Agent skill

AWS Dynamodb

by alinaqi in alinaqi/maggy

AWS DynamoDB single-table design, GSI patterns, SDK v3 TypeScript/Python

MITAuto-check passedDatabases

Install AWS Dynamodb

skills CLI
$ npx skills add alinaqi/maggy --skill aws-dynamodb -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install alinaqi/maggy aws-dynamodb --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/alinaqi/maggy.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/aws-dynamodb .claude/skills/aws-dynamodb && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
aws-dynamodb
GitHub stars
707
Token cost
~4.6k tokens
SKILL.md length
313 words
Files
1
Skills in repo
71
Repo updated
First seen
Licence
MIT

At a glance

AWS DynamoDB single-table design, GSI patterns, SDK v3 TypeScript/Python

  • Tasks that involve NoSQL databases
  • SKILL.md covers Core Principle, Key Concepts, Single-Table Design and SDK v3 Setup (TypeScript), plus 5 more sections
  • Calls aws, npm and docker

What it does

AWS Dynamodb is an agent skill from alinaqi/maggy. AWS DynamoDB single-table design, GSI patterns, SDK v3 TypeScript/Python

Its SKILL.md is about 4.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Databases, covering NoSQL databases. It works with Amazon DynamoDB, Amazon Web Services, TypeScript and Python. The repository describes itself as: What started as an opinionated Claude Code setup kit is now an autonomous AI engineering command center. The licence is MIT.

When your agent uses it

  • Tasks that involve NoSQL databases

Example prompts

  • “/aws-dynamodb”

Requirements

  • Python 3
  • Node.js

What it can do on your machine

Read from SKILL.md and the folder at commit 72a456e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • aws
    • npm
    • docker

    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
    • aws.amazon.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 Dynamodb loads about 4.6k tokens when it runs. Until then it costs about 21 tokens; SKILL.md has 313 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~21
When it runs · the whole SKILL.md, loaded when a task matches
~4.6k

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

Auto-check passed

The automated check found no risky patterns in SKILL.md.

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 alinaqi/maggy at commit 72a456e, republished under its MIT licence (© alinaqi). 313 words, ~4,635 tokens.

Download SKILL.mdSave it as .claude/skills/aws-dynamodb/SKILL.md (or your agent's skills folder).
name
aws-dynamodb
description
AWS DynamoDB single-table design, GSI patterns, SDK v3 TypeScript/Python
when-to-use
When working with DynamoDB tables or AWS SDK data operations
user-invocable
false
paths
**/dynamodb*, **/dynamo*, serverless.*, template.yaml
effort
medium

AWS DynamoDB Skill

DynamoDB is a fully managed NoSQL database designed for single-digit millisecond performance at any scale. Master single-table design and access pattern modeling.

Sources: DynamoDB Docs | SDK v3 | Best Practices


Core Principle

Design for access patterns, not entities. Think access-pattern-first.

DynamoDB requires you to know your queries before designing your schema. Model around how you'll access data, not how data relates. Single-table design stores multiple entity types in one table using generic key attributes.


Key Concepts

ConceptDescription
Partition Key (PK)Primary key attribute - determines data distribution
Sort Key (SK)Optional secondary key for range queries within partition
GSIGlobal Secondary Index - alternate partition/sort keys
LSILocal Secondary Index - same partition, different sort
ItemSingle record (max 400 KB)
AttributeField within an item

Single-Table Design

Why Single Table?
  • Fetch related data in single query
  • Reduce round trips and costs
  • Enable transactions across entity types
  • Simplify operations (backup, restore, IAM)
Generic Key Pattern
typescript
// Instead of entity-specific keys:
// userId, orderId, productId

// Use generic keys that work for all entities:
interface BaseItem {
  PK: string;   // Partition Key
  SK: string;   // Sort Key
  GSI1PK?: string;  // First GSI partition key
  GSI1SK?: string;  // First GSI sort key
  EntityType: string;
  // ... entity-specific attributes
}
Example: E-commerce Schema
typescript
// Users
{ PK: 'USER#123', SK: 'PROFILE', EntityType: 'User', name: 'John', email: 'john@test.com' }
{ PK: 'USER#123', SK: 'ADDRESS#1', EntityType: 'Address', street: '123 Main', city: 'NYC' }

