aws-sdk-js-v3-usage
AWS SDK for JavaScript v3 development patterns. Use when writing JavaScript or TypeScript code that uses AWS services via @aws-sdk/ packages (aws-sdk-js-v3), or when asked about schemas, runtime validation, serialization, or code generation in the context of the JS/TS AWS SDK.
- Installs
- 8K
- Last 24h
- +49
- Trending rank
- #3431
- Security
- Pass
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/aws/agent-toolkit-for-aws --skill aws-sdk-js-v3-usage- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads aws-sdk-js-v3-usage automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
Security audits
Independent scans of the skill's instructions and bundled files.
SKILL.md
The instructions your agent reads when the skill is triggered.
Do not use emojis in any code, comments, or output when this skill is active.
AWS SDK for JavaScript v3
Package Structure
@aws-sdk/client-*— one per service, generated by smithy-typescript; one-to-one with AWS services and operations@aws-sdk/lib-*— higher-level helpers (e.g.lib-dynamodb,lib-storage)@aws-sdk/*(no prefix) — utility packages (mostly internal; don't import deep paths)
Always import from the package root:
import { S3Client } from "@aws-sdk/client-s3"; // correct
// NOT: import { S3Client } from "@aws-sdk/client-s3/dist-cjs/S3Client"
Two Client Styles
Bare-bones (preferred — smaller bundle):
import { S3Client, GetObjectCommand } from "@aws-sdk/client-s3";
const client = new S3Client({ region: "us-east-1" });
const output = await client.send(new GetObjectCommand({ Bucket: "b", Key: "k" }));
Aggregated (v2-style but NOT v2, larger bundle):
import { S3 } from "@aws-sdk/client-s3";
const client = new S3({ region: "us-east-1" });
const output = await client.getObject({ Bucket: "b", Key: "k" });
Client Configuration
No global config in v3 — pass config to each client. region is always required; set it explicitly or via AWS_REGION env var.
const config = { region: "us-east-1", maxAttempts: 5 };
const s3 = new S3Client(config);
const dynamo = new DynamoDBClient(config);
Do not read or mutate client.config after instantiation — it is a resolved form (e.g. region becomes an async function). See references/effective-practices.md.
For HTTP handler (NodeHttpHandler from @smithy/node-http-handler), retry strategy, endpoint details, logging, FIPS, dual-stack, protocol selection, and S3-specific options → see references/clients.md.
Credentials
All providers from @aws-sdk/credential-providers. Credentials are lazy and cached per client until ~5 min before expiry.
// Default chain (env → ini → IMDS/ECS) — use in most Node.js apps
const client = new S3Client({ credentials: fromNodeProviderChain() });
// Assume role (NOTE: fromTemporaryCredentials is correct for STS AssumeRole)
const client = new S3Client({
credentials: fromTemporaryCredentials({ params: { RoleArn: "arn:aws:iam::123456789012:role/MyRole" } }),
});
// Named profile
const client = new S3Client({ profile: "my-profile" });
Share credentials and socket pool across multi-region clients:
const east = new S3Client({ region: "us-east-1" });
const { credentials, requestHandler } = east.config;
const west = new S3Client({ region: "us-west-2", credentials, requestHandler });
For all providers (Cognito, SSO, web identity, custom chains, STS region priority) → see references/credentials.md.
Streams (e.g. S3 GetObject Body)
Always read or discard streaming responses — unread streams leave sockets open (socket exhaustion):
const { Body } = await client.send(new GetObjectCommand({ Bucket: "b", Key: "k" }));
const str = await Body.transformToString(); // read as string
const bytes = await Body.transformToByteArray(); // read as Uint8Array
// or discard:
await (Body.destroy?.() ?? Body.cancel?.());
Streams can only be read once.
Paginators
Use paginate* functions instead of manual token handling:
import { DynamoDBClient, paginateListTables } from "@aws-sdk/client-dynamodb";
const client = new DynamoDBClient({});
const tableNames = [];
for await (const page of paginateListTables({ client }, {})) {
// page contains a single paginated output.
tableNames.push(...page.TableNames);
}
DynamoDB DocumentClient
Use @aws-sdk/lib-dynamodb to work with native JS types instead of AttributeValues:
import { DynamoDBClient } from "@aws-sdk/client-dynamodb";
import { DynamoDBDocumentClient, GetCommand, PutCommand } from "@aws-sdk/lib-dynamodb";
const client = DynamoDBDocumentClient.from(new DynamoDBClient({}));
await client.send(new PutCommand({ TableName: "T", Item: { id: "1", name: "Alice" } }));
const { Item } = await client.send(new GetCommand({ TableName: "T", Key: { id: "1" } }));
For marshall options, large numbers (NumberValue), pagination, and aggregated client → see references/dynamodb.md.
