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Azure Pricing

GitHubOfficialCreated by anthonychuDistributed by GitHub

  • Skill
  • Tool integration
  • Cloud and DevOps
  • MIT
  • No issues found

From the author

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.
— the description by anthonychu

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Azure Pricing skill provides a direct interface to the Azure Retail Prices API, enabling users to fetch up-to-date pricing for various Azure services. It supports complex filtering by region, SKU, and price type, and includes specialized logic for estimating Copilot Studio agent credit consumption. The skill helps users compare pricing models—such as pay-as-you-go, reservations, and savings plans—and provides standardized formulas for calculating monthly and annual costs based on specific usage patterns.

What it does

  • Fetches real-time retail pricing for Azure services via the public API.
  • Supports filtering by service name, region, SKU, and price type.
  • Calculates monthly and annual cost estimates for various Azure resources.
  • Estimates Copilot Studio agent costs based on interaction volume and feature usage.
  • Compares different pricing models like reserved instances and spot pricing.
  • Provides structured cost summary tables for clear financial reporting.

When to use it

  • When you need to know the cost of a specific Azure service or SKU.
  • When comparing pricing across different Azure regions.
  • When building a cost estimate for a cloud architecture or workload.
  • When calculating the expected monthly credit consumption for a Copilot Studio agent.
  • When evaluating the savings potential of reserved instances or savings plans.

Advantages

  • Uses official, real-time data from the Azure Retail Prices API.
  • Simplifies complex pricing calculations with standardized formulas.
  • Provides clear, actionable cost breakdowns for stakeholders.
  • Includes specific logic for Copilot Studio credit estimation.
  • Reduces manual effort in gathering and normalizing pricing data.

Usage examples

“How much does a Standard_D4s_v5 VM cost in East US per month?”
The agent fetches the hourly rate for the specified VM, applies the 730-hour monthly multiplier, and presents a table showing the monthly and annual cost.
“Estimate the monthly cost for a Copilot Studio agent with 1000 users and 5 interactions each.”
The agent calculates total sessions, applies the relevant credit rates for knowledge and tool usage, and provides a breakdown of total credits and estimated USD cost.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/github/azure-pricing/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip azure-pricing.zip -d .agents/skills

Documentation by anthonychu

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-preview

Append $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.

  1. Identify filter fields from the user's request (service name, region, SKU, price type).

  2. 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.

  3. Build the filter string using the fields below and fetch the URL.

  4. Parse the Items array from the JSON response. Each item contains price and metadata.

  5. Follow pagination via NextPageLink if you need more than the first 1000 results (rarely needed).

  6. Calculate cost estimates using the formulas in references/COST-ESTIMATOR.md to produce monthly/annual estimates.

  7. Present results in a clear summary table with service, SKU, region, unit price, and monthly/annual estimates.

Filterable Fields

FieldTypeExample
serviceNamestring (exact, case-sensitive)'Functions', 'Virtual Machines', 'Storage'
serviceFamilystring (exact, case-sensitive)'Compute', 'Storage', 'Databases', 'AI + Machine Learning'
armRegionNamestring (exact, lowercase)'eastus', 'westeurope', 'southeastasia'
armSkuNamestring (exact)'Standard_D4s_v5', 'Standard_LRS'
skuNamestring (contains supported)'D4s v5'
priceTypestring'Consumption', 'Reservation', 'DevTestConsumption'
meterNamestring (contains supported)'Spot'

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

IssueSolution
Empty resultsBroaden the filter — remove priceType or armRegionName first
Wrong service nameUse serviceFamily filter to discover valid serviceName values
Missing savings plan dataEnsure api-version=2023-01-01-preview is in the URL
URL errorsCheck URL encoding — spaces as %20, quotes as %27
Too many resultsAdd more filter fields (region, SKU, priceType) to narrow down

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

  1. Gather inputs from the user: agent type (employee/customer), number of users, interactions/month, knowledge %, tenant graph %, tool usage per session.

  2. 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.

  3. Parse the fetched content to extract the current billing rates table (credits per feature type).

  4. Calculate the estimate using the rates and formulas from the fetched content:

    • total_sessions = users × interactions_per_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

  5. 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:

URLContent
https://learn.microsoft.com/en-us/microsoft-copilot-studio/requirements-messages-managementBilling rates table, billing examples, overage enforcement rules
https://learn.microsoft.com/en-us/microsoft-copilot-studio/billing-licensingLicensing options, M365 Copilot inclusions, prepaid vs pay-as-you-go

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).

Files

references/COPILOT-STUDIO-RATES.md

Copilot Studio — Billing Rates & Estimation

Source: Billing rates and management Estimator: Microsoft agent usage estimator Licensing Guide: Copilot Studio Licensing Guide

Copilot Credit Rate

1 Copilot Credit = $0.01 USD

Billing Rates (cached snapshot — last updated March 2026)

IMPORTANT: Always prefer fetching live rates from the source URLs below. Use this table only as a fallback if web fetch is unavailable.

