aws-cdk-development
About
This skill provides expert AWS CDK guidance for building cloud infrastructure with TypeScript/Python, covering stack creation, construct patterns, and deployment workflows. Use it when implementing infrastructure as code, working with CDK/CloudFormation, or needing help with cdk synth/deploy commands. It includes integrated AWS tools and automated context for streamlined development.
Quick Install
Claude Code
Recommendednpx skills add zxkane/aws-skills -a claude-code/plugin add https://github.com/zxkane/aws-skillsgit clone https://github.com/zxkane/aws-skills.git ~/.claude/skills/aws-cdk-developmentCopy and paste this command in Claude Code to install this skill
Documentation
AWS CDK Development
This skill provides comprehensive guidance for developing AWS infrastructure using the Cloud Development Kit (CDK), with integrated MCP servers for accessing latest AWS knowledge and CDK utilities.
AWS Documentation Requirement
Always verify AWS facts using MCP tools (mcp__aws-mcp__* or mcp__*awsdocs*__*) before answering. The aws-mcp-setup dependency is auto-loaded — if MCP tools are unavailable, guide the user through that skill's setup flow.
CDK-Specific MCP Guidance
AWS Labs replaced the dedicated CDK MCP server (awslabs.cdk-mcp-server) with the broader awslabs.aws-iac-mcp-server, which covers CDK alongside CloudFormation and other AWS infrastructure-as-code workflows.
For CDK construct lookups, best-practice recommendations, and pattern guidance, install awslabs.aws-iac-mcp-server. It ships in the deploy-on-aws plugin from awslabs/agent-plugins, or can be registered directly with claude mcp add aws-iac uvx awslabs.aws-iac-mcp-server@latest.
When to reach for it:
- CDK construct recommendations and API lookups
- CDK and CloudFormation best-practice patterns
- Validation of synthesized templates
- Cross-resource configuration guidance
When to Use This Skill
Use this skill when:
- Creating new CDK stacks or constructs
- Refactoring existing CDK infrastructure
- Implementing Lambda functions within CDK
- Following AWS CDK best practices
- Validating CDK stack configurations before deployment
- Verifying AWS service capabilities and regional availability
Core CDK Principles
Resource Naming
CRITICAL: Do NOT explicitly specify resource names when they are optional in CDK constructs.
Why: CDK-generated names enable:
- Reusable patterns: Deploy the same construct/pattern multiple times without conflicts
- Parallel deployments: Multiple stacks can deploy simultaneously in the same region
- Cleaner shared logic: Patterns and shared code can be initialized multiple times without name collision
- Stack isolation: Each stack gets uniquely identified resources automatically
Pattern: Let CDK generate unique names automatically using CloudFormation's naming mechanism.
// ❌ BAD - Explicit naming prevents reusability and parallel deployments
new lambda.Function(this, 'MyFunction', {
functionName: 'my-lambda', // Avoid this
// ...
});
// ✅ GOOD - Let CDK generate unique names
new lambda.Function(this, 'MyFunction', {
// No functionName specified - CDK generates: StackName-MyFunctionXXXXXX
// ...
});
Security Note: For different environments (dev, staging, prod), follow AWS Security Pillar best practices by using separate AWS accounts rather than relying on resource naming within a single account. Account-level isolation provides stronger security boundaries.
Lambda Function Development
Use the appropriate Lambda construct based on runtime:
TypeScript/JavaScript: Use @aws-cdk/aws-lambda-nodejs
import { NodejsFunction } from 'aws-cdk-lib/aws-lambda-nodejs';
new NodejsFunction(this, 'MyFunction', {
entry: 'lambda/handler.ts',
handler: 'handler',
// Automatically handles bundling, dependencies, and transpilation
});
Python: Use @aws-cdk/aws-lambda-python
import { PythonFunction } from '@aws-cdk/aws-lambda-python-alpha';
new PythonFunction(this, 'MyFunction', {
entry: 'lambda',
index: 'handler.py',
handler: 'handler',
// Automatically handles dependencies and packaging
});
Benefits:
- Automatic bundling and dependency management
- Transpilation handled automatically
- No manual packaging required
- Consistent deployment patterns
Pre-Deployment Validation
Use a multi-layer validation strategy for comprehensive CDK quality checks:
Layer 1: Real-Time IDE Feedback (Recommended)
For TypeScript/JavaScript projects:
Install cdk-nag for synthesis-time validation:
npm install --save-dev cdk-nag
Add to your CDK app:
import { Aspects } from 'aws-cdk-lib';
import { AwsSolutionsChecks } from 'cdk-nag';
const app = new App();
Aspects.of(app).add(new AwsSolutionsChecks());
Optional - VS Code users: Install CDK NAG Validator extension for faster feedback on file save.
For Python/Java/C#/Go projects: cdk-nag is available in all CDK languages and provides the same synthesis-time validation.