// Orders for user (1:N relationship)
{ PK: 'USER#123', SK: 'ORDER#2024-001', EntityType: 'Order', total: 99.99, status: 'shipped' }
{ PK: 'USER#123', SK: 'ORDER#2024-002', EntityType: 'Order', total: 49.99, status: 'pending' }

// Order details (query by order ID using GSI)
{ PK: 'USER#123', SK: 'ORDER#2024-001', GSI1PK: 'ORDER#2024-001', GSI1SK: 'ORDER', ... }
{ PK: 'ORDER#2024-001', SK: 'ITEM#1', GSI1PK: 'ORDER#2024-001', GSI1SK: 'ITEM#1', productId: 'PROD#456', qty: 2 }

// Products
{ PK: 'PROD#456', SK: 'PRODUCT', EntityType: 'Product', name: 'Widget', price: 29.99 }
Access Patterns Covered
1. Get user profile          → Query PK='USER#123', SK='PROFILE'
2. Get user with addresses   → Query PK='USER#123', SK begins_with 'ADDRESS'
3. Get all user orders       → Query PK='USER#123', SK begins_with 'ORDER'
4. Get order by ID           → Query GSI1, PK='ORDER#2024-001'
5. Get order with items      → Query GSI1, PK='ORDER#2024-001'
6. Get product details       → Query PK='PROD#456', SK='PRODUCT'

SDK v3 Setup (TypeScript)

Install Dependencies
bash
npm install @aws-sdk/client-dynamodb @aws-sdk/lib-dynamodb
Client Configuration
typescript
// lib/dynamodb.ts
import { DynamoDBClient } from '@aws-sdk/client-dynamodb';
import { DynamoDBDocumentClient } from '@aws-sdk/lib-dynamodb';

const client = new DynamoDBClient({
  region: process.env.AWS_REGION || 'us-east-1',
  // For local development with DynamoDB Local
  ...(process.env.DYNAMODB_LOCAL && {
    endpoint: 'http://localhost:8000',
    credentials: { accessKeyId: 'local', secretAccessKey: 'local' }
  })
});

// Document client for simplified operations
export const docClient = DynamoDBDocumentClient.from(client, {
  marshallOptions: {
    removeUndefinedValues: true,  // Important: match v2 behavior
    convertClassInstanceToMap: true
  },
  unmarshallOptions: {
    wrapNumbers: false
  }
});

export const TABLE_NAME = process.env.DYNAMODB_TABLE || 'MyTable';
Type Definitions
typescript
// types/dynamodb.ts
export interface BaseItem {
  PK: string;
  SK: string;
  GSI1PK?: string;
  GSI1SK?: string;
  EntityType: string;
  createdAt: string;
  updatedAt: string;
}

export interface User extends BaseItem {
  EntityType: 'User';
  userId: string;
  email: string;
  name: string;
}

export interface Order extends BaseItem {
  EntityType: 'Order';
  orderId: string;
  userId: string;
  total: number;
  status: 'pending' | 'paid' | 'shipped' | 'delivered';
}

// Key builders
export const keys = {
  user: (userId: string) => ({
    PK: `USER#${userId}`,
    SK: 'PROFILE'
  }),
  userOrders: (userId: string) => ({
    PK: `USER#${userId}`,
    SKPrefix: 'ORDER#'
  }),
  order: (userId: string, orderId: string) => ({
    PK: `USER#${userId}`,
    SK: `ORDER#${orderId}`,
    GSI1PK: `ORDER#${orderId}`,
    GSI1SK: 'ORDER'
  })
};

CRUD Operations

Put Item (Create/Update)
typescript
import { PutCommand } from '@aws-sdk/lib-dynamodb';
import { docClient, TABLE_NAME } from './dynamodb';
import { User, keys } from './types';

async function createUser(userId: string, data: { email: string; name: string }): Promise<User> {
  const now = new Date().toISOString();
  const item: User = {
    ...keys.user(userId),
    EntityType: 'User',
    userId,
    email: data.email,
    name: data.name,
    createdAt: now,
    updatedAt: now
  };

  await docClient.send(new PutCommand({
    TableName: TABLE_NAME,
    Item: item,
    ConditionExpression: 'attribute_not_exists(PK)'  // Prevent overwrite
  }));

  return item;
}
Get Item (Read)
typescript
import { GetCommand } from '@aws-sdk/lib-dynamodb';

async function getUser(userId: string): Promise<User | null> {
  const result = await docClient.send(new GetCommand({
    TableName: TABLE_NAME,
    Key: keys.user(userId)
  }));

  return (result.Item as User) || null;
}
typescript
import { QueryCommand } from '@aws-sdk/lib-dynamodb';

