AWS Serverless Eda

What it does

When your agent uses it

• Building serverless APIs
• Lambda functions
• Async workflows
• Mentions serverless

Example prompts

• “/aws-serverless-eda”

Requirements

• Pre-approved tools (allowed-tools): mcp__aws-mcp__*, mcp__awsdocs__*, mcp__cdk__*, Bash(sam *), Bash(aws lambda *), Bash(aws apigateway *), Bash(aws apigatewayv2 *), Bash(aws dynamodb *), Bash(aws stepfunctions *), Bash(aws events *), Bash(aws sqs *), Bash(aws sns *), Bash(aws sts get-caller-identity)

Workflow steps

7 steps, taken from the step headings in SKILL.md.

1. 1Speedy, Simple, Singular
2. 2Think Concurrent Requests, Not Total Requests
3. 3Share Nothing
4. 4Assume No Hardware Affinity
5. 5Orchestrate with State Machines, Not Function Chaining
6. 6Use Events to Trigger Transactions
7. 7Design for Failures and Duplicates

What it can do on your machine

Read from SKILL.md and the folder at commit 68530c6. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • mcp__aws-mcp__*
  • mcp__awsdocs__*
  • mcp__cdk__*
  • Bash(sam *)
  • Bash(aws lambda *)
  • Bash(aws apigateway *)
  • Bash(aws apigatewayv2 *)
  • Bash(aws dynamodb *)
  • Bash(aws stepfunctions *)
  • Bash(aws events *)

  …and 3 more on the same allowed-tools line.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • docs.aws.amazon.com
  • serverlessland.com

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

AWS Serverless Eda loads about 3.2k tokens when it runs, and up to ~32k if it reads all its reference files. Until then it costs about 133 tokens; SKILL.md has 758 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~133

When it runs · the whole SKILL.md, loaded when a task matches

~3.2k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~32k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from zxkane/aws-skills at commit 68530c6, republished under its MIT licence (© zxkane). 758 words, ~3,212 tokens.

name

aws-serverless-eda

description

AWS serverless and event-driven architecture expert based on Well-Architected Framework. Use when building serverless APIs, Lambda functions, REST APIs, microservices, or async workflows. Covers Lambda with TypeScript/Python, API Gateway (REST/HTTP), DynamoDB, Step Functions, EventBridge, SQS, SNS, and serverless patterns. Essential when user mentions serverless, Lambda, API Gateway, event-driven, async processing, queues, pub/sub, or wants to build scalable serverless applications with AWS best practices.

allowed-tools

mcp__aws-mcp__*, mcp__awsdocs__*, mcp__cdk__*, Bash(sam *), Bash(aws lambda *), Bash(aws apigateway *), Bash(aws apigatewayv2 *), Bash(aws dynamodb *), Bash(aws stepfunctions *), Bash(aws events *), Bash(aws sqs *), Bash(aws sns *), Bash(aws sts get-caller-identity)

context

fork

skills

aws-mcp-setup, aws-cdk-development

// ✅ 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
};

// 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 });

// ❌ 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),
  });
};

// ❌ 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),
});

// 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));

// ✅ GOOD - Idempotent operation
export const handler = async (event: SQSEvent) => {
  for (const record of event.Records) {
    const orderId = JSON.parse(record.body).orderId;

    // Check if already processed (idempotency)
    const existing = await dynamodb.getItem({
      TableName: process.env.TABLE_NAME,
      Key: { orderId },
    });

    if (existing.Item) {
      console.log('Order already processed:', orderId);
      continue; // Skip duplicate
    }

    // Process order
    await processOrder(orderId);

    // Mark as processed
    await dynamodb.putItem({
      TableName: process.env.TABLE_NAME,
      Item: { orderId, processedAt: Date.now() },
    });
  }
};

async function withRetry<T>(fn: () => Promise<T>, maxRetries = 3): Promise<T> {
  for (let i = 0; i < maxRetries; i++) {
    try {
      return await fn();
    } catch (error) {
      if (i === maxRetries - 1) throw error;
      await new Promise(resolve => setTimeout(resolve, Math.pow(2, i) * 1000));
    }
  }
  throw new Error('Max retries exceeded');
}

export const handler = async (event: SQSEvent) => {
  const failures: SQSBatchItemFailure[] = [];

  for (const record of event.Records) {
    try {
      await processRecord(record);
    } catch (error) {
      console.error('Failed to process record:', record.messageId, error);
      failures.push({ itemIdentifier: record.messageId });
    }
  }

  // Return partial batch failures for retry
  return { batchItemFailures: failures };
};

const dlq = new sqs.Queue(this, 'DLQ', {
  retentionPeriod: Duration.days(14),
});

const queue = new sqs.Queue(this, 'Queue', {
  deadLetterQueue: {
    queue: dlq,
    maxReceiveCount: 3,
  },
});

// Monitor DLQ depth
new cloudwatch.Alarm(this, 'DLQAlarm', {
  metric: dlq.metricApproximateNumberOfMessagesVisible(),
  threshold: 1,
  evaluationPeriods: 1,
  alarmDescription: 'Messages in DLQ require attention',
});

new NodejsFunction(this, 'Function', {
  entry: 'src/handler.ts',
  tracing: lambda.Tracing.ACTIVE, // X-Ray tracing
  environment: {
    POWERTOOLS_SERVICE_NAME: 'order-service',
    POWERTOOLS_METRICS_NAMESPACE: 'MyApp',
    LOG_LEVEL: 'INFO',
  },
});

© zxkane, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (references) in plugins/serverless-eda/skills/aws-serverless-eda of zxkane/aws-skills.

• SKILL.md
• references/deployment-best-practices.md
• references/eda-patterns.md
• references/observability-best-practices.md
• references/performance-optimization.md
• references/security-best-practices.md
• references/serverless-patterns.md

Open the folder on GitHubat commit 68530c6

Used in 4 other repositories

We found 9 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 4 other GitHub owners. This page covers the copy in zxkane/aws-skills, which our catalogue first saw on October 7, 2026.

• Microck/ordinary-claude-skillsskills_all/aws-skills/skills/aws-serverless-edaskills_categorized/cloud/aws-skills/skills/aws-serverless-eda
• CommandCodeAI/agent-skillsskills/aws-serverless-eda
• sickn33/agentic-awesome-skillsskills/aws-serverless-edaplugins/agentic-awesome-skills/skills/aws-serverless-eda+1 more
• lingxling/awesome-skills-cnantigravity-awesome-skills/skills/aws-serverless-edaantigravity-awesome-skills/plugins/agentic-awesome-skills/skills/aws-serverless-eda+1 more