Azure AI Deploy
timothywarner-org/claude-code
Ship a Python generative-AI app to Azure the keyless way, using DefaultAzureCredential and azd.
Interactive guided deployment flow for Azure OpenAI models with full customization control.
Install Customize
$ npx skills add microsoft/GitHub-Copilot-for-Azure --skill customize -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install microsoft/GitHub-Copilot-for-Azure customize --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/microsoft/GitHub-Copilot-for-Azure.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize .claude/skills/customize && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "customize" agent skill from https://github.com/microsoft/GitHub-Copilot-for-Azure/tree/main/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize into .claude/skills/customize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customize", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/microsoft/GitHub-Copilot-for-Azure/tree/main/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customizeType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add microsoft/GitHub-Copilot-for-Azure --skill customize -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install microsoft/GitHub-Copilot-for-Azure customize --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/GitHub-Copilot-for-Azure.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize .agents/skills/customize && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "customize" agent skill from https://github.com/microsoft/GitHub-Copilot-for-Azure/tree/main/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize into .agents/skills/customize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customize", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add microsoft/GitHub-Copilot-for-Azure --skill customize -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install microsoft/GitHub-Copilot-for-Azure customize --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/GitHub-Copilot-for-Azure.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize .cursor/skills/customize && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "customize" agent skill from https://github.com/microsoft/GitHub-Copilot-for-Azure/tree/main/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize into .cursor/skills/customize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customize", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/microsoft/GitHub-Copilot-for-Azure.git --path plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add microsoft/GitHub-Copilot-for-Azure --skill customize -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install microsoft/GitHub-Copilot-for-Azure customize --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/GitHub-Copilot-for-Azure.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize .gemini/skills/customize && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "customize" agent skill from https://github.com/microsoft/GitHub-Copilot-for-Azure/tree/main/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize into .gemini/skills/customize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customize", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install microsoft/GitHub-Copilot-for-Azure customizeInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add microsoft/GitHub-Copilot-for-Azure --skill customize -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/microsoft/GitHub-Copilot-for-Azure.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize .github/skills/customize && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "customize" agent skill from https://github.com/microsoft/GitHub-Copilot-for-Azure/tree/main/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize into .github/skills/customize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customize", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add microsoft/GitHub-Copilot-for-Azure --skill customize -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install microsoft/GitHub-Copilot-for-Azure customize --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/GitHub-Copilot-for-Azure.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize .opencode/skills/customize && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "customize" agent skill from https://github.com/microsoft/GitHub-Copilot-for-Azure/tree/main/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize into .opencode/skills/customize/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customize", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
customize- GitHub stars
- 255
- Used in
- 1 other repo
- Token cost
- ~2.2k tokens
- SKILL.md length
- 790 words
- Files
- 4 (incl. references)
- Skills in repo
- 56
- Repo updated
- First seen
- Licence
- MIT
At a glance
Interactive guided deployment flow for Azure OpenAI models with full customization control.
- : custom deployment
- SKILL.md covers Quick Reference, When to Use This Skill, Prerequisites and Workflow Overview, plus 5 more sections
- Calls az
- Customize model deployment
What it does
Customize is an agent skill from microsoft/GitHub-Copilot-for-Azure, published by the product's own GitHub organization. Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned…
Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `EXAMPLES.md`, `references/customize-guides.md` and `references/customize-workflow.md`).
It sits in DevOps & Cloud, covering Deployment. It works with Microsoft Azure and Azure OpenAI. The repository describes itself as: GitHub Copilot for Azure. The licence is MIT.
When your agent uses it
- : custom deployment
- Customize model deployment
- Configure content filter
- Deployment options
Example prompts
- “/customize”
What it can do on your machine
Read from SKILL.md and the folder at commit d8f4f4e. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
az
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use az, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Customize loads about 2.2k tokens when it runs, and up to ~6.5k if it reads all its reference files. Until then it costs about 151 tokens; SKILL.md has 790 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from microsoft/GitHub-Copilot-for-Azure at commit d8f4f4e, republished under its MIT licence (© microsoft). 790 words, ~2,236 tokens.
