Generate comprehensive issue reports from HyperPod clusters (EKS and Slurm) by collecting diagnostic logs and configurations for troubleshooting and AWS Support cases. Use when users need to collect diagnostics from HyperPod cluster nodes, generate issue reports for AWS Support, investigate node failures or…
Diagnose and remediate per-node issues on a HyperPod cluster (EKS or Slurm) — a specific node is unhealthy, unresponsive, stuck, or needs replacing. Covers on-node EFA, GPU / accelerator hardware (XID, ECC, NVLink, row-remap, DCGM), Slurm node down/drained, disk and memory pressure, per-node lifecycle-script failures…
Diagnostic-only skill for Slurm scheduler and node-daemon issues on Amazon SageMaker HyperPod Slurm clusters. Scope mirrors the HyperPod troubleshooting guide. Invoke when the user reports a Slurm node stuck in down/drain, "Node unexpectedly rebooted" after auto-repair, slurmd not running, jobs stuck PENDING with…
Remote command execution and file transfer on SageMaker HyperPod cluster nodes via AWS Systems Manager (SSM). This is the primary interface for accessing HyperPod nodes — direct SSH is not available. Use when any skill, workflow, or user request needs to execute commands on cluster nodes, upload files to nodes…
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…
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.
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…
Discovers user intent and generates a structured, step-by-step plan for model customization workflows. This skill must always be activated alongside any other skill when the user's request relates to model customization — including fine-tuning, training, building, customizing, reviewing data, or getting advice on…
Validates the user's environment for SageMaker AI operations — checks SDK version, AWS region, and execution role. Use when the user says "set up", "getting started", "check my environment", "configure SDK", or as the first step in any plan involving SageMaker/Bedrock training, evaluation, or deployment.
Creates a reusable use case specification file that defines the business problem, stakeholders, and measurable success criteria for model customization, as recommended by the AWS Responsible AI Lens. Use as the default first step in any model customization plan. Skip only if the user explicitly declines or already has…
Instructions for awslabs/run-model-context-protocol-servers-with-aws-lambda: See DEVELOP.md for instructions on setting up your development environment.
Instructions for awslabs/Log-Analyzer-with-MCP, covering agents.md, project overview, build & development commands, installation and running the server (local development).
Validate the IAM policies in a CloudFormation template against AWS IAM Access Analyzer before deploying, using the cfn-policy-validator CLI. Use when reviewing or gating a CloudFormation (or CDK-synthesized) template that defines IAM identity or resource policies, when asked to check a template for policy errors…
Phase 1 Business Context Analysis guide. Use when starting a threat model, setting business context, or configuring business features like industry sector, data sensitivity, and regulatory requirements.
Phase 2 Architecture Analysis guide. Use when documenting system components, connections, data stores, or analyzing technical architecture for threat modeling.
Phase 5 Asset Flow Analysis guide. Use when identifying valuable assets, tracking data flows, or analyzing how sensitive data moves through the system.
Phase 6 Threat Identification guide with STRIDE methodology reference. Use when identifying threats, categorizing security issues, applying STRIDE analysis, or assessing threat severity and likelihood.
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+4 7d agoA41 tokens
originalApache-2.0
At most 3 mods per repository are shown here — the rest are on their repository pages: