[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"org-aws-labs":3,"repo-skills-v-0-3-0":334},{"org":4,"repos":60},{"slug":5,"name":6,"logoUrl":7,"githubOrg":8,"website":9,"skillCount":10,"repoCount":11,"topRepos":12,"topTags":28,"lastUpdatedAt":59},"aws-labs","AWS Labs","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Faws-labs.png","awslabs","https:\u002F\u002Faws.amazon.com",150,11,[13,16,19,22,25],{"name":14,"skillCount":15},"awslabs\u002Fstartups",42,{"name":17,"skillCount":18},"awslabs\u002Fhcls-agent-skills",40,{"name":20,"skillCount":21},"awslabs\u002Fagent-plugins",33,{"name":23,"skillCount":24},"awslabs\u002Fcli-agent-orchestrator",16,{"name":26,"skillCount":27},"awslabs\u002Fmcp",7,[29,32,35,38,41,44,47,50,53,56],{"slug":30,"name":31},"aws","AWS",{"slug":33,"name":34},"healthcare","Healthcare",{"slug":36,"name":37},"life-sciences","Life Sciences",{"slug":39,"name":40},"deployment","Deployment",{"slug":42,"name":43},"infrastructure","Infrastructure",{"slug":45,"name":46},"agents","Agents",{"slug":48,"name":49},"architecture","Architecture",{"slug":51,"name":52},"bioinformatics","Bioinformatics",{"slug":54,"name":55},"data-analysis","Data Analysis",{"slug":57,"name":58},"engineering","Engineering","2026-08-01T05:43:53.724377",[61,79,108,131,157,189,224,246,267,284,311],{"name":62,"fullName":14,"repoUrl":63,"skillCount":15,"stars":64,"forks":65,"description":66,"topics":67,"topTags":68,"topTagCount":77,"lastUpdatedAt":78},"startups","https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fstartups",14,15,"Official AWS Startups repository that hosts plugins, skills, tools and resources to support startup builders on AWS",[],[69,70,71,72,73,76],{"slug":30,"name":31},{"slug":48,"name":49},{"slug":39,"name":40},{"slug":42,"name":43},{"slug":74,"name":75},"security","Security",{"slug":57,"name":58},57,"2026-07-25T05:32:20.160804",{"name":80,"fullName":17,"repoUrl":81,"skillCount":18,"stars":82,"forks":83,"description":84,"topics":85,"topTags":98,"topTagCount":21,"lastUpdatedAt":107},"hcls-agent-skills","https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fhcls-agent-skills",4,0,"Agent skills for healthcare and life sciences: genomics, imaging, claims, drug discovery, and more. Works with Amazon Quick, Kiro, Amazon AgentCore, AWS Strands SDK, Claude Code, Codex, and any Agent Skills-compatible platform.",[86,87,88,89,90,91,92,93,94,36,95,96,97],"agent-skills","agentcore","ai-agents","amazon-quick-desktop","claims-processing","drug-discovery","genomics","healthcare-ai","kiro","medical-imaging","risk-adjustment","strands-agents",[99,100,101,102,103,106],{"slug":36,"name":37},{"slug":33,"name":34},{"slug":51,"name":52},{"slug":54,"name":55},{"slug":104,"name":105},"research","Research",{"slug":30,"name":31},"2026-07-25T05:56:34.955181",{"name":109,"fullName":20,"repoUrl":110,"skillCount":21,"stars":111,"forks":112,"description":113,"topics":114,"topTags":117,"topTagCount":130,"lastUpdatedAt":59},"agent-plugins","https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fagent-plugins",831,127,"Agent Plugins for AWS equip AI coding agents with the skills to help you architect, deploy, and operate on AWS.",[109,86,45,30,115,116],"coding-agent-skills","coding-agents",[118,119,120,121,124,127],{"slug":30,"name":31},{"slug":39,"name":40},{"slug":42,"name":43},{"slug":122,"name":123},"debugging","Debugging",{"slug":125,"name":126},"llm","LLM",{"slug":128,"name":129},"observability","Observability",52,{"name":132,"fullName":23,"repoUrl":133,"skillCount":24,"stars":134,"forks":135,"description":136,"topics":137,"topTags":138,"topTagCount":155,"lastUpdatedAt":156},"cli-agent-orchestrator","https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fcli-agent-orchestrator",871,164,null,[],[139,140,143,146,149,152],{"slug":45,"name":46},{"slug":141,"name":142},"mcp","MCP",{"slug":144,"name":145},"automation","Automation",{"slug":147,"name":148},"api-development","API