FAI Build Bicep Module

Scaffolds Bicep modules with AVM metadata, decorators, parameter validation, output definitions, and deployment tests. Enables module composition, versioning, and registry (Bicep Registry, GitHub Container Registry) publishing.

Overview

This skill provides a structured, repeatable procedure for creates bicep modules with avm patterns, parameters, outputs, and deployment tests.. It can be used standalone as a LEGO block or auto-wired inside solution plays via the FAI Protocol.

Category: Infrastructure as Code Complexity: Medium Estimated Time: 10-30 minutes

Parameters

Steps

Step 1: Validate Prerequisites

Verify all required tools, credentials, and dependencies are available.

# Check required tools
command -v node >/dev/null 2>&1 || { echo 'Node.js required'; exit 1; }
command -v az >/dev/null 2>&1 || { echo 'Azure CLI required'; exit 1; }

Step 2: Load Configuration

Read settings from the FAI manifest and TuneKit config files.

# Load from fai-manifest.json if inside a play
CONFIG_DIR="${config_path:-config}"
if [ -f "fai-manifest.json" ]; then
  echo "FAI Protocol detected — auto-wiring context"
fi

Step 3: Execute Core Logic

Perform the primary operation: creates bicep modules with avm patterns, parameters, outputs, and deployment tests..

Step 4: Validate Results

Verify the output meets quality thresholds and WAF compliance.

# Validate output
if [ "$?" -eq 0 ]; then
  echo "✅ Skill completed successfully"
else
  echo "❌ Skill failed — check logs"
  exit 1
fi

Output

WAF Alignment

Compatible Solution Plays

• Play 02
• Play 11

Error Handling

Usage

Standalone

# Run this skill directly
npx frootai skill run fai-build-bicep-module

Inside a Solution Play

When referenced in fai-manifest.json, this skill auto-wires with the play's context:

{
  "primitives": {
    "skills": ["skills/fai-build-bicep-module/"]
  }
}

Via Agent Invocation

Agents can invoke this skill using the /skill command in Copilot Chat.

Configuration Reference

{
  "skill": "skill-name",
  "version": "1.0.0",
  "timeout_seconds": 300,
  "retry_attempts": 3,
  "log_level": "info"
}

Monitoring

Track skill execution metrics:

Troubleshooting

Notes

• This skill follows the FAI SKILL.md specification
• All outputs are deterministic when dry_run=true
• Integrates with FAI Engine for automated pipeline execution
• Part of the Infrastructure as Code category in the FAI primitives catalog