model-deployment
Generates code that deploys fine-tuned models from SageMaker Serverless Model Customization to SageMaker endpoints or Bedrock. Use when the user says "deploy my model", "create an endpoint", "make it available", or asks about deployment options. Identifies the correct deployment pathway (Nova vs OSS), generates deployment code, and handles endpoint configuration.
Install
With your agent
Install OMGSkills skill "awslabs/agent-plugins:plugins/sagemaker-ai/skills/model-deployment" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/awslabs/agent-plugins /tmp/agent-plugins && ln -s /tmp/agent-plugins/plugins/sagemaker-ai/skills/model-deployment ~/.claude/skills/model-deployment
From README
Model Deployment Identifies the correct deployment pathway based on model characteristics and generates deployment code. Scope This skill supports deploying Nova and OSS models that were fine-tuned through SageMaker Serverless Model Customization only. Not supported: Base models (not fine-tuned) Models fine-tuned through other processes Full Fine-Tuning (FFT) — only LoRA fine-tuned models are supported Prerequisites The SDK environment has been verified (SDK version, region, execution role). If not done, activate the sdk-getting-started skill first. --- Principles One thing at a time. Each response advances exactly one decision. Confirm before proceeding. Wait for the user to agree before moving on. But don't re-ask questions already answered in the conversation — use what you know. Don't read files until you need them. Only read pathway references after the pathway is confirmed. Use what you know.
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