This skill provides comprehensive guidance for building serverless applications and event-driven architectures on AWS based on Well-Architected Framework principles.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionaws-serverless-edaExecute the skills CLI command in your project's root directory to begin installation:
Fetches aws-serverless-eda from zxkane/aws-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate aws-serverless-eda. Access via /aws-serverless-eda in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
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Automate repetitive workflows and reduce manual effort
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Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
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Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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This skill provides comprehensive guidance for building serverless applications and event-driven architectures on AWS based on Well-Architected Framework principles.
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.
This skill leverages the CDK MCP server (provided via aws-cdk-development dependency) and AWS Documentation MCP for serverless guidance.
Note: The following AWS MCP servers are available separately via the Full AWS MCP Server (see
aws-mcp-setupskill) and are not bundled with this plugin:
- AWS Serverless MCP — SAM CLI lifecycle (init, deploy, local test)
- AWS Lambda Tool MCP — Direct Lambda invocation
- AWS Step Functions MCP — Workflow orchestration
- Amazon SNS/SQS MCP — Messaging and queue management
Use this skill when:
Functions should be concise and single-purpose
// ✅ GOOD - Single purpose, focused function
export const processOrder = async (event: OrderEvent) => {
// Only handles order processing
const order = await validateOrder(event);
await saveOrder(order);
await publishOrderCreatedEvent(order);
return { statusCode: 200, body: JSON.stringify({ orderId: order.id }) };
};
// ❌ BAD - Function does too much
export const handleEverything = async (event: any) => {
// Handles orders, inventory, payments, shipping...
// Too many responsibilities
};
Keep functions environmentally efficient and cost-aware:
Design for concurrency, not volume
Lambda scales horizontally - design considerations should focus on:
// Consider concurrent Lambda executions accessing DynamoDB
const table = new dynamodb.Table(this, 'Table', {
billingMode: dynamodb.BillingMode.PAY_PER_REQUEST, // Auto-scales with load
});
// Or with provisioned capacity + auto-scaling
const table = new dynamodb.Table(this, 'Table', {
billingMode: dynamodb.BillingMode.PROVISIONED,
readCapacity: 5,
writeCapacity: 5,
});
// Enable auto-scaling for concurrent load
table.autoScaleReadCapacity({ minCapacity: 5, maxCapacity: 100 });
table.autoScaleWriteCapacity({ minCapacity: 5, maxCapacity: 100 });
Function runtime environments are short-lived
// ❌ BAD - Relying on local file system
export const handler = async (event: any) => {
fs.writeFileSync('/tmp/data.json', JSON.stringify(data)); // Lost after execution
};
// ✅ GOOD - Use persistent storage
export const handler = async (event: any) => {
await s3.putObject({
Bucket: process.env.BUCKET_NAME,
Key: 'data.json',
Body: JSON.stringify(data),
});
};
State management:
Applications must be hardware-agnostic
Infrastructure can change without notice:
Design for portability:
Use Step Functions for orchestration
// ❌ BAD - Lambda function chaining
export const handler1 = async (event: any) => {
const result = await processStep1(event);
await lambda.invoke({
FunctionName: 'handler2',
Payload: JSON.stringify(result),
});
};
// ✅ GOOD - Step Functions orchestration
const stateMachine = new stepfunctions.StateMachine(this, 'OrderWorkflow', {
definition: stepfunctions.Chain
.start(validateOrder)
.next(processPayment)
.next(shipOrder)
.next(sendConfirmation),
});
Benefits of Step Functions:
Event-driven over synchronous request/response
// Pattern: Event-driven processing
const bucket = new s3.Bucket(this, 'DataBucket');
bucket.addEventNotification(
s3.EventType.OBJECT_CREATED,
new s3n.LambdaDestination(processFunction),
{ prefix: 'uploads/' }
);
// Pattern: EventBridge integration
const rule = new events.Rule(this, 'OrderRule', {
eventPattern: {
source: ['orders'],
detailType: ['OrderPlaced'],
},
});
rule.addTarget(new targets.LambdaFunction(processOrderFunction));
Benefits:
Operations must be idempotent
// ✅ GOOD - Idempotent operation
export const handler = async (event: SQSEvent) => {
for (const record of event.Records) {
const orderId = JSON.parse(record.body).orderId;
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
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Useful defaults in aws-serverless-eda — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Useful defaults in aws-serverless-eda — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
aws-serverless-eda is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: aws-serverless-eda is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: aws-serverless-eda is focused, and the summary matches what you get after install.
Useful defaults in aws-serverless-eda — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added aws-serverless-eda from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
We added aws-serverless-eda from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
aws-serverless-eda fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
aws-serverless-eda fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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