/dynamodb-toolbox-patterns
Provides TypeScript patterns for DynamoDB-Toolbox v2 including schema/table/entity modeling, .build() command workflow, query/scan access patterns, batch and transaction operations, and single-table design with computed keys. Use when implementing type-safe DynamoDB access
$ npx -y skills add giuseppe-trisciuoglio/developer-kit --skill dynamodb-toolbox-patterns --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/dynamodb-toolbox-patterns
Context preview
The summary Claude sees to decide when to auto-load this skill.
Provides TypeScript patterns for DynamoDB-Toolbox v2 including schema/table/entity modeling, .build() command workflow, query/scan access patterns, batch and transaction operations, and single-table design with computed keys. Use when implementing type-safe DynamoDB access
SKILL.md
dynamodb-toolbox-patterns.SKILL.mdname: dynamodb-toolbox-patterns
description: Provides TypeScript patterns for DynamoDB-Toolbox v2 including schema/table/entity modeling, .build() command workflow, query/scan access patterns, batch and transaction operations, and single-table design with computed keys. Use when implementing type-safe DynamoDB access layers with DynamoDB-Toolbox v2 in TypeScript services or serverless applications.
allowed-tools: Read, Write, Edit, Glob, Grep, Bash
DynamoDB-Toolbox v2 Patterns (TypeScript)
Overview
This skill provides practical TypeScript patterns for using DynamoDB-Toolbox v2 with AWS SDK v3 DocumentClient. It focuses on type-safe schema modeling, `.build()` command usage, and production-ready single-table design.
When to Use
- Defining DynamoDB tables and entities with strict TypeScript inference
- Modeling schemas with `item`, `string`, `number`, `list`, `set`, `map`, and `record`
- Implementing `GetItem`, `PutItem`, `UpdateItem`, `DeleteItem` via `.build()`
- Building query and scan access paths with primary keys and GSIs
- Handling batch and transactional operations
- Designing single-table systems with computed keys and entity patterns
Instructions
1. **Start from access patterns**: identify read/write queries first, then design keys. 2. **Create table + entity boundaries**: one table, multiple entities if using single-table design. 3. **Define schemas with constraints**: apply `.key()`, `.required()`, `.default()`, `.transform()`, `.link()`. 4. **Use `.build()` commands everywhere**: avoid ad-hoc command construction for consistency and type safety. 5. **Add query/index coverage**: validate GSI/LSI paths for each required access pattern. 6. **Use batch/transactions intentionally**: batch for throughput, transactions for atomicity. 7. **Keep items evolvable**: use optional fields, defaults, and derived attributes for schema evolution.
Examples
Install and Setup
npm install dynamodb-toolbox @aws-sdk/client-dynamodb @aws-sdk/lib-dynamodb
import { DynamoDBClient } from '@aws-sdk/client-dynamodb';
import { DynamoDBDocumentClient } from '@aws-sdk/lib-dynamodb';
import { Table } from 'dynamodb-toolbox/table';
import { Entity } from 'dynamodb-toolbox/entity';
import { item, string, number, list, map } from 'dynamodb-toolbox/schema';
const client = new DynamoDBClient({ region: process.env.AWS_REGION ?? 'eu-west-1' });
const documentClient = DynamoDBDocumentClient.from(client);
export const AppTable = new Table({
name: 'app-single-table',
partitionKey: { name: 'PK', type: 'string' },
sortKey: { name: 'SK', type: 'string' },
indexes: {
byType: { type: 'global', partitionKey: { name: 'GSI1PK', type: 'string' }, sortKey: { name: 'GSI1SK', type: 'string' } }
},
documentClient
});Entity Schema with Modifiers and Complex Attributes
const now = () => new Date().toISOString();
export const UserEntity = new Entity({
name: 'User',
table: AppTable,
schema: item({
tenantId: string().required('always'),
userId: string().required('always'),
email: string().required('always').transform(input => input.toLowerCase()),
role: string().enum('admin', 'member').default('member'),
loginCount: number().default(0),
tags: list(string()).default([]),
profile: map({
displayName: string().optional(),
timezone: string().default('UTC')
}).default({ timezone: 'UTC' })
}),
computeKey: ({ tenantId, userId }) => ({