// Get all orders for a user
async function getUserOrders(userId: string): Promise<Order[]> {
  const result = await docClient.send(new QueryCommand({
    TableName: TABLE_NAME,
    KeyConditionExpression: 'PK = :pk AND begins_with(SK, :sk)',
    ExpressionAttributeValues: {
      ':pk': `USER#${userId}`,
      ':sk': 'ORDER#'
    },
    ScanIndexForward: false  // Newest first
  }));

  return (result.Items as Order[]) || [];
}

// Query GSI by order ID
async function getOrderById(orderId: string): Promise<Order | null> {
  const result = await docClient.send(new QueryCommand({
    TableName: TABLE_NAME,
    IndexName: 'GSI1',
    KeyConditionExpression: 'GSI1PK = :pk',
    ExpressionAttributeValues: {
      ':pk': `ORDER#${orderId}`
    }
  }));

  return (result.Items?.[0] as Order) || null;
}

// Paginated query
async function getUserOrdersPaginated(
  userId: string,
  pageSize: number = 20,
  lastKey?: Record<string, any>
): Promise<{ items: Order[]; lastKey?: Record<string, any> }> {
  const result = await docClient.send(new QueryCommand({
    TableName: TABLE_NAME,
    KeyConditionExpression: 'PK = :pk AND begins_with(SK, :sk)',
    ExpressionAttributeValues: {
      ':pk': `USER#${userId}`,
      ':sk': 'ORDER#'
    },
    Limit: pageSize,
    ExclusiveStartKey: lastKey
  }));

  return {
    items: (result.Items as Order[]) || [],
    lastKey: result.LastEvaluatedKey
  };
}
Update Item
typescript
import { UpdateCommand } from '@aws-sdk/lib-dynamodb';

async function updateUser(userId: string, updates: Partial<Pick<User, 'name' | 'email'>>): Promise<User> {
  // Build update expression dynamically
  const updateParts: string[] = ['#updatedAt = :updatedAt'];
  const names: Record<string, string> = { '#updatedAt': 'updatedAt' };
  const values: Record<string, any> = { ':updatedAt': new Date().toISOString() };

  if (updates.name !== undefined) {
    updateParts.push('#name = :name');
    names['#name'] = 'name';
    values[':name'] = updates.name;
  }

  if (updates.email !== undefined) {
    updateParts.push('#email = :email');
    names['#email'] = 'email';
    values[':email'] = updates.email;
  }

  const result = await docClient.send(new UpdateCommand({
    TableName: TABLE_NAME,
    Key: keys.user(userId),
    UpdateExpression: `SET ${updateParts.join(', ')}`,
    ExpressionAttributeNames: names,
    ExpressionAttributeValues: values,
    ReturnValues: 'ALL_NEW',
    ConditionExpression: 'attribute_exists(PK)'  // Must exist
  }));

  return result.Attributes as User;
}

// Atomic counter increment
async function incrementOrderCount(userId: string): Promise<void> {
  await docClient.send(new UpdateCommand({
    TableName: TABLE_NAME,
    Key: keys.user(userId),
    UpdateExpression: 'SET orderCount = if_not_exists(orderCount, :zero) + :inc',
    ExpressionAttributeValues: {
      ':zero': 0,
      ':inc': 1
    }
  }));
}
Delete Item
typescript
import { DeleteCommand } from '@aws-sdk/lib-dynamodb';

async function deleteUser(userId: string): Promise<void> {
  await docClient.send(new DeleteCommand({
    TableName: TABLE_NAME,
    Key: keys.user(userId),
    ConditionExpression: 'attribute_exists(PK)'
  }));
}

