cloudformation-to-pulumi▌
pulumi/agent-skills · updated Apr 8, 2026
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If you have already generated a migration plan before loading this skill, you MUST:
IMPORTANT: PLAN ADJUSTMENT REQUIRED
If you have already generated a migration plan before loading this skill, you MUST:
- Review your existing plan against the workflows and requirements in this skill
- Identify any gaps, missing steps, or incorrect assumptions
- Update and revise your plan to align with this skill's guidance
- Communicate the adjusted plan to the user before proceeding
CRITICAL SUCCESS REQUIREMENTS
The migration output MUST meet all of the following:
-
Complete Resource Coverage
- Every CloudFormation resource MUST be represented in the Pulumi program OR explicitly justified in the final report.
-
CloudFormation Logical ID as Resource Name
- CRITICAL: Every Pulumi resource MUST use the CloudFormation Logical ID as its resource name.
- This enables the
cdk-importertool to automatically find import IDs. - DO NOT rename resources. Automated import will FAIL if you change the logical IDs.
-
Successful Deployment
- The produced Pulumi program must be structurally valid and capable of a successful
pulumi preview(assuming proper config).
- The produced Pulumi program must be structurally valid and capable of a successful
-
Zero-Diff Import Validation (if importing existing resources)
- After import,
pulumi previewmust show NO updates, replaces, creates, or deletes.
- After import,
-
Final Migration Report
- Always output a formal migration report suitable for a Pull Request.
WHEN INFORMATION IS MISSING
If the user has not provided a CloudFormation template, you MUST fetch it from AWS using the stack name.
MIGRATION WORKFLOW
Follow this workflow exactly and in this order:
1. INFORMATION GATHERING
1.1 Verify AWS Credentials (ESC)
Running AWS commands requires credentials loaded via Pulumi ESC.
- If the user has already provided an ESC environment, use it.
- If no ESC environment is specified, ask the user which ESC environment to use before proceeding.
For detailed ESC information: Use skill pulumi-esc.
You MUST confirm the AWS region with the user.
1.2 Get the CloudFormation Template
If user provided a template file: Read the template directly.
If user only provided a stack name: Fetch the template from AWS:
aws cloudformation get-template \
--region <region> \
--stack-name <stack-name> \
--query 'TemplateBody' \
--output json > template.json
1.3 Build Resource Inventory
List all resources in the stack:
aws cloudformation list-stack-resources \
--region <region> \
--stack-name <stack-name> \
--output json
This provides:
LogicalResourceId- Use this as the Pulumi resource namePhysicalResourceId- The actual AWS resource IDResourceType- The CloudFormation resource type
1.4 Analyze Template Structure
Extract from the template:
- Parameters and their defaults
- Mappings
- Conditions
- Outputs
- Resource dependencies (Ref, GetAtt, DependsOn)
2. CODE CONVERSION (CloudFormation → Pulumi)
IMPORTANT: There is NO automated conversion tool for CloudFormation. You MUST convert each resource manually.
2.1 Resource Name Convention (CRITICAL)
Every Pulumi resource MUST use the CloudFormation Logical ID as its name.
// CloudFormation:
// "MyAppBucketABC123": { "Type": "AWS::S3::Bucket", ... }
// Pulumi - CORRECT:
const myAppBucket = new aws.s3.Bucket("MyAppBucketABC123", { ... });
// Pulumi - WRONG (DO NOT do this - import will fail):
const myAppBucket = new aws.s3.Bucket("my-app-bucket", { ... });
This naming convention is REQUIRED because the cdk-importer tool matches resources by name.
2.2 Provider Strategy
⚠️ CRITICAL: ALWAYS USE aws-native BY DEFAULT ⚠️
- Use
aws-nativefor all resources unless there's a specific reason to useaws. - CloudFormation types map directly to aws-native (e.g.,
AWS::S3::Bucket→aws-native.s3.Bucket). - Only use
aws(classic) when aws-native doesn't support a required feature.
This is MANDATORY for successful imports with cdk-importer. The cdk-importer works by matching CloudFormation resources to Pulumi resources, and CloudFormation maps 1:1 to aws-native. Using the classic aws provider will cause import failures.