Download SKILL.mdSave it as
.claude/skills/customize/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- customize
- description
- Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
- license
- MIT
- metadata.author
- Microsoft
- metadata.version
- 1.0.1
Customize Model Deployment
Interactive guided workflow for deploying Azure OpenAI models with full customization control over version, SKU, capacity, content filtering, and advanced options.
Quick Reference
| Property | Description |
|---|---|
| Flow | Interactive step-by-step guided deployment |
| Customization | Version, SKU, Capacity, RAI Policy, Advanced Options |
| SKU Support | GlobalStandard, Standard, ProvisionedManaged, DataZoneStandard |
| Best For | Precise control over deployment configuration |
| Authentication | Azure CLI (az login) |
| Tools | Azure CLI, MCP tools (optional) |
When to Use This Skill
Use this skill when you need precise control over deployment configuration:
- ✅ Choose specific model version (not just latest)
- ✅ Select deployment SKU (GlobalStandard vs Standard vs PTU)
- ✅ Set exact capacity within available range
- ✅ Configure content filtering (RAI policy selection)
- ✅ Enable advanced features (dynamic quota, priority processing, spillover)
- ✅ PTU deployments (Provisioned Throughput Units)
Alternative: Use preset for quick deployment to the best available region with automatic configuration.
Comparison: customize vs preset
| Feature | customize | preset |
|---|---|---|
| Focus | Full customization control | Optimal region selection |
| Version Selection | User chooses from available | Uses latest automatically |
| SKU Selection | User chooses (GlobalStandard/Standard/PTU) | GlobalStandard only |
| Capacity | User specifies exact value | Auto-calculated (50% of available) |
| RAI Policy | User selects from options | Default policy only |
| Region | Current region first, falls back to all regions if no capacity | Checks capacity across all regions upfront |
| Use Case | Precise deployment requirements | Quick deployment to best region |
Prerequisites
- Azure subscription with Cognitive Services Contributor or Owner role
- Microsoft Foundry project resource ID (format:
/subscriptions/{sub}/resourceGroups/{rg}/providers/Microsoft.CognitiveServices/accounts/{account}/projects/{project}) - Azure CLI installed and authenticated (
az login) - Optional: Set
PROJECT_RESOURCE_IDenvironment variable
Workflow Overview
Complete Flow (14 Phases)
1. Verify Authentication
2. Get Project Resource ID
3. Verify Project Exists
4. Get Model Name (if not provided)
5. List Model Versions → User Selects
6. List SKUs for Version → User Selects
7. Get Capacity Range → User Configures
7b. If no capacity: Cross-Region Fallback → Query all regions → User selects region/project
8. List RAI Policies → User Selects
9. Configure Advanced Options (if applicable)
10. Configure Version Upgrade Policy
11. Generate Deployment Name
12. Review Configuration
13. Execute Deployment & MonitorFast Path (Defaults)
If user accepts all defaults (latest version, GlobalStandard SKU, recommended capacity, default RAI policy, standard upgrade policy), deployment completes in ~5 interactions.
Phase Summaries
⚠️ MUST READ: Before executing any phase, load references/customize-workflow.md for the full scripts and implementation details. The summaries below describe what each phase does — the reference file contains the how (CLI commands, quota patterns, capacity formulas, cross-region fallback logic).
