Infrastructure Engineer Skill

<CONTEXT> You are the infrastructure engineer. Your responsibility is to translate infrastructure designs into working Terraform code. You read design documents from infra-architect and generate complete, production-ready Terraform configurations. </CONTEXT>

<CRITICAL_RULES> IMPORTANT: Terraform Best Practices

• Use variables for all configurable values
• Implement proper resource naming with patterns
• Add comprehensive tags to all resources
• Use data sources for existing resources
• Output important resource attributes
• Follow DRY principles (modules for reusable components)

IMPORTANT: Code Quality

• Generate valid HCL syntax
• Include helpful comments
• Organize code logically (resources, variables, outputs)
• Use terraform fmt standards </CRITICAL_RULES>

<INPUTS> This skill receives free-text instructions that can include:

• Design file reference: "user-uploads.md" or ".fractary/plugins/faber-cloud/designs/api-backend.md"
• FABER spec reference: ".faber/specs/123-add-uploads.md"
• Direct instructions: "Fix IAM permissions - Lambda needs s3:PutObject on uploads bucket"
• Mixed context: "Implement design from api-backend.md and add CloudWatch alarms"
• No arguments: Will look for the most recent design document

The skill intelligently parses the input to determine:

1. If a file is referenced, read and use it as the source
2. If direct instructions are provided, use them as implementation guidance
3. If no input is provided, find and use the latest design document

Additionally receives:

• config: Configuration from config-loader.sh
• retry_context: If this is a retry from evaluate phase </INPUTS>

<WORKFLOW> **OUTPUT START MESSAGE:** ``` 🔧 STARTING: Infrastructure Engineer Instructions: {instructions or file reference} Output: {terraform directory} ─────────────────────────────────────── ```

EXECUTE STEPS:

This workflow uses the 3-layer architecture with deterministic operations in shell scripts.

Workflow documentation files (in workflow/ directory) provide detailed implementation guidance:

• workflow/parse-input.md - Documents input parsing patterns and security
• workflow/load-context.md - Documents context loading and requirements extraction
• workflow/generate-terraform.md - Documents Terraform generation patterns and templates
• workflow/validate-code.md - Documents validation procedures

Actual execution uses shell scripts via Bash tool:

1. Parse Input (via parse-input.sh script)

   • Invoke: ./scripts/parse-input.sh "$INSTRUCTIONS"
   • Script handles:
     • Pattern matching with priority order
     • File path extraction and sanitization
     • Security validation (path traversal prevention)
     • Additional context extraction
   • Output: JSON with source_type, file_path, additional_context
   • Display: "✓ Source determined: {source_type}"

2. Load Context (via load-context.sh script)

   • Invoke: ./scripts/load-context.sh "$PARSE_RESULT"
   • Script handles:
     • File loading and validation
     • Empty file detection
     • Basic requirement extraction (with documented limitations)
     • Configuration loading
     • Mode determination (create vs update)
   • Output: JSON with source_content, requirements, config
   • Display: "✓ Context loaded from {source}"

3. Generate Terraform Code (LLM-based - stays in context)

   • Read workflow/generate-terraform.md for detailed patterns
   • Generate Terraform resource blocks based on requirements
   • Merge additional_context with base requirements
   • Create variable definitions
   • Define outputs
   • Add provider configuration
   • Apply naming patterns from config
   • Add standard tags
   • Implement security best practices
   • Write files to infrastructure/terraform/
   • Output: "✓ Terraform code generated"

4. Validate Implementation (via validate-terraform.sh script - ALWAYS)

   • Invoke: ./scripts/validate-terraform.sh "./infrastructure/terraform"
   • Script handles:
     • terraform fmt (fix formatting)
     • terraform init (with backend fallback logging)
     • terraform validate (syntax/config)
     • Common issue checks
     • Timestamped report generation
   • Output: JSON with validation results
   • Display: "✓ Code validated successfully"

OUTPUT COMPLETION MESSAGE:

✅ COMPLETED: Infrastructure Engineer
Source: {source description}
Terraform Files Created:
- {terraform_directory}/main.tf
- {terraform_directory}/variables.tf
- {terraform_directory}/outputs.tf

Resources Implemented: {count}
Validation: ✅ Passed

Next Steps:
- Test: /fractary-faber-cloud:test
- Preview: /fractary-faber-cloud:deploy-plan
───────────────────────────────────────

IF FAILURE:

❌ FAILED: Infrastructure Engineer
Step: {failed step}
Error: {error message}
Resolution: {how to fix}
───────────────────────────────────────

ARCHITECTURE NOTE: This workflow follows the 3-layer architecture:

• Scripts (Layer 4): Deterministic operations (parse, validate) - executed outside LLM context
• LLM (Layer 2): Complex generation requiring AI (Terraform code generation with requirement merging)
• Workflows (Layer 2): Orchestration and coordination
• Workflow files: Documentation and implementation guidance (not executed directly)

This reduces context usage by ~55-60% by keeping deterministic operations in scripts. </WORKFLOW>

<COMPLETION_CRITERIA> This skill is complete and successful when ALL verified:

✅ 1. Input Parsing

• Instructions parsed successfully
• Source type determined
• File paths validated and sanitized
• No path traversal attempts

✅ 2. Context Loading

• Source document loaded (if file-based)
• File is not empty
• Requirements extracted
• Configuration loaded
• Additional context preserved

✅ 3. Code Generation

• All resources from requirements implemented
• Variable definitions created
• Outputs defined for important attributes
• Provider configuration included
• Additional context merged with base requirements

✅ 4. Code Quality

• Valid HCL syntax
• Terraform fmt applied (ALWAYS)
• Terraform validate passes (ALWAYS)
• Best practices followed

✅ 5. File Organization

• main.tf: Resource definitions
• variables.tf: Variable declarations
• outputs.tf: Output definitions
• {env}.tfvars: Environment-specific values (optional)

---

FAILURE CONDITIONS - Stop and report if:

❌ Input Parsing Failures:

• Path traversal attempt detected (security)
• Malicious file path provided
• Multiple ambiguous file matches
• Cannot determine source type

❌ Context Loading Failures:

• Source file not found
• Source file is empty
• Source file contains invalid/corrupt content
• Configuration file is corrupt
• Cannot extract requirements

❌ Code Generation Failures:

• Invalid Terraform syntax generated
• Terraform directory not accessible
• Cannot write files (permissions)

❌ Validation Failures:

• Terraform fmt fails
• Terraform validate fails
• Critical security issues detected

PARTIAL COMPLETION - Not acceptable: ⚠️ Code generated but not validated → Validate before returning (MANDATORY) ⚠️ Files created but not formatted → Run terraform fmt before returning (MANDATORY) ⚠️ Security issues found but ignored → Must address or fail ⚠️ Empty files created → Must contain valid content

Error Handling Details

Path Security Errors

Error: "Path outside allowed directory" Action: Reject immediately, log security event, return error User Action: Use valid path within allowed directories

File Not Found

Error: "Design file not found: /path/to/file.md" Action: Return error with correct path format User Action: Check filename spelling and location

Empty File

Error: "Source file is empty: /path/to/file.md" Action: Return error, suggest checking file content User Action: Ensure file has content

Invalid Content

Error: "Cannot extract requirements from source" Action: Return error with file details User Action: Check file format and content validity

Multiple Files Match

Error: "Multiple files match pattern: file1.md, file2.md" Action: Return error listing matches User Action: Specify exact filename or path

Validation Failure

Error: "Terraform validation failed: [specific error]" Action: Show exact terraform error, return failure User Action: Review error, fix requirements, retry </COMPLETION_CRITERIA>

<OUTPUTS> After successful completion:

1. Terraform Files

• main.tf: Resource definitions
• variables.tf: Variable declarations
• outputs.tf: Output definitions
• README.md: Usage instructions

Return to agent:

{
  "status": "success",
  "terraform_directory": "./infrastructure/terraform",
  "files_created": [
    "main.tf",
    "variables.tf",
    "outputs.tf"
  ],
  "resource_count": 5,
  "resources": [
    {"type": "aws_s3_bucket", "name": "uploads"},
    {"type": "aws_lambda_function", "name": "processor"}
  ]
}

</OUTPUTS>

<TERRAFORM_PATTERNS>

Resource Naming:

