Hf Cloud Sagemaker Deployment Planner
Plan and coordinate a model deployment to Amazon SageMaker, including serving stack and...
Install
npx skills add waybarrios/opencode-power-pack --skill hf-cloud-sagemaker-deployment-planner -g -a claude-code -y- Repository
- waybarrios/opencode-power-pack549
- Category
- Media
- Updated
- 8d ago
- License
- MIT
- Context cost
- Mediumabout 1,615 tokens
- Runs scripts
- No, instructions only
What it does
Plan and coordinate a model deployment to Amazon SageMaker, including serving stack and real-time versus async inference. Use as the entry point for SageMaker hosting requests, before image, IAM, and endpoint implementation skills.
SageMaker Deployment Planner
You are helping a user deploy a model to Amazon SageMaker. Most users invoking this skill want the model deployed with reasonable defaults, in as few questions as possible. Ask only what you need, recommend a pathway honestly, and hand off to the specialized skills.
Workflow phases
- Discovery, what is being deployed and what are the constraints (this skill)
- Pathway selection, real-time / serverless / async / batch / Bedrock CMI (this skill)
- Context preflight,
hf-cloud-aws-context-discovery, thenhf-cloud-python-env-setup - IAM preflight,
hf-cloud-sagemaker-iam-preflight - Image selection,
hf-cloud-serving-image-selection - Deployment,
hf-cloud-sagemaker-production-defaults
Phases 1, 2 are this skill's job. The others activate when their patterns match.
Discovery: ask only what you need
You will eventually need to know:
- What model: HuggingFace ID, S3 path to artifacts, or model name. If the user is vague ("the model I fine-tuned"), ask for the artifact location.
- Model type: text-generation LLM, embedding/reranker, or other (classifier, NER, etc.). This determines the serving stack, usually inferable from the model name (anything ending in
-embed-*, starting withBAAI/bge-,sentence-transformers/*etc. is embeddings; chat/instruct models are LLMs). Only ask if it's genuinely ambiguous. - Traffic shape: roughly how often will this be called?
- Latency tolerance: interactive, near-real-time, or async?
- Cost sensitivity: ask only if the user signals it or the traffic pattern is ambiguous.
Region comes from hf-cloud-aws-context-discovery, don't ask unless the user volunteers it.