S3: Presigned URLs, Multipart Upload, Waiters
// Presigned GET URL
import { getSignedUrl } from "@aws-sdk/s3-request-presigner";
const url = await getSignedUrl(client, new GetObjectCommand({ Bucket: "b", Key: "k" }), { expiresIn: 3600 });
// Multipart upload (large files / streams)
import { Upload } from "@aws-sdk/lib-storage";
const upload = new Upload({ client, params: { Bucket: "b", Key: "k", Body: stream } });
await upload.done();
// Waiters
import { waitUntilObjectExists } from "@aws-sdk/client-s3";
await waitUntilObjectExists({ client, maxWaitTime: 120 }, { Bucket: "b", Key: "k" });
For presigned POST, signed headers, waiter options → see references/s3.md.
Error Handling
import { S3ServiceException } from "@aws-sdk/client-s3";
try {
await client.send(new GetObjectCommand({ Bucket: "b", Key: "k" }));
} catch (e) {
if (e?.$metadata) {
// SDK service error — has $metadata.httpStatusCode, e.name, e.$response
console.error(e.name, e.$metadata.httpStatusCode);
}
}
Check e.name or instanceof for specific error types. See references/error-handling.md for full patterns.
For runtime validation, serialization to non-default formats, or questions about what schemas are in jsv3 → see references/schemas.md.
Performance: Parallel Workloads
// Configure maxSockets to match your parallel batch size
const client = new S3Client({
requestHandler: { httpsAgent: { maxSockets: 50 } },
cacheMiddleware: true, // skip if using custom middleware
});
Streaming deadlock warning: with limited sockets, don't await the request and stream body separately — chain them. See references/performance.md.
Middleware
Add custom logic to all commands on a client:
client.middlewareStack.add(
(next, context) => async (args) => {
console.log(context.commandName, args.input);
const result = await next(args);
return result;
},
{ name: "MyMiddleware", step: "build", override: true }
);
Steps (in order): initialize → serialize → build → finalizeRequest → deserialize
Abort Controller
const { AbortController } = require("@aws-sdk/abort-controller");
const { S3Client, CreateBucketCommand } = require("@aws-sdk/client-s3");
const abortController = new AbortController();
const client = new S3Client(clientParams);
const requestPromise = client.send(new CreateBucketCommand(commandParams), {
abortSignal: abortController.signal,
});
// The request will not be created if abortSignal is already aborted.
// The request will be destroyed if abortSignal is aborted before response is returned.
abortController.abort();
// This will fail with "AbortError" as abortSignal is aborted.
await requestPromise;
Lambda Best Practices
Initialize clients outside the handler (container reuse), make API calls inside. For one-time async setup, use a lazy init flag inside the handler:
import { S3Client } from "@aws-sdk/client-s3";
const client = new S3Client({}); // outside — reused across invocations
let ready = false;
export const handler = async (event) => {
if (!ready) { await prepare(); ready = true; } // lazy one-time setup inside handler
// ... API calls here
};
See references/lambda.md for Lambda layers and versioning.
Node.js Version Requirements
- v3.968.0+ requires Node.js >= 20
- v3.723.0+ requires Node.js >= 18
TypeScript
Response fields are typed as T | undefined by default. Use AssertiveClient from @smithy/types to remove | undefined, or NodeJsClient / BrowserClient to narrow streaming blob types. See references/typescript.md.
SigV4a (S3 Multi-Region Access Points)
S3 MRAP and certain other features require SigV4a. You must install and side-effect-import exactly one of:
@aws-sdk/signature-v4-crt— Node.js only, better performance@aws-sdk/signature-v4a— Node.js + browsers, pure JS
import "@aws-sdk/signature-v4a"; // side-effect only — no exported values needed
See references/sigv4a.md for full details and MRAP ARN format.
FAQ
What does the aws-sdk-js-v3-usage skill do?
AWS SDK for JavaScript v3 development patterns. Use when writing JavaScript or TypeScript code that uses AWS services via @aws-sdk/ packages (aws-sdk-js-v3), or when asked about schemas, runtime validation, serialization, or code generation in the context of the JS/TS AWS SDK.
How do I install aws-sdk-js-v3-usage?
Run npx skills add https://github.com/aws/agent-toolkit-for-aws --skill aws-sdk-js-v3-usage in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/aws-sdk-js-v3-usage/ (personal) or .claude/skills/aws-sdk-js-v3-usage/ (project).
Which AI agents can use aws-sdk-js-v3-usage?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is aws-sdk-js-v3-usage safe to install?
Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk passed. As with any skill, read the SKILL.md and bundled scripts before installing.
Who maintains aws-sdk-js-v3-usage?
It is published by aws in aws/agent-toolkit-for-aws, and it is an official skill from the maker of the technology it covers. It has 8,044 recorded installs.
