Aws Sdk Python Usage

This one loads when you import boto3 or botocore, giving Claude the patterns for AWS SDK Python development. It covers the client versus resource decision (which matters more than you'd think, especially for DynamoDB), proper error handling with typed exceptions instead of string matching on ClientError, pagination with JMESPath searches, and service-specific APIs for S3 and DynamoDB. The most useful bit is probably the insistence on letting exceptions propagate instead of catching and swallowing them, and keeping sys.exit calls out of business logic. Solid for anyone writing AWS automation scripts or Lambda functions in Python.

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last updated: Aug 21, 2026

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Install

$ npx -y skills add aws/agent-toolkit-for-aws --skill aws-sdk-python-usage --agent claude-code

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AWS SDK for Python (boto3)

boto3 is the high-level Python SDK for AWS. It wraps botocore (the low-level SDK) and provides two distinct interfaces: clients (low-level, 1:1 API mapping) and resources (high-level, object-oriented). Understanding which to use and when is essential.

Client vs Resource

Clients map directly to AWS service APIs. Every service has a client. Responses are plain dicts.

Resources provide an object-oriented interface with attributes and actions. Only some services have resources (S3, DynamoDB, EC2, IAM, SQS, SNS, CloudFormation, CloudWatch, Glacier). Resources auto-marshal types (especially useful for DynamoDB).

import boto3

# Client - low-level, all services
s3_client = boto3.client("s3")
response = s3_client.list_buckets()
buckets = response["Buckets"]  # plain dicts

# Resource - high-level, select services
s3_resource = boto3.resource("s3")
for bucket in s3_resource.buckets.all():
    print(bucket.name)  # attribute access, not dict keys

SKILL.md on GitHub

Details

Repository: github.com/aws/agent-toolkit-for-aws
Categories: Documentation, AI & Agent Building, Python, Cloud & Infrastructure, Databases
First seen: May 16, 2026