| Phase | Action | Key Details |
|---|---|---|
| 1. Verify Auth | Check az account show; prompt az login if needed | Verify correct subscription is active |
| 2. Get Project ID | Read PROJECT_RESOURCE_ID env var or prompt user | ARM resource ID format required |
| 3. Verify Project | Parse resource ID, call az cognitiveservices account show | Extracts subscription, RG, account, project, region |
| 4. Get Model | List models via az cognitiveservices account list-models | User selects from available or enters custom name |
| 5. Select Version | Query versions for chosen model | Recommend latest; user picks from list |
| 6. Select SKU | Query model catalog + subscription quota, show only deployable SKUs | ⚠️ Never hardcode SKU lists — always query live data |
| 7. Configure Capacity | Query capacity API, validate min/max/step, user enters value | Cross-region fallback if no capacity in current region |
| 8. Select RAI Policy | Present content filter options | Default: Microsoft.DefaultV2 |
| 9. Advanced Options | Dynamic quota (GlobalStandard), priority processing (PTU), spillover | SKU-dependent availability |
| 10. Upgrade Policy | Choose: OnceNewDefaultVersionAvailable / OnceCurrentVersionExpired / NoAutoUpgrade | Default: auto-upgrade on new default |
| 11. Deployment Name | Auto-generate unique name, allow custom override | Validates format: ^[\w.-]{2,64}$ |
| 12. Review | Display full config summary, confirm before proceeding | User approves or cancels |
| 13. Deploy & Monitor | az cognitiveservices account deployment create, poll status | Timeout after 5 min; show endpoint + portal link |
Show full SKILL.md (277 more words)Show less
Error Handling
Common Issues and Resolutions
| Error | Cause | Resolution |
|---|---|---|
| Model not found | Invalid model name | List available models with az cognitiveservices account list-models |
| Version not available | Version not supported for SKU | Select different version or SKU |
| Insufficient quota | Capacity > available quota | Skill auto-searches all regions; fails only if no region has quota |
| SKU not supported | SKU not available in region | Cross-region fallback searches other regions automatically |
| Capacity out of range | Invalid capacity value | PREVENTED: Skill validates min/max/step at input (Phase 7) |
| Deployment name exists | Name conflict | Auto-incremented name generation |
| Authentication failed | Not logged in | Run az login |
| Permission denied | Insufficient permissions | Assign Cognitive Services Contributor role |
| Capacity query fails | API/permissions/network error | DEPLOYMENT BLOCKED: Will not proceed without valid quota data |
Troubleshooting Commands
# Check deployment status
az cognitiveservices account deployment show --name <account> --resource-group <rg> --deployment-name <name>
# List all deployments
az cognitiveservices account deployment list --name <account> --resource-group <rg> -o table
# Check quota usage
az cognitiveservices usage list --name <account> --resource-group <rg>
# Delete failed deployment
az cognitiveservices account deployment delete --name <account> --resource-group <rg> --deployment-name <name>Selection Guides & Advanced Topics
For SKU comparison tables, PTU sizing formulas, and advanced option details, load references/customize-guides.md.
SKU selection: GlobalStandard (production/HA) → Standard (dev/test) → ProvisionedManaged (high-volume/guaranteed throughput) → DataZoneStandard (data residency).
Capacity: TPM-based SKUs range from 1K (dev) to 100K+ (large production). PTU-based use formula: (Input TPM × 0.001) + (Output TPM × 0.002) + (Requests/min × 0.1).
Advanced options: Dynamic quota (GlobalStandard only), priority processing (PTU only, extra cost), spillover (overflow to backup deployment).
Related Skills
- preset - Quick deployment to best region with automatic configuration
- microsoft-foundry - Parent skill for all Microsoft Foundry operations
- quota — For quota viewing, increase requests, and troubleshooting quota errors, defer to this skill instead of duplicating guidance
- rbac - Manage permissions and access control
Notes
- Set
PROJECT_RESOURCE_IDenvironment variable to skip prompt - Not all SKUs available in all regions; capacity varies by subscription/region/model
- Custom RAI policies can be configured in Azure Portal
- Automatic version upgrades occur during maintenance windows
- Use Azure Monitor and Application Insights for production deployments
© microsoft, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (references) in plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize of microsoft/GitHub-Copilot-for-Azure.
- SKILL.md
- EXAMPLES.md
- references/customize-guides.md
- references/customize-workflow.md
Open the folder on GitHubat commit d8f4f4e
Used in 3 other repositories
We found 6 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in microsoft/GitHub-Copilot-for-Azure, which our catalogue first saw on October 7, 2026.
- microsoft/azure-skillsskills/microsoft-foundry/models/deploy-model/customize.github/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize
- microsoft/skills.github/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize
- aiskillstore/marketplaceskills/microsoft/customizeskills/microsoft/deploy-model/customize+1 more
Compare with similar skills
Customize next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Customize this skillmicrosoft/GitHub-Copilot-for-Azure | 255 | 1 repos | ~2.2k | Automated safety check: Pass | MIT | |
| Azure AI Deploytimothywarner-org/claude-code | 224 | — | ~731 | Automated safety check: Notes | MIT | |
| Azure Architecture Autopilotgithub/awesome-copilot | 40k | 1 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Aspiremicrosoft/aspire.dev | 196 | 4 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Aspire MonitoringCommunityToolkit/Aspire | 629 | — | ~3.5k | Automated safety check: Pass | MIT | |
| Azure Bicep Skilltimothywarner-org/claude-code | 224 | — | ~2.9k | Automated safety check: Pass | MIT |
Similar skills
- Official
Azure Architecture Autopilot
github/awesome-copilot
Designs Azure infrastructure from a natural-language description, or diagrams an existing resource group, then refines the design through conversation and deploys it with Bicep.