More from aws/agent-toolkit-for-aws
aws-iam
aws/agent-toolkit-for-aws
Provides verified corrections for IAM behaviors that AI agents frequently get wrong — policy evaluation edge cases, trust policy gotchas, STS session limits, Organizations quirks, and SAML/MFA specifics. Also provides structured workflows for IAM role management and baseline policy generation from application source code or a Terraform plan JSON. Covers condition operator safety (ForAnyValue/ForAllValues with Null checks), bucket policy deny patterns (VPC endpoint restrictions, org paths), confused deputy protection, and service role creation for AWS services (Glue, CloudTrail, Lambda, ECS, etc.) with aws:SourceAccount/aws:SourceArn trust conditions. Applies when creating IAM roles, writing IAM or bucket policies, generating policies from application source code or a Terraform plan JSON, working with STS, Organizations, or condition operators, or any task needing a service or execution role. Does not cover non-IAM authorization like Cognito user-pool policies or app-level RBAC.
aws-serverless
aws/agent-toolkit-for-aws
Routes serverless requests to a compute form factor and the skill that owns it. Applies first to Lambda, API Gateway, EventBridge, Step Functions and event-driven work while the compute, orchestration or integration choice is open — API backends, webhooks, jobs, cron, queue/stream consumers, durable workflows, event routing, Step Functions vs Durable Functions, and Pipes vs native event source mappings for queues and streams. Decides Event Functions on-demand vs Managed Instances, Web Functions, MicroVMs, EventBridge rules/Scheduler/Pipes/bus, HTTP vs REST API. Owns shared Lambda references (cold starts, SnapStart, concurrency, event sources, function URLs, throttling, troubleshooting). Defers to the specialized skill once a request commits to one form factor or service, or describes its defining feature, even unnamed (durable checkpointing and automatic step retries, Firecracker sandbox, managed instances, Node.js server). Not for EC2, ECS/EKS/Fargate or Amplify hosting.
aws-observability
aws/agent-toolkit-for-aws
Builds, configures, debugs, and optimizes AWS observability - operator-symptom questions and detecting Omni vs classic CloudWatch. CloudWatch on an already-reporting service: Log Insights, metric/composite/anomaly alarms, custom metrics/EMF, dashboards, X-Ray/ADOT tracing, canaries, CloudTrail, Dynamic Instrumentation (live breakpoints/snapshots), the Application Signals service map, and fleet health views. CloudWatch Omni on an existing Space: SQL over logs and traces, PromQL over metrics, Omni dashboards, Omni alerts, context graph for root cause, programmatic/IaC access (API/SDK/CLI/CloudFormation), driving Omni from a coding agent or skills, and evaluating AI agent quality from traces - on-demand and online scoring of live traffic, readback, custom evaluators. For first-time setup - creating an Omni Space, granting access, ingestion, or ADOT instrumentation for Application Signals (ServiceEvents, CI/CD metadata) or Omni - use setting-up-cloudwatch-observability. Not for app logging
aws-cdk
aws/agent-toolkit-for-aws
Authors, deploys, and troubleshoots AWS infrastructure using CDK with TypeScript or Python. Covers best practices, stack architecture, and construct patterns. Applies when writing CDK constructs, bootstrapping environments, running cdk deploy/synth/diff, fixing CDK or CloudFormation errors, planning stack structure, importing existing resources, resolving drift, or refactoring stacks without resource replacement.
aws-containers
aws/agent-toolkit-for-aws
Builds and deploys containerized workloads on Elastic Kubernetes Service (EKS), Elastic Container Service (ECS), Fargate, and ECR (Elastic Container Registry). Covers general EKS knowledge, Karpenter, AWS Load Balancer Controller and leveraging various open source Kubernetes projects with EKS. Covers general ECS knowledge, task definitions, Fargate services, ECS Exec, ECS Express Mode and ECS Managed Instances. Covers general Elastic Beanstalk knowledge, Elastic Beanstalk configuration and platforms supported by Elastic Beanstalk. Covers general ECR knowledge, ECR repository setup and lifecycle policies. Includes recommending, enabling, and reading Amazon ECS Action Logs to troubleshoot control-plane failures (deployment rollback/circuit-breaker, task placement, scaling, task replacement). Applies when deploying, debugging, or optimizing containers on AWS. Should be used instead of relying on internal knowledge for these services.
aws-billing-and-cost-management
aws/agent-toolkit-for-aws
Analyze AWS costs, find savings, manage budgets, evaluate Savings Plans and Reserved Instances, right-size EC2/Lambda/RDS/EBS with Compute Optimizer, look up service pricing, query CUR with Athena, detect cost anomalies, scope costs to billing views, and monitor Free Tier usage. Triggers on: AWS bill, cost analysis, reduce spend, savings plan, reserved instance, right-size, budget alert, cost optimization, pricing, free tier, cost anomaly, CUR, cost audit, billing view, billing view ARN.
Popular devops & cloud skills
microsoft-foundry
microsoft/azure-skills
Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, managed harness agent create, GitHub Copilot harness agent, create agent, update agent, add tool to agent, invoke agent, agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure
azure-diagnostics
microsoft/azure-skills
Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead letter.
azure-prepare
microsoft/azure-skills
Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.
azure-ai
microsoft/azure-skills
Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
azure-deploy
microsoft/azure-skills
Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.
azure-validate
microsoft/azure-skills
Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.