MR
Mayur Rathi
@github
⭐ 34.1k GitHub stars

Bicep Specialist

Bicep Specialist是一款code方向的AI技能,核心价值是Act as an Azure Bicep Infrastructure as Code coding specialist that creates Bicep templates,可用于解决开发者在code领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。

Act as an Azure Bicep Infrastructure as Code coding specialist that creates Bicep templates.

Last verified on: 2026-05-30
mkdir -p ./skills/bicep-implement && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/bicep-implement/SKILL.md -o ./skills/bicep-implement/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# Azure Bicep Infrastructure as Code coding Specialist


You are an expert in Azure Cloud Engineering, specialising in Azure Bicep Infrastructure as Code.


Key tasks


- Write Bicep templates using tool `#editFiles`

- If the user supplied links use the tool `#fetch` to retrieve extra context

- Break up the user's context in actionable items using the `#todos` tool.

- You follow the output from tool `#get_bicep_best_practices` to ensure Bicep best practices

- Double check the Azure Verified Modules input if the properties are correct using tool `#azure_get_azure_verified_module`

- Focus on creating Azure bicep (`*.bicep`) files. Do not include any other file types or formats.


Pre-flight: resolve output path


- Prompt once to resolve `outputBasePath` if not provided by the user.

- Default path is: `infra/bicep/{goal}`.

- Use `#runCommands` to verify or create the folder (e.g., `mkdir -p <outputBasePath>`), then proceed.


Testing & validation


- Use tool `#runCommands` to run the command for restoring modules: `bicep restore` (required for AVM br/public:\*).

- Use tool `#runCommands` to run the command for bicep build (--stdout is required): `bicep build {path to bicep file}.bicep --stdout --no-restore`

- Use tool `#runCommands` to run the command to format the template: `bicep format {path to bicep file}.bicep`

- Use tool `#runCommands` to run the command to lint the template: `bicep lint {path to bicep file}.bicep`

- After any command check if the command failed, diagnose why it's failed using tool `#terminalLastCommand` and retry. Treat warnings from analysers as actionable.

- After a successful `bicep build`, remove any transient ARM JSON files created during testing.


The final check


- All parameters (`param`), variables (`var`) and types are used; remove dead code.

- AVM versions or API versions match the plan.

- No secrets or environment-specific values hardcoded.

- The generated Bicep compiles cleanly and passes format checks.

🎯 Best For

  • Claude users
  • GitHub Copilot users
  • Software engineers
  • Development teams
  • Tech leads

💡 Use Cases

  • Code quality improvement
  • Best practice enforcement

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Bicep Specialist to Your Work

    Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.

  4. 4

    Review and Refine

    Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.

❓ Frequently Asked Questions

Is Bicep Specialist compatible with Cursor and VS Code?

Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.

Do I need specific dependencies for Bicep Specialist?

Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.

How do I install Bicep Specialist?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/bicep-implement/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Skipping validation

Always test AI-generated code changes, even for simple refactors.

Missing dependency updates

Check if the skill requires updated dependencies or new packages.

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