Defines AWS SAM infrastructure patterns and boto3 best practices for deploying Agno agents.
npx skills add https://github.com/allankltsn/setup_kiro --skill agno-aws-allankltsn
Please help me install this Agent Skill. Skill: agno-aws Source: https://github.com/allankltsn/setup_kiro/tree/main/.kiro/skills/agno-aws Command: npx skills add https://github.com/allankltsn/setup_kiro --skill agno-aws-allankltsn
template.yaml with Globals, arm64/Graviton, HTTP API, least-privilege SAM policy templates, and environment-based parameters. - Package Optimization: Moves heavy dependencies into Lambda Layers, excludes boto3 from the artifact, uses sam build --use-container, and strips tests and junk files. - boto3 Best Practices: Module-scoped reusable clients, explicit timeouts and adaptive retries via botocore Config, paginators, ClientError handling, and credential-chain-only authentication. - Use Case: When writing a new Lambda function that reads secrets from Secrets Manager and sessions from DynamoDB, apply this Skill to generate the SAM template with least-privilege policies and a shared boto3 client module that also works against LocalStack in development. ## Quick Start Ask the AI to model the agent's AWS infrastructure as a SAM template with least-privilege IAM and an optimized boto3 client layer following the agno-aws standards.High-intent search queries and answers about installing and using this skill.
Define all resources in a template.yaml using AWS::Serverless types with Globals for runtime, timeout, and memory, then run sam build --use-container and sam deploy. Store per-environment parameters in samconfig.toml for reproducible deployments.
Create boto3 clients once at module scope, outside the handler, so they are reused across invocations of the same container. Configure explicit timeouts and adaptive retries via botocore.config.Config, and never pass credentials in code.
No, boto3 and botocore already exist in the Lambda runtime, so exclude them from the package to keep the artifact small. Only bundle boto3 if you need a newer version than the runtime provides.
Move heavy dependencies into a Lambda Layer, exclude tests and cache files from CodeUri, pin versions in requirements.txt, and build with sam build --use-container. Tune MemorySize by profiling since more memory also increases CPU.
Yes, the same template runs against LocalStack in development by switching the endpoint via the AWS_ENDPOINT_URL environment variable. Production uses the Lambda role credential chain while LocalStack uses test credentials.
Use SAM policy templates like DynamoDBCrudPolicy or S3ReadPolicy scoped to specific resources, granting each function only the permissions it uses. Never use wildcards in Action or Resource, and reference secrets by ARN rather than embedding values.
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