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SKILL.md

model-evaluation

Agent skill fromawslabs/agent-plugins

Generates python code that evaluates SageMaker models. Supports two evaluation types: LLM-as-Judge and Custom Scorer. Use when the user says "evaluate my model", "run a benchmark", "test model performance", "how did my model perform", "compare models", or other similar requests.

How to install model-evaluation

install model-evaluation
# install the agent-plugins pack with the skills CLI
npx skills add awslabs/agent-plugins

# or add only this skill to Claude Code: copy the folder

plugins/sagemaker-ai/skills/model-evaluation/

# into

~/.claude/skills/model-evaluation/ (all projects)

.claude/skills/model-evaluation/ (one project)

plugins/sagemaker-ai/skills/model-evaluation/SKILL.md

Apache-2.0Full file
1# Model Evaluation
2
3Generate code that evaluates a SageMaker model.
4
5## Prerequisites
6
7- The SDK environment has been verified (SDK version, region, execution role). If not done, activate the `sdk-getting-started` skill first.
8
9## Principles
10
111. **One thing at a time.** Each response advances exactly one decision. Never combine multiple questions in a single turn.
122. **Confirm before proceeding.** Wait for the user to agree before moving to the next step.
133. **Don't read files until you need them.** Only read reference files when you've reached the step that requires them.
144. **Don't ask what you already know.** If the answer is in conversation history, workflow_state.json, plan.md, or any file you've already read — use it. Confirm if unsure, but don't re-ask.
155. **No narration.** Share outcomes and ask questions. Keep responses short.
166. **No repetition.** If you said something before a tool call, don't repeat it after.
17
18## Scope
19
20This skill supports the evaluation feature for SageMaker Serverless Model Customization. It can evaluate any base or fine-tuned model supported by SageMaker serverless model customization — both OSS models (Llama, Mistral, Qwen, etc.) and Nova models.
21
22Tell the user when the skill is activated:
23
24> "I can help evaluate any base or fine-tuned model supported by SageMaker serverless model customization."
25…

Excerpt shown under the repository's Apache-2.0 license.

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