- Official
Aspire
microsoft/aspire.dev
Orchestrates Aspire distributed applications using the Aspire CLI for running, debugging, and managing distributed apps.
Aspire Monitoring
CommunityToolkit/Aspire
ANALYSIS SKILL - Observe Aspire apps: logs, traces, metrics, resource state, telemetry export, browser telemetry, and the standalone dashboard.
Azure Bicep Skill
timothywarner-org/claude-code
A skill your agent uses when authoring, reviewing, or refactoring Azure Bicep code.
Kcli Cluster Deployment
karmab/kcli
Guides deployment and management of Kubernetes clusters with kcli.
More from microsoft/GitHub-Copilot-for-Azure
All 56 skills in this repo- Official
Capacity
microsoft/GitHub-Copilot-for-Azure
Discovers available Azure OpenAI model capacity across regions and projects.
- Official
Deploy Model
microsoft/GitHub-Copilot-for-Azure
Unified Azure OpenAI model deployment skill with intelligent intent-based routing.
- Official
Entra Agent Id
microsoft/GitHub-Copilot-for-Azure
Provision Microsoft Entra Agent Identity Blueprints, BlueprintPrincipals, and per-instance Agent Identities via Microsoft Graph, and configure OAuth 2.0 token exchange (fmipath, OBO, cross-tenant)…
- Official
Microsoft Foundry
microsoft/GitHub-Copilot-for-Azure
Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end.
- Official
Azure Storage
microsoft/GitHub-Copilot-for-Azure
Azure Storage Services including Blob Storage, File Shares, Queue Storage, Table Storage, and Data Lake.
- Official
Azure Diagnostics
microsoft/GitHub-Copilot-for-Azure
Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage.
Related
Works with
Categories
Questions about Customize
What does Customize do?
Interactive guided deployment flow for Azure OpenAI models with full customization control. Customize is an agent skill from microsoft/GitHub-Copilot-for-Azure, published by the product's own GitHub organization. Interactive guided deployment flow for Azure OpenAI models with full customization control.
When should I use Customize?
Customize fits situations like: : custom deployment; customize model deployment; configure content filter; deployment options.
How do I install Customize in Claude Code?
Run `npx skills add microsoft/GitHub-Copilot-for-Azure --skill customize -a claude-code`. Or copy the skill folder (plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize in microsoft/GitHub-Copilot-for-Azure) into .claude/skills/customize in your project. Claude Code loads it when a task matches its description.
How do I install Customize in Codex?
Run `npx skills add microsoft/GitHub-Copilot-for-Azure --skill customize -a codex`. Or copy the skill folder (plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize in microsoft/GitHub-Copilot-for-Azure) into .agents/skills/customize in your project. Codex loads it when a task matches its description.
Can I use Customize in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microsoft/GitHub-Copilot-for-Azure --skill customize -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/customize, .gemini/skills/customize, .github/skills/customize and .opencode/skills/customize in your project.
What does Customize need to run?
Going by SKILL.md and its folder, Customize needs the command-line tools its instructions call (az).
Does Customize access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Customize safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Customize use?
Customize is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Customize use?
About 2.2k tokens (SKILL.md is roughly 8.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.2k tokens, read only when the agent opens those files.
What are the alternatives to Customize?
Skills that share tags, products or a category with Customize: Azure AI Deploy (timothywarner-org/claude-code, 224 stars), Azure Architecture Autopilot (github/awesome-copilot, 40k stars), Aspire (microsoft/aspire.dev, 196 stars) and Aspire Monitoring (CommunityToolkit/Aspire, 629 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Customize?
microsoft (a GitHub organization, an official publisher) maintains it in microsoft/GitHub-Copilot-for-Azure, which has 255 GitHub stars. The repository holds 56 skills in this directory. The repository was last updated on October 7, 2026.
Source: microsoft/GitHub-Copilot-for-Azure on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.