2.3 CloudFormation Intrinsic Functions
Map CloudFormation intrinsic functions to Pulumi equivalents:
| CloudFormation | Pulumi Equivalent |
|---|---|
!Ref (resource) |
Resource output (e.g., bucket.id) |
!Ref (parameter) |
Pulumi config |
!GetAtt Resource.Attr |
Resource property output |
!Sub "..." |
pulumi.interpolate |
!Join [delim, [...]] |
pulumi.interpolate or .apply() |
!If [cond, true, false] |
Ternary operator |
!Equals [a, b] |
=== comparison |
!Select [idx, list] |
Array indexing with .apply() |
!Split [delim, str] |
.apply(v => v.split(...)) |
Fn::ImportValue |
Stack references or config |
Example: !Sub
// CloudFormation: !Sub "arn:aws:s3:::${MyBucket}/*"
// Pulumi:
const bucketArn = pulumi.interpolate`arn:aws:s3:::${myBucket.bucket}/*`;
Example: !GetAtt
// CloudFormation: !GetAtt MyFunction.Arn
// Pulumi:
const functionArn = myFunction.arn;
2.4 CloudFormation Conditions
Convert CloudFormation conditions to TypeScript logic:
// CloudFormation:
// "Conditions": {
// "CreateProdResources": { "Fn::Equals": [{ "Ref": "Environment" }, "prod"] }
// }
// Pulumi:
const config = new pulumi.Config();
const environment = config.require("environment");
const createProdResources = environment === "prod";
if (createProdResources) {
// Create production-only resources
}
2.5 CloudFormation Parameters
Convert parameters to Pulumi config:
// CloudFormation:
// "Parameters": {
// "InstanceType": { "Type": "String", "Default": "t3.micro" }
// }
// Pulumi:
const config = new pulumi.Config();
const instanceType = config.get("instanceType") || "t3.micro";
2.6 CloudFormation Mappings
Convert mappings to TypeScript objects:
// CloudFormation:
// "Mappings": {
// "RegionMap": {
// "us-east-1": { "AMI": "ami-12345" },
// "us-west-2": { "AMI": "ami-67890" }
// }
// }
// Pulumi:
const regionMap: Record<string, { ami: string }> = {
"us-east-1": { ami: "ami-12345" },
"us-west-2": { ami: "ami-67890" },
};
const ami = regionMap[aws.config.region!].ami;
2.7 Custom Resources
CloudFormation Custom Resources (AWS::CloudFormation::CustomResource or Custom::*) require special handling:
- Identify the purpose: Read the Lambda function code to understand what it does
- Find native replacement: Check if Pulumi has a native resource that provides the same functionality
- If no replacement: Document in the migration report that manual implementation is needed
2.8 TypeScript Output Handling
aws-native outputs often include undefined. Avoid ! non-null assertions. Always safely unwrap with .apply():
// WRONG
functionName: lambdaFunction.functionName!,
// CORRECT
functionName: lambdaFunction.functionName.apply(name => name || ""),
3. RESOURCE IMPORT
After conversion, import existing resources to be managed by Pulumi.
3.0 Pre-Import Validation (REQUIRED)
Before proceeding with import, verify your code:
- Check Provider Usage: Scan your code to ensure all resources use
aws-native - Document Exceptions: Any use of
aws(classic) provider must be justified - Verify Resource Names: Confirm all resources use CloudFormation Logical IDs as names
3.1 Automated Import with cdk-importer
Because you used CloudFormation Logical IDs as resource names, you can use the cdk-importer tool to automatically import resources.
Follow cfn-importer.md for detailed import procedures.
3.2 Manual Import for Failed Resources
For resources that fail automatic import:
- Follow cloudformation-id-lookup.md to find the import ID format
- Use
pulumi import:
pulumi import <pulumi-resource-type> <logical-id> <import-id>
3.3 Running Preview After Import
After import, run pulumi preview. There must be:
- NO updates
- NO replaces
- NO creates
- NO deletes
If there are changes, investigate and update the program until preview is clean.
OUTPUT FORMAT (REQUIRED)
When performing a migration, always produce:
- Overview (high-level description)
- Migration Plan Summary
- Pulumi Code Outputs (TypeScript; organized by file)
- Resource Mapping Table:
| CloudFormation Logical ID | CFN Type | Pulumi Type | Provider |
|---|---|---|---|
MyAppBucketABC123 |
AWS::S3::Bucket |
aws-native.s3.Bucket |
aws-native |
MyLambdaFunction456 |
AWS::Lambda::Function |
aws-native.lambda.Function |
aws-native |
- Custom Resources Summary (if any)
- Final Migration Report (PR-ready)
- Next Steps (import instructions)
FOR DETAILED DOCUMENTATION
Fetch content from official Pulumi documentation:
How to use cloudformation-to-pulumi on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add cloudformation-to-pulumi
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches cloudformation-to-pulumi from GitHub repository pulumi/agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate cloudformation-to-pulumi. Access the skill through slash commands (e.g., /cloudformation-to-pulumi) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★58 reviews- ★★★★★Noah Martin· Dec 20, 2024
I recommend cloudformation-to-pulumi for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Min Liu· Dec 8, 2024
Registry listing for cloudformation-to-pulumi matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Diego Mehta· Dec 4, 2024
Useful defaults in cloudformation-to-pulumi — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Camila Kapoor· Nov 27, 2024
Useful defaults in cloudformation-to-pulumi — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Anaya Li· Nov 23, 2024
Registry listing for cloudformation-to-pulumi matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Noah Yang· Nov 11, 2024
cloudformation-to-pulumi reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Olivia Zhang· Oct 18, 2024
I recommend cloudformation-to-pulumi for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Min Bhatia· Oct 14, 2024
cloudformation-to-pulumi reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Noah Menon· Oct 2, 2024
Registry listing for cloudformation-to-pulumi matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Camila Jain· Sep 21, 2024
cloudformation-to-pulumi fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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