Batch Operations

Batch Write (Up to 25 items)
typescript
import { BatchWriteCommand } from '@aws-sdk/lib-dynamodb';

async function batchCreateItems(items: BaseItem[]): Promise<void> {
  // DynamoDB allows max 25 items per batch
  const chunks = [];
  for (let i = 0; i < items.length; i += 25) {
    chunks.push(items.slice(i, i + 25));
  }

  for (const chunk of chunks) {
    await docClient.send(new BatchWriteCommand({
      RequestItems: {
        [TABLE_NAME]: chunk.map(item => ({
          PutRequest: { Item: item }
        }))
      }
    }));
  }
}
Batch Get (Up to 100 items)
typescript
import { BatchGetCommand } from '@aws-sdk/lib-dynamodb';

async function batchGetUsers(userIds: string[]): Promise<User[]> {
  const result = await docClient.send(new BatchGetCommand({
    RequestItems: {
      [TABLE_NAME]: {
        Keys: userIds.map(id => keys.user(id))
      }
    }
  }));

  return (result.Responses?.[TABLE_NAME] as User[]) || [];
}

Transactions

TransactWrite (Atomic Multi-Item)
typescript
import { TransactWriteCommand } from '@aws-sdk/lib-dynamodb';

async function createOrderWithItems(
  userId: string,
  orderId: string,
  orderData: { total: number },
  items: { productId: string; quantity: number }[]
): Promise<void> {
  const now = new Date().toISOString();

  const transactItems = [
    // Create order
    {
      Put: {
        TableName: TABLE_NAME,
        Item: {
          ...keys.order(userId, orderId),
          EntityType: 'Order',
          orderId,
          userId,
          total: orderData.total,
          status: 'pending',
          createdAt: now,
          updatedAt: now
        },
        ConditionExpression: 'attribute_not_exists(PK)'
      }
    },
    // Update user's order count
    {
      Update: {
        TableName: TABLE_NAME,
        Key: keys.user(userId),
        UpdateExpression: 'SET orderCount = if_not_exists(orderCount, :zero) + :inc',
        ExpressionAttributeValues: { ':zero': 0, ':inc': 1 }
      }
    },
    // Add order items
    ...items.map((item, index) => ({
      Put: {
        TableName: TABLE_NAME,
        Item: {
          PK: `ORDER#${orderId}`,
          SK: `ITEM#${index}`,
          GSI1PK: `ORDER#${orderId}`,
          GSI1SK: `ITEM#${index}`,
          EntityType: 'OrderItem',
          productId: item.productId,
          quantity: item.quantity,
          createdAt: now
        }
      }
    }))
  ];

  await docClient.send(new TransactWriteCommand({
    TransactItems: transactItems
  }));
}

GSI Patterns

Sparse Index
typescript
// Only items with GSI1PK attribute appear in the index
// Useful for "featured" or "flagged" items

// Featured products (only some products have GSI1PK)
{ PK: 'PROD#1', SK: 'PRODUCT', GSI1PK: 'FEATURED', GSI1SK: 'PROD#1', ... }  // In index
{ PK: 'PROD#2', SK: 'PRODUCT', ... }  // Not in index (no GSI1PK)

// Query featured products
const featured = await docClient.send(new QueryCommand({
  TableName: TABLE_NAME,
  IndexName: 'GSI1',
  KeyConditionExpression: 'GSI1PK = :pk',
  ExpressionAttributeValues: { ':pk': 'FEATURED' }
}));
Inverted Index (GSI)
typescript
// Main table: User -> Orders (PK=USER#, SK=ORDER#)
// GSI: Orders by status (GSI1PK=STATUS#, GSI1SK=ORDER#)

{ PK: 'USER#123', SK: 'ORDER#001', GSI1PK: 'STATUS#pending', GSI1SK: 'ORDER#001', ... }
{ PK: 'USER#456', SK: 'ORDER#002', GSI1PK: 'STATUS#shipped', GSI1SK: 'ORDER#002', ... }

// Get all pending orders across all users
const pending = await docClient.send(new QueryCommand({
  TableName: TABLE_NAME,
  IndexName: 'GSI1',
  KeyConditionExpression: 'GSI1PK = :pk',
  ExpressionAttributeValues: { ':pk': 'STATUS#pending' }
}));
Multi-Attribute Composite Keys (Nov 2025+)
typescript
// New feature: Up to 4 attributes per partition/sort key
// No more synthetic keys like "TOURNAMENT#WINTER2024#REGION#NA-EAST"

// Table definition (IaC)
const table = {
  AttributeDefinitions: [
    { AttributeName: 'tournament', AttributeType: 'S' },
    { AttributeName: 'region', AttributeType: 'S' },
    { AttributeName: 'score', AttributeType: 'N' }
  ],
  GlobalSecondaryIndexes: [{
    IndexName: 'TournamentRegionIndex',
    KeySchema: [
      { AttributeName: 'tournament', KeyType: 'HASH' },  // Composite PK part 1
      { AttributeName: 'region', KeyType: 'HASH' },      // Composite PK part 2
      { AttributeName: 'score', KeyType: 'RANGE' }
    ]
  }]
};

