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Found 492 Skills
Define the design rules (Skill Laws) that all Skills must follow, including core principles such as AI-first, human-centric, and ready-to-use. When to use: When users create a new Skill, optimize an existing Skill, ask about Skill design specifications, or need to evaluate Skill quality.
Use this skill when architecting on AWS, selecting services, optimizing costs, or following the Well-Architected Framework. Triggers on EC2, S3, Lambda, RDS, DynamoDB, CloudFront, IAM, VPC, ECS, EKS, SQS, SNS, API Gateway, and any task requiring AWS architecture decisions, service selection, or cost management.
Provision AWS infrastructure with Terraform. Create modules, manage state, and implement IaC best practices. Use when deploying AWS resources declaratively.
Setup and initialization guide for developing AWS CDK (Cloud Development Kit) applications in Python. This skill enables users to configure environment prerequisites, create new CDK projects, manage dependencies, and deploy to AWS.
AWS API Gateway for REST and HTTP API management. Use when creating APIs, configuring integrations, setting up authorization, managing stages, implementing rate limiting, or troubleshooting API issues.
(Public Preview) Perform code upgrades, migrations, codebase analysis, and transformations using AWS Transform custom. Use this skill when a user asks to upgrade, migrate, modernize, analyze, or transform code across a repository. ATX supports any-to-any transformations including language version upgrades (Java, Python, Node.js, Ruby, Go, .NET, etc.), framework upgrades and migrations (Spring Boot, React, Angular, Django, etc.), API and SDK migrations (AWS SDK v1 to v2, boto2 to boto3, JS SDK v2 to v3), library upgrades, code refactoring, architecture migrations (x86 to Graviton/ARM64), language-to-language translations, and custom organization-specific transformations. Executes transformations locally on the user's machine using the ATX CLI. Always use the ATX CLI following the reference files — never attempt to modify code, upgrade dependencies, or run analysis manually.
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, read/download files from nodes, run diagnostics, install packages, or perform any operation requiring shell access to HyperPod instances. Other HyperPod skills depend on this skill for all node-level operations.
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 a use case specification to reuse. Captures problem statement, primary users, and LLM-as-a-Judge success tenets.
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 performance problems, document cluster state, or create diagnostic snapshots. Triggers on requests involving issue reports, diagnostic collection, support case preparation, or cluster troubleshooting that requires gathering logs and system information from multiple nodes.
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), Python, and PyTorch. Use when checking component versions, verifying CUDA/driver compatibility, detecting version mismatches across nodes, planning upgrades, documenting cluster configuration, or troubleshooting version-related issues on HyperPod. Triggers on requests about versions, compatibility, component checks, or upgrade planning for HyperPod clusters.
Laws of UX critique skill. Use when evaluating mockups, screenshots, design specs, prototypes, flows, onboarding, checkout, dashboards, forms, or design-review requests, even when the user does not say UX or name a law. Output the 2-4 most relevant laws with specific application and law-grounded recommendations. Do not use for pure frontend implementation code review, WCAG/accessibility audits, or brand/visual-identity critique unless interaction usability is also in scope.
Use when deploying your agent to AWS, or when a deploy has failed. Handles pre-flight validation, CDK/IAM/quota error diagnosis, version management, rollback, and canary deployments. Triggers on: "deploy my agent", "agentcore deploy", "deploy failed", "CDK error", "rollback", "canary deploy", "pin version", "redeploy", "deploy stuck". Not for production hardening — use agents-harden. Not for adding capabilities before deploy — use agents-build or agents-connect. Not for VPC configuration errors — use agents-build.