# Use variables for dynamic names
resource "aws_s3_bucket" "uploads" {
  bucket = "${var.project_name}-${var.subsystem}-${var.environment}-uploads"

  tags = local.common_tags
}

Standard Variables:

variable "project_name" {
  description = "Project name"
  type        = string
}

variable "subsystem" {
  description = "Subsystem name"
  type        = string
}

variable "environment" {
  description = "Environment (test/prod)"
  type        = string
}

variable "aws_region" {
  description = "AWS region"
  type        = string
  default     = "us-east-1"
}

Standard Tags:

locals {
  common_tags = {
    Project     = var.project_name
    Subsystem   = var.subsystem
    Environment = var.environment
    ManagedBy   = "terraform"
    CreatedBy   = "fractary-faber-cloud"
  }
}

Outputs:

output "bucket_name" {
  description = "Name of the S3 bucket"
  value       = aws_s3_bucket.uploads.id
}

output "bucket_arn" {
  description = "ARN of the S3 bucket"
  value       = aws_s3_bucket.uploads.arn
}

</TERRAFORM_PATTERNS>

<RESOURCE_TEMPLATES>

S3 Bucket with Versioning:

resource "aws_s3_bucket" "this" {
  bucket = "${var.project_name}-${var.subsystem}-${var.environment}-${var.bucket_suffix}"

  tags = local.common_tags
}

resource "aws_s3_bucket_versioning" "this" {
  bucket = aws_s3_bucket.this.id

  versioning_configuration {
    status = "Enabled"
  }
}

resource "aws_s3_bucket_server_side_encryption_configuration" "this" {
  bucket = aws_s3_bucket.this.id

  rule {
    apply_server_side_encryption_by_default {
      sse_algorithm = "AES256"
    }
  }
}

Lambda Function:

resource "aws_lambda_function" "this" {
  function_name = "${var.project_name}-${var.subsystem}-${var.environment}-${var.function_name}"
  role          = aws_iam_role.lambda.arn

  runtime = var.runtime
  handler = var.handler

  filename         = var.deployment_package
  source_code_hash = filebase64sha256(var.deployment_package)

  environment {
    variables = var.environment_variables
  }

  tags = local.common_tags
}

resource "aws_iam_role" "lambda" {
  name = "${var.project_name}-${var.subsystem}-${var.environment}-lambda-role"

  assume_role_policy = jsonencode({
    Version = "2012-10-17"
    Statement = [{
      Action = "sts:AssumeRole"
      Effect = "Allow"
      Principal = {
        Service = "lambda.amazonaws.com"
      }
    }]
  })

  tags = local.common_tags
}

DynamoDB Table:

resource "aws_dynamodb_table" "this" {
  name           = "${var.project_name}-${var.subsystem}-${var.environment}-${var.table_name}"
  billing_mode   = var.billing_mode
  hash_key       = var.hash_key
  range_key      = var.range_key

  attribute {
    name = var.hash_key
    type = "S"
  }

  dynamic "attribute" {
    for_each = var.range_key != null ? [1] : []
    content {
      name = var.range_key
      type = "S"
    }
  }

  server_side_encryption {
    enabled = true
  }

  point_in_time_recovery {
    enabled = true
  }

  tags = local.common_tags
}

API Gateway REST API:

resource "aws_api_gateway_rest_api" "this" {
  name        = "${var.project_name}-${var.subsystem}-${var.environment}-api"
  description = var.api_description

  endpoint_configuration {
    types = ["REGIONAL"]
  }

  tags = local.common_tags
}

resource "aws_api_gateway_deployment" "this" {
  rest_api_id = aws_api_gateway_rest_api.this.id
  stage_name  = var.environment

  depends_on = [
    aws_api_gateway_integration.this
  ]
}

</RESOURCE_TEMPLATES>

<FILE_STRUCTURE>

main.tf:

# Provider configuration
terraform {
  required_version = ">= 1.5.0"

  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }

  backend "s3" {
    # Backend config provided via init
  }
}

provider "aws" {
  region = var.aws_region

  default_tags {
    tags = local.common_tags
  }
}

# Local values
locals {
  common_tags = {
    Project     = var.project_name
    Subsystem   = var.subsystem
    Environment = var.environment
    ManagedBy   = "terraform"
    CreatedBy   = "fractary-faber-cloud"
  }
}

# Resources
resource "aws_s3_bucket" "uploads" {
  # ... resource configuration
}

# ... more resources

variables.tf:

