Dataset Transformation

When you're prepping datasets for ML training or evaluation and need to convert between formats like OpenAI chat, SageMaker SFT/DPO, HuggingFace preference, or Bedrock Nova, this generates the transformation code for you instead of making you write it inline. It walks through an 11-step workflow that determines whether you're doing training or eval data (this matters because the schema resolution is different), figures out your source and target formats, examines samples, then generates and refines a Python transformation function before running it. Works with local files or S3. The workflow is thorough but rigid: you go step by step, confirm at each stage, and it won't let you skip around.

skills.sh installs: 153
GitHub stars: 938
last updated: Jun 11, 2026

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Install

$ npx -y skills add awslabs/agent-plugins --skill dataset-transformation --agent claude-code

Installs into .claude/skills of the current project.

Files

Dataset Transformation Agent

Transforms a data set provided by the user into their desired format.

When to Use

User needs to generate code for transforming datasets for SageMaker model training or model evaluation.
A dataset requires processing, cleaning, or formatting before training or evaluation.
Workflow requires a formal review and approval cycle before execution.