model-selection
Selects a base model for the user's use case by querying SageMaker Hub. Use when the user asks which model to use, wants to select or change their base model, mentions a model name or family (e.g., "Llama", "Mistral", "Nova"), or wants to evaluate a base model — always activate even for known model names because the exact Hub model ID must be resolved. Queries available models, presents benchmarks and licenses, and confirms selection.
Install
With your agent
Install OMGSkills skill "awslabs/agent-plugins:plugins/sagemaker-ai/skills/model-selection" 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-selection ~/.claude/skills/model-selectionFrom README
Model Selection Guides the user through selecting a base model based on their use case. When to Use User asks which model to use User wants to select or change their base model User mentions a model name or family (e.g., "Llama", "Mistral", "Nova") — the exact Hub model ID still needs to be resolved User wants to evaluate a base model before deciding whether to finetune Prerequisites A usecasespec.md file exists. If not, activate the use-case-specification skill to generate it first. Workflow Step 1: Check Region Run: None → STOP. Tell user: "Set your region via export AWSDEFAULTREGION=us-west-2 or aws configure." Set → store REGION in context, continue. Step 2: Discover Hub List all available SageMaker Hubs in the user's region by calling the SageMaker ListHubs API using the awscallaws tool. From the results, filter out any hub whose HubDescription contains "AI Registry" — these do not contain JumpStart models.
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