Python (boto3)

Setup
python
# requirements.txt
boto3>=1.34.0

# db.py
import boto3
from boto3.dynamodb.conditions import Key, Attr
import os

dynamodb = boto3.resource(
    'dynamodb',
    region_name=os.getenv('AWS_REGION', 'us-east-1'),
    endpoint_url=os.getenv('DYNAMODB_LOCAL_ENDPOINT')  # For local dev
)

table = dynamodb.Table(os.getenv('DYNAMODB_TABLE', 'MyTable'))
Operations
python
from datetime import datetime
from typing import Optional, List
from decimal import Decimal

def create_user(user_id: str, email: str, name: str) -> dict:
    now = datetime.utcnow().isoformat()
    item = {
        'PK': f'USER#{user_id}',
        'SK': 'PROFILE',
        'EntityType': 'User',
        'userId': user_id,
        'email': email,
        'name': name,
        'createdAt': now,
        'updatedAt': now
    }

    table.put_item(
        Item=item,
        ConditionExpression='attribute_not_exists(PK)'
    )
    return item


def get_user(user_id: str) -> Optional[dict]:
    response = table.get_item(
        Key={'PK': f'USER#{user_id}', 'SK': 'PROFILE'}
    )
    return response.get('Item')


def get_user_orders(user_id: str) -> List[dict]:
    response = table.query(
        KeyConditionExpression=Key('PK').eq(f'USER#{user_id}') & Key('SK').begins_with('ORDER#'),
        ScanIndexForward=False
    )
    return response.get('Items', [])


def update_user(user_id: str, **updates) -> dict:
    update_parts = ['#updatedAt = :updatedAt']
    names = {'#updatedAt': 'updatedAt'}
    values = {':updatedAt': datetime.utcnow().isoformat()}

    for key, value in updates.items():
        update_parts.append(f'#{key} = :{key}')
        names[f'#{key}'] = key
        values[f':{key}'] = value

    response = table.update_item(
        Key={'PK': f'USER#{user_id}', 'SK': 'PROFILE'},
        UpdateExpression=f'SET {", ".join(update_parts)}',
        ExpressionAttributeNames=names,
        ExpressionAttributeValues=values,
        ReturnValues='ALL_NEW'
    )
    return response['Attributes']


def delete_user(user_id: str) -> None:
    table.delete_item(
        Key={'PK': f'USER#{user_id}', 'SK': 'PROFILE'}
    )

Local Development

DynamoDB Local
bash
# Docker
docker run -d -p 8000:8000 amazon/dynamodb-local

# Create table locally
aws dynamodb create-table \
  --endpoint-url http://localhost:8000 \
  --table-name MyTable \
  --attribute-definitions \
    AttributeName=PK,AttributeType=S \
    AttributeName=SK,AttributeType=S \
    AttributeName=GSI1PK,AttributeType=S \
    AttributeName=GSI1SK,AttributeType=S \
  --key-schema \
    AttributeName=PK,KeyType=HASH \
    AttributeName=SK,KeyType=RANGE \
  --global-secondary-indexes \
    'IndexName=GSI1,KeySchema=[{AttributeName=GSI1PK,KeyType=HASH},{AttributeName=GSI1SK,KeyType=RANGE}],Projection={ProjectionType=ALL}' \
  --billing-mode PAY_PER_REQUEST
NoSQL Workbench

AWS provides NoSQL Workbench for visual data modeling and querying.


CLI Quick Reference

bash
# Table operations
aws dynamodb create-table --cli-input-json file://table.json
aws dynamodb describe-table --table-name MyTable
aws dynamodb delete-table --table-name MyTable

# Item operations
aws dynamodb put-item --table-name MyTable --item '{"PK":{"S":"USER#1"},"SK":{"S":"PROFILE"}}'
aws dynamodb get-item --table-name MyTable --key '{"PK":{"S":"USER#1"},"SK":{"S":"PROFILE"}}'
aws dynamodb delete-item --table-name MyTable --key '{"PK":{"S":"USER#1"},"SK":{"S":"PROFILE"}}'

# Query
aws dynamodb query --table-name MyTable \
  --key-condition-expression "PK = :pk" \
  --expression-attribute-values '{":pk":{"S":"USER#1"}}'