Development",{"slug":150,"name":151},"cli","CLI",{"slug":153,"name":154},"orchestration","Orchestration",24,"2026-07-29T06:00:28.147989",{"name":141,"fullName":26,"repoUrl":158,"skillCount":27,"stars":159,"forks":160,"description":161,"topics":162,"topTags":170,"topTagCount":187,"lastUpdatedAt":188},"https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fmcp",9427,1634,"Open source MCP Servers for AWS",[30,141,163,164,165,166,167,168,169],"mcp-client","mcp-clients","mcp-host","mcp-server","mcp-servers","mcp-tools","modelcontextprotocol",[171,172,175,178,181,184],{"slug":30,"name":31},{"slug":173,"name":174},"database","Database",{"slug":176,"name":177},"serverless","Serverless",{"slug":179,"name":180},"sql","SQL",{"slug":182,"name":183},"migration","Migration",{"slug":185,"name":186},"aurora","Aurora",10,"2026-07-12T08:37:22.601527",{"name":190,"fullName":191,"repoUrl":192,"skillCount":193,"stars":194,"forks":195,"description":196,"topics":197,"topTags":208,"topTagCount":65,"lastUpdatedAt":223},"agentcore-samples","awslabs\u002Fagentcore-samples","https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fagentcore-samples",6,3176,1233,"Amazon Bedrock Agentcore accelerates AI agents into production with the scale, reliability, and security, critical to real-world deployment.",[198,199,45,200,201,202,203,204,205,206,207],"agent","agentic-ai","authentication","bedrock","core","gateway","identity-management","memory-management","production-code","runtime",[209,212,215,218,221,222],{"slug":210,"name":211},"finance","Finance",{"slug":213,"name":214},"analytics","Analytics",{"slug":216,"name":217},"accounting","Accounting",{"slug":219,"name":220},"reporting","Reporting",{"slug":144,"name":145},{"slug":30,"name":31},"2026-07-12T08:41:44.135656",{"name":225,"fullName":226,"repoUrl":227,"skillCount":228,"stars":229,"forks":83,"description":230,"topics":231,"topTags":235,"topTagCount":244,"lastUpdatedAt":245},"codeknit","awslabs\u002Fcodeknit","https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fcodeknit",2,3,"Static code structure extractor that turns a codebase into a compact, LLM-friendly graph of functions, classes, and relationships for refactoring, duplicate detection, and analysis across 12 languages",[232,125,233,234],"code-analysis","refactoring","static-analysis",[236,238,239,240,241],{"slug":232,"name":237},"Code Analysis",{"slug":57,"name":58},{"slug":48,"name":49},{"slug":122,"name":123},{"slug":242,"name":243},"git","Git",5,"2026-07-12T08:38:40.01893",{"name":247,"fullName":248,"repoUrl":249,"skillCount":250,"stars":251,"forks":252,"description":136,"topics":253,"topTags":257,"topTagCount":82,"lastUpdatedAt":266},"aws-cloudformation-iam-policy-validator","awslabs\u002Faws-cloudformation-iam-policy-validator","https:\u002F\u002Fgithub.com\u002Fawslabs\u002Faws-cloudformation-iam-policy-validator",1,146,25,[30,254,255,256],"aws-iam","aws-iam-policies","cloudformation",[258,259,262,265],{"slug":30,"name":31},{"slug":260,"name":261},"compliance","Compliance",{"slug":263,"name":264},"infrastructure-as-code","Infrastructure as Code",{"slug":74,"name":75},"2026-07-12T08:37:13.052325",{"name":268,"fullName":269,"repoUrl":270,"skillCount":250,"stars":229,"forks":83,"description":136,"topics":271,"topTags":272,"topTagCount":82,"lastUpdatedAt":283},"managed-service-for-apache-flink-agent-steering-files","awslabs\u002Fmanaged-service-for-apache-flink-agent-steering-files","https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fmanaged-service-for-apache-flink-agent-steering-files",[],[273,274,277,280],{"slug":30,"name":31},{"slug":275,"name":276},"data-engineering","Data