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SDK Getting Started

AWS LabsOfficialPublished by AWS Labs

  • Skill
  • Tool integration
  • Cloud and DevOps
  • Apache-2.0
  • Low risk
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From the author

Validates the user's environment for SageMaker AI operations — checks SDK version, AWS region, and execution role. Use when the user says "set up", "getting started", "check my environment", "configure SDK", or as the first step in any plan involving SageMaker/Bedrock training, evaluation, or deployment.
— the description by AWS Labs

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill performs essential preflight checks to ensure the user's environment is correctly configured for SageMaker AI operations. It verifies the SageMaker Python SDK version, detects the active AWS region, and validates the IAM execution role's trust policies. By automating these checks, it ensures that downstream tasks like training, evaluation, or deployment have the necessary prerequisites in place, storing the validated configuration in the conversation context for later use.

What it does

  • Verifies the installed version of the SageMaker Python SDK.
  • Automatically detects the current AWS region.
  • Resolves and validates the IAM execution role ARN.
  • Checks IAM role trust policies for required service principals.
  • Reports environment status and configuration details.
  • Stores validated environment data for use by other agent skills.

When to use it

  • At the beginning of any SageMaker or Bedrock project.
  • When a user requests help setting up or configuring their SDK.
  • When troubleshooting environment-related issues in SageMaker.
  • As the first step in a multi-step plan involving AI model training or deployment.

Advantages

  • Prevents runtime failures by catching configuration issues early.
  • Reduces manual effort by programmatically detecting environment settings.
  • Ensures consistent environment state across different agent tasks.
  • Provides clear feedback on missing permissions or trust policy requirements.

Usage examples

“I want to get started with SageMaker. Can you help me set up?”
The agent will verify the SDK version, detect the AWS region, and validate the execution role, reporting the environment status.
“Check my environment for SageMaker training.”
The agent performs a preflight check to confirm the SDK is up to date and the IAM role has the necessary trust policies.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/awslabs/sdk-getting-started/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip sdk-getting-started.zip -d .agents/skills

Documentation by AWS Labs

SDK Getting Started

Preflight checks to verify the user's environment can run SageMaker AI operations. The agent runs these checks directly (no code generation) and stores results in conversation context for downstream skills.

Principles

  1. Don't ask for what you can look up. Resolve region and role programmatically before asking the user.

Workflow

Read and follow references/sagemaker-python-sdk-setup.md.

References

  • references/sagemaker-python-sdk-setup.md - SageMaker Python SDK version, region, and execution role checks

  • references/execution-role-setup.md — Execution role resolution and validation

Files

ATTRIBUTION.md

Attribution

This folder is an unmodified copy of the Agent Skill "sdk-getting-started", distributed by AutoGineer (https://autogineer.com/agent-skills).

The skill's own files are unmodified copies. AutoGineer is not affiliated with or endorsed by the author or the publisher.

Files added by AutoGineer

  • ATTRIBUTION.md: this file, written by AutoGineer

  • LICENSE: copied from LICENSE

  • NOTICE: copied from NOTICE

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python

Security

What our scanner noticed· Low risk

  • Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
AWS Labs
Publisher
AWS Labs (Official)
Source
awslabs/agent-plugins · plugins/sagemaker-ai/skills/sdk-getting-started · commit fbefb37
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • NOTICE (added by AutoGineer from NOTICE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by AWS Labs or AWS Labs.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download sdk-getting-started.zip