AI & LLM Engineering · Amazon SageMaker

Finds or validates a usable SageMaker execution role before deploying or training, so scripts do not try to create IAM roles they lack permission to create.

huggingface/skills

Chooses the right serving container and current image URI for deploying a Hugging Face model to a SageMaker endpoint, preferring Hugging Face images over generic ones.

huggingface/skills

Sets up an isolated Python environment with a supported interpreter and current boto3 before any SageMaker deployment, training or AWS automation code runs.

huggingface/skills

Validates dataset formatting and quality for SageMaker model fine-tuning (SFT, DPO, or RLVR).

awslabs/agent-plugins

Generates code that transforms datasets between ML schemas for model training or evaluation.

awslabs/agent-plugins

Deploys SageMaker endpoints with autoscaling, CloudWatch alarms and tags on by default, using scripts for real-time, scale-to-zero and async setups.

huggingface/skills

Selects a fine-tuning technique (SFT, DPO, RLVR, or RLAIF) for the user's use case and validates it against the selected model's available recipes.

awslabs/agent-plugins

A skill your agent uses for GPU training or inference clusters on SageMaker HyperPod (Slurm or EKS), ParallelCluster, or self-managed EC2/EKS GPU instances.

aws/tools-for-devops-agent

Diagnose performance issues on Amazon SageMaker HyperPod clusters — uneven NCCL bandwidth across nodes and poor filesystem throughput.

awslabs/agent-plugins

Diagnostic-only skill for Slurm scheduler and node-daemon issues on Amazon SageMaker HyperPod Slurm clusters.

awslabs/agent-plugins

Entry point for hosting a model on Amazon SageMaker: asks a few questions, picks a deployment pathway and hands off to the specialist skills.

huggingface/skills

Remote command execution and file transfer on SageMaker HyperPod cluster nodes via AWS Systems Manager (SSM).

awslabs/agent-plugins

Uses Meta's LlamaGuard moderation model to screen prompts and model replies against six safety categories, with vLLM, FastAPI and NeMo Guardrails setups.

Orchestra-Research/AI-Research-SKILLs

Selects a base model for the user's use case by querying SageMaker Hub.

awslabs/agent-plugins

Deep expertise in ML/CV model selection, training pipelines, and inference architecture.

alirezarezvani/claude-cto-team

Implement a production SageMaker endpoint with autoscaling, CloudWatch alarms, and tags.

waybarrios/opencode-power-pack

Check and compare software component versions on SageMaker HyperPod cluster nodes - NVIDIA drivers, CUDA toolkit, cuDNN, NCCL, EFA, AWS OFI NCCL, GDRCopy, MPI, Neuron SDK (Trainium/Inferentia)…

awslabs/agent-plugins

Select and verify the current region-specific serving container URI for a SageMaker model deployment.

waybarrios/opencode-power-pack

Generates code that fine-tunes a base model using SageMaker serverless training jobs.

awslabs/agent-plugins

Generates python code that evaluates SageMaker models. An agent skill from awslabs/agent-plugins.

awslabs/agent-plugins

Diagnose NCCL failures and adjacent training-pod failures on HyperPod GPU clusters (EKS or Slurm) — training hangs, AllReduce / collective-op timeouts, EFA or libfabric errors, rendezvous failures…

awslabs/agent-plugins

Generates code that deploys fine-tuned models from SageMaker Serverless Model Customization to SageMaker endpoints or Bedrock.

awslabs/agent-plugins

Plan and coordinate a model deployment to Amazon SageMaker, including serving stack and real-time versus async inference.

waybarrios/opencode-power-pack

Selects, deploys, and customizes AI models on Amazon SageMaker.

aws/agent-toolkit-for-aws

Cost guardrail for AWS DevOps Agent that covers ALL AWS services and native agent tools.

aws/tools-for-devops-agent