Engineering",{"slug":278,"name":279},"data-pipeline","Data Pipeline",{"slug":281,"name":282},"performance","Performance","2026-07-12T08:37:20.055112",{"name":285,"fullName":286,"repoUrl":287,"skillCount":250,"stars":288,"forks":289,"description":290,"topics":291,"topTags":304,"topTagCount":229,"lastUpdatedAt":310},"nx-plugin-for-aws","awslabs\u002Fnx-plugin-for-aws","https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fnx-plugin-for-aws",85,27,"The @aws\u002Fnx-plugin is a collection of code generators that automate the creation and configuration of cloud-native applications using AWS, TypeScript, Python and React within the Nx development ecosystem.",[30,292,293,294,295,296,141,297,298,299,300,301,302,303],"aws-cdk","cloudfront","cloudscape","fastapi","lambda","nx","productivity","python","react","tanstack","trpc","typescript",[305,306,309],{"slug":30,"name":31},{"slug":307,"name":308},"cloud","Cloud",{"slug":263,"name":264},"2026-07-29T05:39:03.760685",{"name":312,"fullName":313,"repoUrl":314,"skillCount":250,"stars":315,"forks":316,"description":317,"topics":318,"topTags":327,"topTagCount":82,"lastUpdatedAt":333},"threat-designer","awslabs\u002Fthreat-designer","https:\u002F\u002Fgithub.com\u002Fawslabs\u002Fthreat-designer",267,46,"Threat Designer is a GenerativeAI application designed to automate and streamline the threat modeling process for secure system design.",[199,319,320,321,322,323,324,325,326],"appsec","cybersecurity","devsecops","generativeai","threat-modeling","threat-modeling-tool","threatmodeling","threatmodelling",[328,329,330,331],{"slug":30,"name":31},{"slug":232,"name":237},{"slug":74,"name":75},{"slug":323,"name":332},"Threat Modeling","2026-07-12T08:37:14.772466",{"items":335,"total":21},[336,352,367,379,394,405,415,426,439,454,467,480,498,509,520,534,548,558,573,583,597,608,619,630],{"slug":337,"name":337,"fn":338,"description":339,"org":340,"tags":341,"stars":111,"repoUrl":110,"updatedAt":351},"amazon-location-service","integrate Amazon Location Service maps","Integrates Amazon Location Service APIs for AWS applications. Use this skill when users want to add maps (interactive MapLibre or static images); geocode addresses to coordinates or reverse geocode coordinates to addresses; calculate routes, travel times, or service areas; find places and businesses through text search, nearby search, or autocomplete suggestions; retrieve detailed place information including hours, contacts, and addresses; monitor geographical boundaries with geofences; or track device locations. Covers authentication, SDK integration, and all Amazon Location Service capabilities.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[342,344,345,348],{"name":148,"slug":147,"type":343},"tag",{"name":31,"slug":30,"type":343},{"name":346,"slug":347,"type":343},"Maps","maps",{"name":349,"slug":350,"type":343},"Navigation","navigation","2026-07-12T08:39:49.88311",{"slug":353,"name":353,"fn":354,"description":355,"org":356,"tags":357,"stars":111,"repoUrl":110,"updatedAt":366},"amplify-workflow","build and deploy apps with AWS Amplify","Build and deploy full-stack web and mobile apps with AWS Amplify Gen2 (TypeScript code-first). Covers auth (Cognito), data (AppSync\u002FDynamoDB including schema modeling, enum types, relationships, authorization rules), storage (S3), functions, APIs, and AI (Amplify AI Kit with Bedrock). Supports React, Next.js, Vue, Angular, React Native, Flutter, Swift, and Android. Always use this skill for Amplify Gen2 topics — even for questions you