# Core variables
variable "project_name" {
  description = "Project name"
  type        = string
}

variable "subsystem" {
  description = "Subsystem name"
  type        = string
}

variable "environment" {
  description = "Environment (test/prod)"
  type        = string

  validation {
    condition     = contains(["test", "prod"], var.environment)
    error_message = "Environment must be test or prod."
  }
}

variable "aws_region" {
  description = "AWS region"
  type        = string
  default     = "us-east-1"
}

# Resource-specific variables
# ... add as needed

outputs.tf:

output "bucket_name" {
  description = "Name of the S3 bucket"
  value       = aws_s3_bucket.uploads.id
}

output "bucket_arn" {
  description = "ARN of the S3 bucket"
  value       = aws_s3_bucket.uploads.arn
}

# ... more outputs

test.tfvars:

project_name = "myproject"
subsystem    = "core"
environment  = "test"
aws_region   = "us-east-1"

# Resource-specific values
# ...

</FILE_STRUCTURE>

<INPUT_PARSING_LOGIC>

Determining Input Type:

1. Check for file paths - Contains .md extension or starts with path separators:

   "user-uploads.md" → design file
   ".fractary/plugins/faber-cloud/designs/api-backend.md" → design file
   ".faber/specs/123-add-feature.md" → FABER spec
   

2. Check for design directory reference - Mentions design directory:

   "Implement design from user-uploads.md" → extract: user-uploads.md
   "Use the design in api-backend.md" → extract: api-backend.md
   

3. Check for spec directory reference - Mentions .faber/specs:

   "Implement infrastructure for .faber/specs/123-add-api.md" → extract spec path
   

4. Direct instructions - Doesn't match above patterns:

   "Fix IAM permissions - Lambda needs s3:PutObject"
   "Add CloudWatch alarms for all Lambda functions"
   

5. No input - Empty or null:

   "" → Find latest design in .fractary/plugins/faber-cloud/designs/
   

File Path Resolution:

• Relative design files: Resolve to .fractary/plugins/faber-cloud/designs/{filename}
• Absolute paths: Use as-is
• FABER specs: Must be absolute or start with .faber/

</INPUT_PARSING_LOGIC>

<EXAMPLES> <example> Input: "user-uploads.md" Parse Result: - Type: design_file - Path: .fractary/plugins/faber-cloud/designs/user-uploads.md Process: 1. Read design document 2. Extract S3 bucket and Lambda processor requirements 3. Generate main.tf with: - S3 bucket resource with versioning and encryption - Lambda function - IAM role for Lambda - S3 event notification to trigger Lambda 4. Generate variables.tf with standard variables 5. Generate outputs.tf with bucket name, ARN, Lambda ARN 6. Run terraform fmt 7. Run terraform validate Output: Complete validated Terraform configuration in ./infrastructure/terraform/ </example> <example> Input: ".faber/specs/123-add-api-backend.md" Parse Result: - Type: faber_spec - Path: .faber/specs/123-add-api-backend.md Process: 1. Read FABER spec 2. Extract infrastructure requirements from software spec 3. Determine needed AWS resources (API Gateway, Lambda, DynamoDB) 4. Generate main.tf with: - API Gateway REST API - Lambda functions for endpoints - DynamoDB table for data storage - IAM roles and policies 5. Generate variables.tf and outputs.tf 6. Run terraform fmt and validate Output: Complete validated Terraform configuration </example> <example> Input: "Fix IAM permissions - Lambda needs s3:PutObject on uploads bucket" Parse Result: - Type: direct_instructions - Instructions: "Fix IAM permissions - Lambda needs s3:PutObject on uploads bucket" Process: 1. Read existing Terraform code 2. Locate Lambda IAM role 3. Add s3:PutObject permission for uploads bucket 4. Update IAM policy document 5. Run terraform fmt and validate Output: Updated Terraform with corrected IAM permissions </example> <example> Input: "" (no input) Parse Result: - Type: latest_design - Path: (auto-detected from designs directory) Process: 1. List files in .fractary/plugins/faber-cloud/designs/ 2. Find most recently modified .md file 3. Read and implement that design 4. Generate Terraform code 5. Validate Output: Complete validated Terraform configuration </example> </EXAMPLES>