Layer 2: Synthesis-Time Validation (Required)
-
Synthesis with cdk-nag: Validate stack with comprehensive rules
cdk synth # cdk-nag runs automatically via Aspects -
Suppress legitimate exceptions with documented reasons:
import { NagSuppressions } from 'cdk-nag'; // Document WHY the exception is needed NagSuppressions.addResourceSuppressions(resource, [ { id: 'AwsSolutions-L1', reason: 'Lambda@Edge requires specific runtime for CloudFront compatibility' } ]);
Layer 3: Pre-Commit Safety Net
-
Build: Ensure compilation succeeds
npm run build # or language-specific build command -
Tests: Run unit and integration tests
npm test # or pytest, mvn test, etc. -
Validation Script: Meta-level checks
./scripts/validate-stack.sh
The validation script now focuses on:
- Language detection
- Template size and resource count analysis
- Synthesis success verification
- (Note: Detailed anti-pattern checks are handled by cdk-nag)
Workflow Guidelines
Development Workflow
- Design: Plan infrastructure resources and relationships
- Verify AWS Services: Use AWS Documentation MCP to confirm service availability and features
- Check regional availability for all required services
- Verify service limits and quotas
- Confirm latest API specifications
- Implement: Write CDK constructs following best practices
- Use CDK MCP server for construct recommendations
- Reference CDK best practices via MCP tools
- Validate: Run pre-deployment checks (see above)
- Synthesize: Generate CloudFormation templates
- Review: Examine synthesized templates for correctness
- Deploy: Deploy to target environment
- Verify: Confirm resources are created correctly
Stack Organization
- Use nested stacks for complex applications
- Separate concerns into logical construct boundaries
- Export values that other stacks may need
- Use CDK context for environment-specific configuration
Testing Strategy
- Unit test individual constructs
- Integration test stack synthesis
- Snapshot test CloudFormation templates
- Validate resource properties and relationships
Using MCP Servers Effectively
When to Use AWS Documentation MCP
Always verify before implementing:
- New AWS service features or configurations
- Service availability in target regions
- API parameter specifications
- Service limits and quotas
- Security best practices for AWS services
Example scenarios:
- "Check if Lambda supports Python 3.13 runtime"
- "Verify DynamoDB is available in eu-south-2"
- "What are the current Lambda timeout limits?"
- "Get latest S3 encryption options"
When to Use CDK MCP Server
Leverage for CDK-specific guidance:
- CDK construct selection and usage
- CDK API parameter options
- CDK best practice patterns
- Construct property configurations
- CDK-specific optimizations
Example scenarios:
- "What's the recommended CDK construct for API Gateway REST API?"
- "How to configure NodejsFunction bundling options?"
- "Best practices for CDK stack organization"
- "CDK construct for DynamoDB with auto-scaling"
MCP Usage Best Practices
- Verify First: Always check AWS Documentation MCP before implementing new features
- Regional Validation: Check service availability in target deployment regions
- CDK Guidance: Use CDK MCP for construct-specific recommendations
- Stay Current: MCP servers provide latest information beyond knowledge cutoff
- Combine Sources: Use both skill patterns and MCP servers for comprehensive guidance
CDK Patterns Reference
For detailed CDK patterns, anti-patterns, and architectural guidance, refer to the comprehensive reference:
File: references/cdk-patterns.md
This reference includes:
- Common CDK patterns and their use cases
- Anti-patterns to avoid
- Security best practices
- Cost optimization strategies
- Performance considerations
Additional Resources
- Validation Script:
scripts/validate-stack.sh- Pre-deployment validation - CDK Patterns:
references/cdk-patterns.md- Detailed pattern library - AWS Documentation MCP: Integrated for latest AWS information
- CDK MCP Server: Integrated for CDK-specific guidance
GitHub Actions Integration
When GitHub Actions workflow files exist in the repository, ensure all checks defined in .github/workflows/ pass before committing. This prevents CI/CD failures and maintains code quality standards.
GitHub Repository
Related Skills
content-collections
MetaThis skill provides a production-tested setup for Content Collections, a TypeScript-first tool that transforms Markdown/MDX files into type-safe data collections with Zod validation. Use it when building blogs, documentation sites, or content-heavy Vite + React applications to ensure type safety and automatic content validation. It covers everything from Vite plugin configuration and MDX compilation to deployment optimization and schema validation.
polymarket
MetaThis skill enables developers to build applications with the Polymarket prediction markets platform, including API integration for trading and market data. It also provides real-time data streaming via WebSocket to monitor live trades and market activity. Use it for implementing trading strategies or creating tools that process live market updates.
creating-opencode-plugins
MetaThis skill helps developers create OpenCode plugins that hook into 25+ event types like commands, files, and LSP operations. It provides the plugin structure, event API specifications, and implementation patterns for JavaScript/TypeScript modules. Use it when you need to intercept, monitor, or extend the OpenCode AI assistant's lifecycle with custom event-driven logic.
sglang
MetaSGLang is a high-performance LLM serving framework that specializes in fast, structured generation for JSON, regex, and agentic workflows using its RadixAttention prefix caching. It delivers significantly faster inference, especially for tasks with repeated prefixes, making it ideal for complex, structured outputs and multi-turn conversations. Choose SGLang over alternatives like vLLM when you need constrained decoding or are building applications with extensive prefix sharing.
