What problem does it solve? Writing Python code against AWS services with boto3 often leads to subtle mistakes: wrong exception imports, manual pagination loops, raw AttributeValue dicts from DynamoDB, and unclosed S3 streaming bodies. This Skill provides authoritative patterns for clients, resources, sessions, error handling, pagination, waiters, and service-specific APIs so generated code follows AWS SDK best practices. ## Core Features & Use Cases - Client vs Resource Guidance: Choose between low-level clients and high-level resources, with correct session, credential, and profile configuration. - Error Handling & Resilience: Use typed client exceptions, botocore.config.Config retries and timeouts, paginators with JMESPath filtering, and waiters for resource state polling. - Service Deep Dives: Detailed references for S3 transfers and presigned URLs, and DynamoDB operations with automatic type marshalling via the resource interface. - Use Case: When asked to write a script that uploads files to S3 with progress callbacks and retries, or query a DynamoDB table with condition expressions, this Skill ensures the generated code uses upload_file with TransferConfig, Key/Attr condition builders, and proper exception handling. ## Quick Start Ask the assistant to write a Python script using boto3 that lists S3 objects with pagination and handles errors with typed exceptions.
