Aws Development logo

Aws Development

Organization
Mindrally
aws-development

AWS development best practices for Lambda, SAM, CDK, DynamoDB, IAM, and serverless architecture using Infrastructure as Code.

Overview

PublisherMindrally
Repositoryskills
Skill nameaws-development
Stars
259
Forks
41
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Mindrally on GitHub. Read the source before you install it.

Installation

Install the Aws Development AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Mindrally/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/aws-development .claude/skills/aws-development
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aws Development in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aws Development on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aws Development is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AWS Development Best Practices

Overview

This skill provides comprehensive guidelines for developing applications on Amazon Web Services (AWS), focusing on serverless architecture, Infrastructure as Code, and security best practices.

Core Principles

  • Write clean, well-structured code with accurate AWS SDK examples
  • Use Infrastructure as Code (Terraform, CDK, SAM) for all infrastructure
  • Follow the principle of least privilege for all IAM policies
  • Implement comprehensive logging, metrics, and tracing for observability

AWS Lambda Guidelines

Configuration Standards

  • Use TypeScript implementation on ARM64 architecture for better performance and cost
  • Set appropriate memory and timeout values based on workload requirements
  • Use environment variables for configuration, never hardcode values
  • Implement proper error handling and retry logic

Lambda Best Practices

typescript
// Use ES modules and typed handlers
import { APIGatewayProxyHandler } from 'aws-lambda';

export const handler: APIGatewayProxyHandler = async (event) => {
  try {
    // Validate input at function start
    if (!event.body) {
      return { statusCode: 400, body: JSON.stringify({ error: 'Missing body' }) };
    }

    // Business logic here

    return { statusCode: 200, body: JSON.stringify({ success: true }) };
  } catch (error) {
    console.error('Lambda error:', error);
    return { statusCode: 500, body: JSON.stringify({ error: 'Internal error' }) };
  }
};

AWS CDK Guidelines

Implementation Standards

  • Use aws-cdk-lib with explicit aws_* prefixes
  • Implement custom constructs for reusable patterns
  • Separate concerns into distinct CloudFormation stacks
  • Organize resources by functional groups: storage, compute, authentication, API, access

Project Structure

aws/
├── constructs/     # CDK custom constructs
├── stacks/         # CloudFormation stack definitions
├── functions/      # Lambda function implementations
└── tests/          # Infrastructure tests

CDK Best Practices

typescript
import * as cdk from 'aws-cdk-lib';
import * as lambda from 'aws-cdk-lib/aws_lambda';
import * as dynamodb from 'aws-cdk-lib/aws_dynamodb';

// Use custom constructs for reusable patterns
export class ApiConstruct extends Construct {
  constructor(scope: Construct, id: string, props: ApiProps) {
    super(scope, id);
    // Implementation
  }
}

DynamoDB Patterns

Table Design

  • Design tables around access patterns, not entity relationships
  • Use single-table design when appropriate
  • Implement GSIs for additional access patterns
  • Use on-demand capacity for variable workloads, provisioned for predictable

Best Practices

  • Always use strongly typed item definitions
  • Implement optimistic locking with version attributes
  • Use batch operations for multiple items
  • Enable point-in-time recovery for production tables

IAM Security Best Practices

Principles

  • Apply least privilege: grant only permissions needed
  • Use IAM roles, not access keys, for AWS service access
  • Implement resource-based policies where appropriate
  • Regular audit and rotate credentials

Policy Example

json
{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "dynamodb:GetItem",
        "dynamodb:PutItem",
        "dynamodb:Query"
      ],
      "Resource": "arn:aws:dynamodb:*:*:table/MyTable"
    }
  ]
}

SAM Template Configuration

Template Structure

yaml
AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31

Globals:
  Function:
    Timeout: 30
    Runtime: nodejs20.x
    Architectures:
      - arm64
    Tracing: Active

Resources:
  MyFunction:
    Type: AWS::Serverless::Function
    Properties:
      CodeUri: src/
      Handler: index.handler
      Events:
        Api:
          Type: Api
          Properties:
            Path: /items
            Method: GET

API Gateway Configuration

Best Practices

  • Use Cognito or IAM for authentication
  • Implement request validation
  • Enable CORS only when necessary
  • Use usage plans and API keys for rate limiting

Step Functions for Orchestration

  • Use Step Functions for complex workflows
  • Implement error handling with Catch and Retry
  • Use Express workflows for high-volume, short-duration
  • Use Standard workflows for long-running processes

Security Standards

Encryption

  • Enable encryption at rest for all storage services
  • Use AWS KMS for key management
  • Enable encryption in transit (TLS)
  • Use custom KMS keys for sensitive data

Secrets Management

  • Store secrets in AWS Secrets Manager or Parameter Store
  • Never commit secrets to version control
  • Rotate secrets automatically
  • Use IAM roles to access secrets

Observability

Logging

  • Use structured JSON logging
  • Include correlation IDs across services
  • Log at appropriate levels (INFO, WARN, ERROR)
  • Enable CloudWatch Logs Insights for querying

Monitoring

  • Create CloudWatch alarms for critical metrics
  • Use X-Ray for distributed tracing
  • Implement custom metrics for business KPIs
  • Set up dashboards for operational visibility

Testing

Unit Testing

  • Mock AWS SDK calls in unit tests
  • Use localstack or SAM local for integration testing
  • Test IAM policies with policy simulator
  • Validate CloudFormation/CDK with cfn-lint

Integration Testing

typescript
import { DynamoDBClient } from '@aws-sdk/client-dynamodb';
import { mockClient } from 'aws-sdk-client-mock';

const ddbMock = mockClient(DynamoDBClient);

beforeEach(() => {
  ddbMock.reset();
});

test('handler returns items', async () => {
  ddbMock.on(QueryCommand).resolves({ Items: [] });
  const result = await handler(event);
  expect(result.statusCode).toBe(200);
});

CI/CD Integration

  • Use AWS CodePipeline or GitHub Actions for CI/CD
  • Run cdk diff or sam validate before deployment
  • Implement staging environments (dev, staging, prod)
  • Use parameter overrides for environment-specific config

Common Pitfalls to Avoid

  1. Hardcoding AWS credentials or secrets
  2. Not setting appropriate Lambda timeouts
  3. Ignoring cold start optimization
  4. Over-provisioning resources
  5. Not implementing proper error handling
  6. Missing CloudWatch alarms
  7. Inadequate IAM policies (too permissive)
  8. Not using VPC when required for compliance

Frequently asked questions

What does the Aws Development AI skill do?

AWS development best practices for Lambda, SAM, CDK, DynamoDB, IAM, and serverless architecture using Infrastructure as Code.

Why use Aws Development on TypingMind?

Because you install it once and use it with any model. Aws Development is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aws Development in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Mindrally/skills/tree/main/aws-development. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Aws Development?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aws Development?

As many as you like. As long as a model supports skills, you can use Aws Development with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aws Development AI skill free?

Yes. It is published on GitHub by Mindrally under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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