terraform-search-import
Discover existing cloud resources using Terraform Search queries and bulk import them into Terraform management. Use when bringing unmanaged infrastructure under Terraform control, auditing cloud resources, or migrating to IaC.
What this skill does
# Terraform Search and Bulk Import
Discover existing cloud resources using declarative queries and generate configuration for bulk import into Terraform state.
**References:**
- [Terraform Search - list block](https://developer.hashicorp.com/terraform/language/block/tfquery/list)
- [Bulk Import](https://developer.hashicorp.com/terraform/language/import/bulk)
## When to Use
- Bringing unmanaged resources under Terraform control
- Auditing existing cloud infrastructure
- Migrating from manual provisioning to IaC
- Discovering resources across multiple regions/accounts
## IMPORTANT: Check Provider Support First
**BEFORE starting, you MUST verify the target resource type is supported:**
```bash
# Check what list resources are available
./scripts/list_resources.sh aws # Specific provider
./scripts/list_resources.sh # All configured providers
```
## Decision Tree
1. **Identify target resource type** (e.g., aws_s3_bucket, aws_instance)
2. **Check if supported**: Run `./scripts/list_resources.sh <provider>`
3. **Choose workflow**:
- ** If supported**: Check for terraform version available.
- ** If terraform version is above 1.14.0** Use Terraform Search workflow (below)
- ** If not supported or terraform version is below 1.14.0 **: Use Manual Discovery workflow (see [references/MANUAL-IMPORT.md](references/MANUAL-IMPORT.md))
**Note**: The list of supported resources is rapidly expanding. Always verify current support before using manual import.
## Prerequisites
Before writing queries, verify the provider supports list resources for your target resource type.
### Discover Available List Resources
Run the helper script to extract supported list resources from your provider:
```bash
# From a directory with provider configuration (runs terraform init if needed)
./scripts/list_resources.sh aws # Specific provider
./scripts/list_resources.sh # All configured providers
```
Or manually query the provider schema:
```bash
terraform providers schema -json | jq '.provider_schemas | to_entries | map({key: (.key | split("/")[-1]), value: (.value.list_resource_schemas // {} | keys)})'
```
Terraform Search requires an initialized working directory. Ensure you have a configuration with the required provider before running queries:
```hcl
# terraform.tf
terraform {
required_providers {
aws = {
source = "hashicorp/aws"
version = "~> 6.0"
}
}
}
```
Run `terraform init` to download the provider, then proceed with queries.
## Terraform Search Workflow (Supported Resources Only)
1. Create `.tfquery.hcl` files with `list` blocks defining search queries
2. Run `terraform query` to discover matching resources
3. Generate configuration with `-generate-config-out=<file>`
4. Review and refine generated `resource` and `import` blocks
5. Run `terraform plan` and `terraform apply` to import
## Query File Structure
Query files use `.tfquery.hcl` extension and support:
- `provider` blocks for authentication
- `list` blocks for resource discovery
- `variable` and `locals` blocks for parameterization
```hcl
# discovery.tfquery.hcl
provider "aws" {
region = "us-west-2"
}
list "aws_instance" "all" {
provider = aws
}
```
## List Block Syntax
```hcl
list "<list_type>" "<symbolic_name>" {
provider = <provider_reference> # Required
# Optional: filter configuration (provider-specific)
# The `config` block schema is provider-specific. Discover available options using `terraform providers schema -json | jq '.provider_schemas."registry.terraform.io/hashicorp/<provider>".list_resource_schemas."<resource_type>"'`
config {
filter {
name = "<filter_name>"
values = ["<value1>", "<value2>"]
}
region = "<region>" # AWS-specific
}
# Optional: limit results
limit = 100
}
```
## Supported List Resources
Provider support for list resources varies by version. **Always check what's available for your specific provider version using the discovery script.**
## Query Examples
### Basic Discovery
```hcl
# Find all EC2 instances in configured region
list "aws_instance" "all" {
provider = aws
}
```
### Filtered Discovery
```hcl
# Find instances by tag
list "aws_instance" "production" {
provider = aws
config {
filter {
name = "tag:Environment"
values = ["production"]
}
}
}
# Find instances by type
list "aws_instance" "large" {
provider = aws
config {
filter {
name = "instance-type"
values = ["t3.large", "t3.xlarge"]
}
}
}
```
### Multi-Region Discovery
```hcl
provider "aws" {
region = "us-west-2"
}
locals {
regions = ["us-west-2", "us-east-1", "eu-west-1"]
}
list "aws_instance" "all_regions" {
for_each = toset(local.regions)
provider = aws
config {
region = each.value
}
}
```
### Parameterized Queries
```hcl
variable "target_environment" {
type = string
default = "staging"
}
list "aws_instance" "by_env" {
provider = aws
config {
filter {
name = "tag:Environment"
values = [var.target_environment]
}
}
}
```
## Running Queries
```bash
# Execute queries and display results
terraform query
# Generate configuration file
terraform query -generate-config-out=imported.tf
# Pass variables
terraform query -var='target_environment=production'
```
## Query Output Format
```
list.aws_instance.all account_id=123456789012,id=i-0abc123,region=us-west-2 web-server
```
Columns: `<query_address> <identity_attributes> <name_tag>`
## Generated Configuration
The `-generate-config-out` flag creates:
```hcl
# __generated__ by Terraform
resource "aws_instance" "all_0" {