# Scan (avoid in production)
aws dynamodb scan --table-name MyTable --limit 10

Anti-Patterns

  • Scan operations - Always use Query with proper key conditions
  • Hot partitions - Distribute writes with high-cardinality partition keys
  • Large items - Keep items under 400KB; use S3 for large data
  • Too many GSIs - Each GSI duplicates data; design carefully
  • Ignoring capacity - Monitor consumed capacity, use on-demand for variable loads
  • No condition expressions - Always validate with ConditionExpression
  • Fetching all attributes - Use ProjectionExpression to limit data
  • Multi-table design without reason - Single-table is preferred unless access patterns don't overlap

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

Files

Just SKILL.md in skills/aws-dynamodb of alinaqi/maggy.

Open the folder on GitHubat commit 72a456e

Compare with similar skills

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    AI Engine Optimization - semantic triples, page templates, content clusters for AI citations

    707 GitHub stars~3.7k tokensUpdated 15 days ago
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  • Agent Teams

    alinaqi/maggy

    Claude Code Agent Teams - default team-based development with strict TDD pipeline enforcement

    707 GitHub stars~5k tokensUpdated 15 days ago
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  • AI Models

    alinaqi/maggy

    Latest AI models reference - Claude, OpenAI, Gemini, Eleven Labs, Replicate

    707 GitHub stars~4.1k tokensUpdated 15 days ago
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  • Android Java

    alinaqi/maggy

    Android Java development with MVVM, ViewBinding, and Espresso testing

    707 GitHub stars~3.9k tokensUpdated 15 days ago
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  • Android Kotlin

    alinaqi/maggy

    Android Kotlin development with Coroutines, Jetpack Compose, Hilt, and MockK testing

    707 GitHub stars~3k tokensUpdated 15 days ago
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  • Autonomous Testing

    alinaqi/maggy

    AI-driven testing agent that auto-discovers, generates, executes, evaluates, and fixes tests for any project type

    707 GitHub stars~1.1k tokensUpdated 15 days ago
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Categories

Questions about AWS Dynamodb

What does AWS Dynamodb do?

AWS DynamoDB single-table design, GSI patterns, SDK v3 TypeScript/Python. AWS Dynamodb is an agent skill from alinaqi/maggy.

When should I use AWS Dynamodb?

AWS Dynamodb fits situations like: tasks that involve NoSQL databases.

How do I install AWS Dynamodb in Claude Code?

Run `npx skills add alinaqi/maggy --skill aws-dynamodb -a claude-code`. Or copy the skill folder (skills/aws-dynamodb in alinaqi/maggy) into .claude/skills/aws-dynamodb in your project. Claude Code loads it when a task matches its description.

How do I install AWS Dynamodb in Codex?

Run `npx skills add alinaqi/maggy --skill aws-dynamodb -a codex`. Or copy the skill folder (skills/aws-dynamodb in alinaqi/maggy) into .agents/skills/aws-dynamodb in your project. Codex loads it when a task matches its description.

Can I use AWS Dynamodb in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add alinaqi/maggy --skill aws-dynamodb -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aws-dynamodb, .gemini/skills/aws-dynamodb, .github/skills/aws-dynamodb and .opencode/skills/aws-dynamodb in your project.

What does AWS Dynamodb need to run?

Going by SKILL.md and its folder, AWS Dynamodb needs the command-line tools its instructions call (aws, npm and docker). Our summary lists: Python 3; Node.js.

Does AWS Dynamodb access the network?

SKILL.md names 2 domains. As links in the text: docs.aws.amazon.com and aws.amazon.com. This is read from the text; nothing was executed.

Is AWS Dynamodb safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does AWS Dynamodb use?

AWS Dynamodb is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does AWS Dynamodb use?

About 4.6k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to AWS Dynamodb?

Skills that share tags, products or a category with AWS Dynamodb: Implement (dynamodb-toolbox/dynamodb-toolbox, 2k stars), Plan (dynamodb-toolbox/dynamodb-toolbox, 2k stars), Spec (dynamodb-toolbox/dynamodb-toolbox, 2k stars) and AWS SDK Python Usage (aws/agent-toolkit-for-aws, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains AWS Dynamodb?

alinaqi (a GitHub user) maintains it in alinaqi/maggy, which has 707 GitHub stars. The repository holds 71 skills in this directory. The repository was last updated on September 24, 2026.

Source: alinaqi/maggy on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.