think you know — it contains validated, version-specific patterns that prevent common mistakes. TRIGGER when: user mentions Amplify Gen2; project has amplify\u002F directory or amplify_outputs; code imports @aws-amplify packages; user asks about defineBackend, defineAuth, defineData, defineStorage, or npx ampx. SKIP: Amplify Gen1 (amplify CLI v6), standalone SAM\u002FCDK without Amplify (use aws-serverless), direct Bedrock without Amplify AI Kit (use bedrock).",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[358,361,362,363,364],{"name":359,"slug":360,"type":343},"Auth","auth",{"name":31,"slug":30,"type":343},{"name":174,"slug":173,"type":343},{"name":40,"slug":39,"type":343},{"name":365,"slug":303,"type":343},"TypeScript","2026-07-12T08:39:43.500162",{"slug":368,"name":368,"fn":369,"description":370,"org":371,"tags":372,"stars":111,"repoUrl":110,"updatedAt":378},"api-gateway","build and manage Amazon API Gateway APIs","Build, manage, and operate APIs with Amazon API Gateway (REST, HTTP, and WebSocket). Triggers on phrases like: API Gateway, REST API, HTTP API, WebSocket API, custom domain, Lambda authorizer, usage plan, throttling, CORS, VPC link, private API. Also covers troubleshooting API Gateway errors (4xx, 5xx, timeout, CORS failures) and IaC templates containing API Gateway resources. For general REST API design unrelated to AWS, do not trigger.\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[373,374,375],{"name":148,"slug":147,"type":343},{"name":31,"slug":30,"type":343},{"name":376,"slug":377,"type":343},"REST API","rest-api","2026-07-12T08:39:00.149339",{"slug":380,"name":380,"fn":381,"description":382,"org":383,"tags":384,"stars":111,"repoUrl":110,"updatedAt":393},"aws-architecture-diagram","generate AWS architecture diagrams","Generate validated AWS architecture diagrams as draw.io XML using official AWS4 icon libraries. Use this skill whenever the user wants to create, generate, or design AWS architecture diagrams, cloud infrastructure diagrams, or system design visuals. Also triggers for requests to visualize existing infrastructure from CloudFormation, CDK, or Terraform code. Supports two modes: analyze an existing codebase to auto-generate diagrams, or brainstorm interactively from scratch. Exports .drawio files with optional PNG\u002FSVG\u002FPDF export via draw.io desktop CLI.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[385,386,387,390],{"name":49,"slug":48,"type":343},{"name":31,"slug":30,"type":343},{"name":388,"slug":389,"type":343},"Design","design",{"name":391,"slug":392,"type":343},"Diagrams","diagrams","2026-07-12T08:37:11.012278",{"slug":395,"name":395,"fn":396,"description":397,"org":398,"tags":399,"stars":111,"repoUrl":110,"updatedAt":404},"aws-lambda","build and deploy AWS Lambda functions","Design, build, deploy, test, and debug serverless applications with AWS Lambda. Triggers on phrases like: Lambda function, event source, serverless application, API Gateway, EventBridge, Step Functions, serverless API, event-driven architecture, Lambda trigger. For deploying non-serverless apps to AWS, use deploy-on-aws plugin instead.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[400,401,402,403],{"name":148,"slug":147,"type":343},{"name":31,"slug":30,"type":343},{"name":40,"slug":39,"type":343},{"name":177,"slug":176,"type":343},"2026-07-12T08:38:58.598492",{"slug":406,"name":406,"fn":407,"description":408,"org":409,"tags":410,"stars":111,"repoUrl":110,"updatedAt":414},"aws-lambda-durable-functions","build resilient AWS Lambda durable functions","Build resilient, long-running, multi-step applications with AWS Lambda durable functions with automatic state persistence, retry logic, and orchestration for long-running executions. Covers the critical replay model, step operations, wait\u002Fcallback patterns, error handling with saga pattern, testing with LocalDurableTestRunner. Triggers on phrases like: lambda durable functions, workflow orchestration, state machines, retry\u002Fcheckpoint patterns, long-running stateful Lambda functions, saga pattern, human-in-the-loop callbacks, and reliable serverless applications.