PK: `TENANT#${tenantId}`,
SK: `USER#${userId}`,
GSI1PK: `TENANT#${tenantId}#TYPE#USER`,
GSI1SK: `EMAIL#${userId}`
})
});`.build()` CRUD Commands
import { PutItemCommand } from 'dynamodb-toolbox/entity/actions/put';
import { GetItemCommand } from 'dynamodb-toolbox/entity/actions/get';
import { UpdateItemCommand, $add } from 'dynamodb-toolbox/entity/actions/update';
import { DeleteItemCommand } from 'dynamodb-toolbox/entity/actions/delete';
await UserEntity.build(PutItemCommand)
.item({ tenantId: 't1', userId: 'u1', email: 'A@Example.com' })
.send();
const { Item } = await UserEntity.build(GetItemCommand)
.key({ tenantId: 't1', userId: 'u1' })
.send();
await UserEntity.build(UpdateItemCommand)
.item({ tenantId: 't1', userId: 'u1', loginCount: $add(1) })
.send();
await UserEntity.build(DeleteItemCommand)
.key({ tenantId: 't1', userId: 'u1' })
.send();Query and Scan Patterns
import { QueryCommand } from 'dynamodb-toolbox/table/actions/query';
import { ScanCommand } from 'dynamodb-toolbox/table/actions/scan';
const byTenant = await AppTable.build(QueryCommand)
.query({
partition: `TENANT#t1`,
range: { beginsWith: 'USER#' }
})
.send();
const byTypeIndex = await AppTable.build(QueryCommand)
.query({
index: 'byType',
partition: 'TENANT#t1#TYPE#USER'
})
.options({ limit: 25 })
.send();
const scanned = await AppTable.build(ScanCommand)
.options({ limit: 100 })
.send();Batch and Transaction Workflows
import { BatchWriteCommand } from 'dynamodb-toolbox/table/actions/batchWrite';
import { TransactWriteCommand } from 'dynamodb-toolbox/table/actions/transactWrite';
await AppTable.build(BatchWriteCommand)
.requests(
UserEntity.build(PutItemCommand).item({ tenantId: 't1', userId: 'u2', email: 'u2@example.com' }),
UserEntity.build(PutItemCommand).item({ tenantId: 't1', userId: 'u3', email: 'u3@example.com' })
)
.send();
await AppTable.build(TransactWriteCommand)
.requests(
UserEntity.build(PutItemCommand).item({ tenantId: 't1', userId: 'u4', email: 'u4@example.com' }),
UserEntity.build(UpdateItemCommand).item({ tenantId: 't1', userId: 'u1', loginCount: $add(1) })
)
.send();Single-Table Design Guidance
- Model each business concept as an entity with strict schema.
- Keep PK/SK predictable and composable (`TENANT#`, `USER#`, `ORDER#`).
- Encode access paths into GSI keys, not in-memory fil
Read more
name: dynamodb-toolbox-patterns description: Provides TypeScript patterns for DynamoDB-Toolbox v2 including schema/table/entity modeling, .build() command workflow, query/scan access patterns, batch and transaction operations, and single-table design with computed keys. Use when implementing type-safe DynamoDB access layers with DynamoDB-Toolbox v2 in TypeScript services or serverless applications. allowed-tools: Read, Write, Edit, Glob, Grep, Bash
DynamoDB-Toolbox v2 Patterns (TypeScript)
Overview
This skill provides practical TypeScript patterns for using DynamoDB-Toolbox v2 with AWS SDK v3 DocumentClient. It focuses on type-safe schema modeling, `.build()` command usage, and production-ready single-table design.
When to Use
- Defining DynamoDB tables and entities with strict TypeScript inference
- Modeling schemas with `item`, `string`, `number`, `list`, `set`, `map`, and `record`
- Implementing `GetItem`, `PutItem`, `UpdateItem`, `DeleteItem` via `.build()`
- Building query and scan access paths with primary keys and GSIs
- Handling batch and transactional operations
- Designing single-table systems with computed keys and entity patterns
Instructions
1. **Start from access patterns**: identify read/write queries first, then design keys. 2. **Create table + entity boundaries**: one table, multiple entities if using single-table design. 3. **Define schemas with constraints**: apply `.key()`, `.required()`, `.default()`, `.transform()`, `.link()`. 4. **Use `.build()` commands everywhere**: avoid ad-hoc command construction for consistency and type safety. 5. **Add query/index coverage**: validate GSI/LSI paths for each required access pattern. 6. **Use batch/transactions intentionally**: batch for throughput, transactions for atomicity. 7. **Keep items evolvable**: use optional fields, defaults, and derived attributes for schema evolution.