ami = "ami-0c55b159cbfafe1f0"
instance_type = "t2.micro"
# ... all attributes
}
import {
to = aws_instance.all_0
provider = aws
identity = {
account_id = "123456789012"
id = "i-0abc123"
region = "us-west-2"
}
}
```
## Post-Generation Cleanup
Generated configuration includes all attributes. Clean up by:
1. Remove computed/read-only attributes
2. Replace hardcoded values with variables
3. Add proper resource naming
4. Organize into appropriate files
```hcl
# Before: generated
resource "aws_instance" "all_0" {
ami = "ami-0c55b159cbfafe1f0"
instance_type = "t2.micro"
arn = "arn:aws:ec2:..." # Remove - computed
id = "i-0abc123" # Remove - computed
# ... many more attributes
}
# After: cleaned
resource "aws_instance" "web_server" {
ami = var.ami_id
instance_type = var.instance_type
subnet_id = var.subnet_id
tags = {
Name = "web-server"
Environment = var.environment
}
}
```
## Import by Identity
Generated imports use identity-based import (Terraform 1.12+):
```hcl
import {
to = aws_instance.web
provider = aws
identity = {
account_id = "123456789012"
id = "i-0abc123"
region = "us-west-2"
}
}
```
## Best Practices
### Query Design
- Start broad, then add filters to narrow results
- Use `limit` to prevent overwhelming output
- Test queries before generating configuration
### Configuration Management
- Review all generated code before applying
- Remove unnecessary default values
- Use consistent naming conventions
- Add proper variable abstraction
## Troubleshooting
| Issue | Solution |
|-------|----------|
| "No list resources found" | Check provider version supports list resources |
| Query returns empty | Verify region and filter values |
| Generated config has errors | Remove computed attributes, fix deprecated arguments |
| Import fails | Ensure resource not already in state |
## Complete Example
```hcl
# main.tf - Initialize provider
terraform {
required_version = ">= 1.14"
required_providers {
aws = {
source = "hashicorp/aws"
version = "~> 6.0" # Always use latest version
}
}
}
# discovery.tfquery.hcl - Define queries
provider "aws"Related in Cloud & DevOps
appbuilder-action-scaffolder
IncludedCreate, implement, deploy, and debug Adobe Runtime actions with consistent layout, validation, and error handling. Use this skill whenever the user needs to add actions to an App Builder project, understand action structure (params, response format, web/raw actions), configure actions in the manifest, use App Builder SDKs (State, Files, Events, database), deploy and invoke actions via CLI, debug action issues, or implement patterns such as webhook receivers, custom event providers, journaling consumers, large payload redirects, action sequence pipelines, and Asset Compute workers. Also trigger when users mention serverless functions in Adobe context, action logging, IMS authentication for actions, or cron-style scheduled actions.
orchestrating-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. Use this skill when the user needs a multi-step Data Cloud pipeline, cross-phase troubleshooting, or data space and data kit management. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase sf data360 workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching phase-specific skill), the task is STDM/session tracing/parquet telemetry (use observing-agentforce), standard CRM SOQL (use querying-soql), or Apex implementation (use generating-apex).
github-project-automation
IncludedAutomate GitHub repository setup with CI/CD workflows, issue templates, Dependabot, and CodeQL security scanning. Includes 12 production-tested workflows and prevents 18 errors: YAML syntax, action pinning, and configuration. Use when: setting up GitHub Actions CI/CD, creating issue/PR templates, enabling Dependabot or CodeQL scanning, deploying to Cloudflare Workers, implementing matrix testing, or troubleshooting YAML indentation, action version pinning, secrets syntax, runner versions, or CodeQL configuration. Keywords: github actions, github workflow, ci/cd, issue templates, pull request templates, dependabot, codeql, security scanning, yaml syntax, github automation, repository setup, workflow templates, github actions matrix, secrets management, branch protection, codeowners, github projects, continuous integration, continuous deployment, workflow syntax error, action version pinning, runner version, github context, yaml indentation error
sf-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase `sf data360` workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching sf-datacloud-* skill), the task is STDM/session tracing/parquet telemetry (use sf-ai-agentforce-observability), standard CRM SOQL (use sf-soql), or Apex implementation (use sf-apex).
fabric-cli
IncludedUse this skill for Fabric.so CLI workflows with the `fabric` terminal command: diagnose/install/login, search or browse a Fabric library, save notes/links/files, create folders, ask the Fabric AI assistant, manage tasks/workspaces, generate shell completion, check subscription usage, produce JSON output, and use Fabric as persistent agent memory. Do not use for Microsoft Fabric/Azure/Power BI `fab`, Daniel Miessler's Fabric framework, Python Fabric SSH, Fabric.js, or textile/fashion fabric.
lark
IncludedLark/Feishu CLI skills: lark-cli operations for docs, markdown, sheets, base, calendar, im, mail, task, okr, drive, wiki, slides, whiteboard, apps, approval, attendance, contact, vc, minutes, event. Use when the user needs to operate Lark/Feishu resources via lark-cli, send messages, manage documents, spreadsheets, calendars, tasks, OKRs, deploy web pages, or any Feishu/Lark workspace operations.