilot Studio pricing or costs
- User asks about Copilot Credits or agent credit consumption
- User wants to estimate monthly costs for a Copilot Studio agent
- User mentions agent usage estimation or the Copilot Studio estimator
- User asks how much an agent will cost to run
Key Facts
- 1 Copilot Credit = $0.01 USD
- Credits are pooled across the entire tenant
- Employee-facing agents with M365 Copilot licensed users get classic answers, generative answers, and tenant graph grounding at zero cost
- Overage enforcement triggers at 125% of prepaid capacity
Step-by-step Estimation
- Gather inputs from the user: agent type (employee/customer), number of users, interactions/month, knowledge %, tenant graph %, tool usage per session.
- Fetch live billing rates — use the built-in web fetch tool to download the latest rates from the source URLs listed below. This ensures the estimate always uses the most current Microsoft pricing.
- Parse the fetched content to extract the current billing rates table (credits per feature type).
- Calculate the estimate using the rates and formulas from the fetched content:
- totalsessions = users × interactionsper_month
- Knowledge credits: apply tenant graph grounding rate, generative answer rate, and classic answer rate
- Agent tools credits: apply agent action rate per tool call
- Agent flow credits: apply flow rate per 100 actions
- Prompt modifier credits: apply basic/standard/premium rates per 10 responses
- Present results in a clear table with breakdown by category, total credits, and estimated USD cost.
Source URLs to Fetch
When answering Copilot Studio pricing questions, fetch the latest content from these URLs to use as context:
Fetch at least the first URL (billing rates) before calculating. The second URL provides supplementary context for licensing questions.
See references/COPILOT-STUDIO-RATES.md for a cached snapshot of rates, formulas, and billing examples (use as fallback if web fetch is unavailable).
More skills from github/awesome-copilot
- Aacquire-codebase-knowledgeUse this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
- Aacreadiness-assessRun the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.
- Aacreadiness-generate-instructionsGenerate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.
- Aacreadiness-policyHelp the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.
- Aad-campaign-analyzerUse this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign planning or creative generation without performance data.
- Aadd-educational-commentsAdd educational comments to the file specified, or prompt asking for file to comment if one is not provided.
- Aadobe-illustrator-scriptingWrite, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
- Aagent-architectureDesign AI agent architectures through requirements discovery, or audit and diagnose architectural flaws in existing agents. Architecture only; excludes implementation and general code review.
- Aagent-governancePatterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
- Aagent-owasp-complianceCheck any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
- Aagent-skill-stackFind, evaluate, and assemble the smallest compatible set of AI Agent Skills for an end-to-end natural-language goal. Use when a user wants Skills for a multi-step workflow, asks which Skills fit a project, needs an installed-Skill audit or conflict check, has low Skill recall, wants indirect helpers such as humanizers or compliance checks, or wants a project-specific Skill Stack with controlled installation. Search local Skills, registries, GitHub, and OpenCLI; compare adoption, verified fit, safety, and overlap. Do not use for locating one known or common Skill; use the generic find-skills workflow.
- Aagent-supply-chainVerify supply chain integrity for AI agent plugins, tools, and dependencies. Use this skill when: - Generating SHA-256 integrity manifests for agent plugins or tool packages - Verifying that installed plugins match their published manifests - Detecting tampered, modified, or untracked files in agent tool directories - Auditing dependency pinning and version policies for agent components - Building provenance chains for agent plugin promotion (dev → staging → production) - Any request like "verify plugin integrity", "generate manifest", "check supply chain", or "sign this plugin"