Examples
Install and Setup
npm install dynamodb-toolbox @aws-sdk/client-dynamodb @aws-sdk/lib-dynamodb
import { DynamoDBClient } from '@aws-sdk/client-dynamodb';
import { DynamoDBDocumentClient } from '@aws-sdk/lib-dynamodb';
import { Table } from 'dynamodb-toolbox/table';
import { Entity } from 'dynamodb-toolbox/entity';
import { item, string, number, list, map } from 'dynamodb-toolbox/schema';
const client = new DynamoDBClient({ region: process.env.AWS_REGION ?? 'eu-west-1' });
const documentClient = DynamoDBDocumentClient.from(client);
export const AppTable = new Table({
name: 'app-single-table',
partitionKey: { name: 'PK', type: 'string' },
sortKey: { name: 'SK', type: 'string' },
indexes: {
byType: { type: 'global', partitionKey: { name: 'GSI1PK', type: 'string' }, sortKey: { name: 'GSI1SK', type: 'string' } }
},
documentClient
});Entity Schema with Modifiers and Complex Attributes
const now = () => new Date().toISOString();
export const UserEntity = new Entity({
name: 'User',
table: AppTable,
schema: item({
tenantId: string().required('always'),
userId: string().required('always'),
email: string().required('always').transform(input => input.toLowerCase()),
role: string().enum('admin', 'member').default('member'),
loginCount: number().default(0),
tags: list(string()).default([]),
profile: map({
displayName: string().optional(),
timezone: string().default('UTC')
}).default({ timezone: 'UTC' })
}),
computeKey: ({ tenantId, userId }) => ({
PK: `TENANT#${tenantId}`,
SK: `USER#${userId}`,
GSI1PK: `TENANT#${tenantId}#TYPE#USER`,
GSI1SK: `EMAIL#${userId}`
})
});`.build()` CRUD Commands
import { PutItemCommand } from 'dynamodb-toolbox/entity/actions/put';
import { GetItemCommand } from 'dynamodb-toolbox/entity/actions/get';
import { UpdateItemCommand, $add } from 'dynamodb-toolbox/entity/actions/update';
import { DeleteItemCommand } from 'dynamodb-toolbox/entity/actions/delete';
await UserEntity.build(PutItemCommand)
.item({ tenantId: 't1', userId: 'u1', email: 'A@Example.com' })
.send();
const { Item } = await UserEntity.build(GetItemCommand)
.key({ tenantId: 't1', userId: 'u1' })
.send();
await UserEntity.build(UpdateItemCommand)
.item({ tenantId: 't1', userId: 'u1', loginCount: $add(1) })
.send();
await UserEntity.build(DeleteItemCommand)
.key({ tenantId: 't1', userId: 'u1' })
.send();Query and Scan Patterns
import { QueryCommand } from 'dynamodb-toolbox/table/actions/query';
import { ScanCommand } from 'dynamodb-toolbox/table/actions/scan';
const byTenant = await AppTable.build(QueryCommand)
.query({
partition: `TENANT#t1`,
range: { beginsWith: 'USER#' }
})
.send();
const byTypeIndex = await AppTable.build(QueryCommand)
.query({
index: 'byType',
partition: 'TENANT#t1#TYPE#USER'
})
.options({ limit: 25 })
.send();
const scanned = await AppTable.build(ScanCommand)
.options({ limit: 100 })
.send();Batch and Transaction Workflows
import { BatchWriteCommand } from 'dynamodb-toolbox/table/actions/batchWrite';
import { TransactWriteCommand } from 'dynamodb-toolbox/table/actions/transactWrite';
await AppTable.build(BatchWriteCommand)
.requests(
UserEntity.build(PutItemCommand).item({ tenantId: 't1', userId: 'u2', email: 'u2@example.com' }),
UserEntity.build(PutItemCommand).item({ tenantId: 't1', userId: 'u3', email: 'u3@example.com' })
)
.send();
await AppTable.build(TransactWriteCommand)
.requests(
UserEntity.build(PutItemCommand).item({ tenantId: 't1', userId: 'u4', email: 'u4@example.com' }),
UserEntity.build(UpdateItemCommand).item({ tenantId: 't1', userId: 'u1', loginCount: $add(1) })
)
.send();Single-Table Design Guidance
- Model each business concept as an entity with strict schema.
- Keep PK/SK predictable and composable (`TENANT#`, `USER#`, `ORDER#`).
- Encode access paths into GSI keys, not in-memory fil
Showing the first part of this file.
Modular plugin marketplace for Claude Code and agentic CLIs, with validated, spec-driven skills, agents, commands, and workflows for Java, TypeScript, Python, PHP, AWS, and AI.
Repo: giuseppe-trisciuoglio/developer-kit
Other skills on developer-kit.
- /chunking-strategy
Provides chunking strategies for RAG systems. Generates chunk size recommendations (256-1024 tokens), overlap percentages (10-20%), and semantic boundary detection methods. Validates semantic coherence and evaluates retrieval precision/recall metrics. Use when building
Open skill - /prompt-engineering
Provides workflows to write, debug, and optimize prompts for LLMs, including few-shot example selection, chain-of-thought structuring, system prompt design, and template composition. Use when the user asks to write or improve a prompt, wants help with few-shot examples,
Open skill - /rag
Implements document chunking, embedding generation, vector storage, and retrieval pipelines for Retrieval-Augmented Generation systems. Use when building RAG applications, creating document Q&A systems, or integrating AI with knowledge bases.
Open skill - /aws-cloudformation-auto-scaling
Provides AWS CloudFormation patterns for Auto Scaling including EC2, ECS, and Lambda. Use when creating Auto Scaling groups, launch configurations, launch templates, scaling policies, lifecycle hooks, and predictive scaling. Covers template structure with Parameters, Outputs,
Open skill - /aws-cloudformation-bedrock
Provides AWS CloudFormation patterns for Amazon Bedrock resources including agents, knowledge bases, data sources, guardrails, prompts, flows, and inference profiles. Use when creating Bedrock agents with action groups, implementing RAG with knowledge bases, configuring vector
Open skill - /aws-cloudformation-cloudfront
Provides AWS CloudFormation patterns for CloudFront distributions, origins (ALB, S3, Lambda@Edge, VPC Origins), CacheBehaviors, Functions, SecurityHeaders, parameters, Outputs and cross-stack references. Use when creating CloudFront distributions with CloudFormation, configuring
Open skill