FeatureRateUnit
Classic answer1per response
Generative answer2per response
Agent action5per action (triggers, deep reasoning, topic transitions, computer use)
Tenant graph grounding10per message
Agent flow actions13per 100 flow actions
Text & gen AI tools (basic)1per 10 responses
Text & gen AI tools (standard)15per 10 responses
Text & gen AI tools (premium)100per 10 responses
Content processing tools8per page
Notes
  • Classic answers: Predefined, manually authored responses. Static — don't change unless updated by the maker.

  • Generative answers: Dynamically generated using AI models (GPTs). Adapt based on context and knowledge sources.

  • Tenant graph grounding: RAG over tenant-wide Microsoft Graph, including external data via connectors. Optional per agent.

  • Agent actions: Steps like triggers, deep reasoning, topic transitions visible in the activity map. Includes Computer-Using Agents.

  • Text & gen AI tools: Prompt tools embedded in agents. Three tiers (basic/standard/premium) based on the underlying language model.

  • Agent flow actions: Predefined flow action sequences executed without agent reasoning/orchestration at each step.

Reasoning Model Billing

When using a reasoning-capable model:

Total cost = feature rate for operation + text & gen AI tools (premium) per 10 responses

Example: A generative answer using a reasoning model costs 2 credits (generative answer) + 10 credits (premium per response, prorated from 100/10).

Estimation Formula

Inputs
ParameterDescription
usersNumber of end users
interactions_per_monthAverage interactions per user per month
knowledge_pct% of responses from knowledge sources (0-100)
tenant_graph_pctOf knowledge responses, % using tenant graph grounding (0-100)
tool_promptAverage Prompt tool calls per session
tool_agent_flowAverage Agent flow calls per session
tool_computer_useAverage Computer use calls per session
tool_custom_connectorAverage Custom connector calls per session
tool_mcpAverage MCP (Model Context Protocol) calls per session
tool_rest_apiAverage REST API calls per session
prompts_basicAverage basic AI prompt uses per session
prompts_standardAverage standard AI prompt uses per session
prompts_premiumAverage premium AI prompt uses per session
Calculation
total_sessions = users × interactions_per_month

── Knowledge Credits ──
tenant_graph_credits    = total_sessions × (knowledge_pct/100) × (tenant_graph_pct/100) × 10
generative_answer_credits = total_sessions × (knowledge_pct/100) × (1 - tenant_graph_pct/100) × 2
classic_answer_credits  = total_sessions × (1 - knowledge_pct/100) × 1

── Agent Tools Credits ──
tool_calls = total_sessions × (prompt + computer_use + custom_connector + mcp + rest_api)
tool_credits = tool_calls × 5

── Agent Flow Credits ──
flow_calls = total_sessions × tool_agent_flow
flow_credits = ceil(flow_calls / 100) × 13

── Prompt Modifier Credits ──
basic_credits    = ceil(total_sessions × prompts_basic / 10) × 1
standard_credits = ceil(total_sessions × prompts_standard / 10) × 15
premium_credits  = ceil(total_sessions × prompts_premium / 10) × 100

── Total ──
total_credits = knowledge + tools + flows + prompts
cost_usd = total_credits × 0.01

Billing Examples (from Microsoft Docs)

Customer Support Agent
  • 4 classic answers + 2 generative answers per session

  • 900 customers/day

  • Daily: [(4×1) + (2×2)] × 900 = 7,200 credits

  • Monthly (30d): 216,000 credits = **$2,160**

Sales Performance Agent (Tenant Graph Grounded)
  • 4 generative answers + 4 tenant graph grounded responses per session

  • 100 unlicensed users

  • Daily: [(4×2) + (4×10)] × 100 = 4,800 credits

  • Monthly (30d): 144,000 credits = **$1,440**

Order Processing Agent
  • 4 action calls per trigger (autonomous)

  • Per trigger: 4 × 5 = 20 credits

Employee vs Customer Agent Types

Agent TypeIncluded with M365 Copilot?
Employee-facing (BtoE)Classic answers, generative answers, and tenant graph grounding are included at zero cost when the user has a Microsoft 365 Copilot license
Customer/partner-facingAll usage is billed normally

Overage Enforcement

  • Triggered at 125% of prepaid capacity

  • Custom agents are disabled (ongoing conversations continue)

  • Email notification sent to tenant admin

  • Resolution: reallocate capacity, purchase more, or enable pay-as-you-go

Live Source URLs

For the latest rates, fetch content from these pages:

Requirements and compatibility

Written for: GitHub Copilot

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

The author says: Requires internet access to prices.azure.com and learn.microsoft.com. No authentication needed.

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
anthonychu
Publisher
GitHub (Official)
Distributed by
GitHub
Source
github/awesome-copilot · skills/azure-pricing · commit 797337f
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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