\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[411,412,413],{"name":49,"slug":48,"type":343},{"name":31,"slug":30,"type":343},{"name":177,"slug":176,"type":343},"2026-07-12T08:39:05.546173",{"slug":416,"name":416,"fn":417,"description":418,"org":419,"tags":420,"stars":111,"repoUrl":110,"updatedAt":425},"aws-lambda-managed-instances","configure AWS Lambda Managed Instances","Evaluate, configure, and migrate workloads to AWS Lambda Managed Instances (LMI). Triggers on: Lambda Managed Instances, LMI, capacity provider, multi-concurrency Lambda, dedicated instance Lambda, EC2-backed Lambda, cold start elimination, Graviton Lambda, instance type for Lambda, scheduled scaling for LMI, Lambda cost optimization with Reserved Instances or Savings Plans. Also trigger when users describe high-volume predictable workloads seeking cost savings, want to scale LMI capacity on a schedule, or compare Lambda vs EC2 for steady-state traffic. For standard Lambda without LMI, use the aws-lambda skill instead.\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[421,422,423,424],{"name":31,"slug":30,"type":343},{"name":40,"slug":39,"type":343},{"name":43,"slug":42,"type":343},{"name":282,"slug":281,"type":343},"2026-07-12T08:39:07.007071",{"slug":427,"name":427,"fn":428,"description":429,"org":430,"tags":431,"stars":111,"repoUrl":110,"updatedAt":438},"aws-lambda-microvms","build and run applications on AWS Lambda","Build, run, debug, and operate applications on AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable serverless compute environments that run inside a container with up to 8-hour lifetimes. Triggers on: Lambda MicroVMs, Firecracker isolation, snapshot-resumable compute, suspend\u002Fresume, sandboxed or untrusted code execution, AI\u002Fagent code-execution sandboxes, interactive code playgrounds and notebooks (Jupyter, REPLs), reinforcement-learning environments, multi-tenant CI executors and build runners, sessionful game or simulation servers, isolated security scanners, long-lived sessions, or port-listening servers (gRPC, WebSocket, custom TCP). For standard event-driven Lambda functions, use the aws-lambda skill instead.\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[432,433,436,437],{"name":31,"slug":30,"type":343},{"name":434,"slug":435,"type":343},"Containers","containers",{"name":40,"slug":39,"type":343},{"name":177,"slug":176,"type":343},"2026-07-12T08:39:02.879049",{"slug":440,"name":440,"fn":441,"description":442,"org":443,"tags":444,"stars":111,"repoUrl":110,"updatedAt":453},"aws-serverless-deployment","deploy serverless applications with AWS","AWS SAM and AWS CDK deployment for serverless applications. Triggers on phrases like: use SAM, SAM template, SAM init, SAM deploy, CDK serverless, CDK Lambda construct, NodejsFunction, PythonFunction, SAM and CDK together, serverless CI\u002FCD pipeline. For general app deployment with service selection, use deploy-on-aws plugin instead.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[445,446,447,450,452],{"name":31,"slug":30,"type":343},{"name":40,"slug":39,"type":343},{"name":448,"slug":449,"type":343},"Node.js","nodejs",{"name":451,"slug":299,"type":343},"Python",{"name":177,"slug":176,"type":343},"2026-07-12T08:39:04.220873",{"slug":455,"name":455,"fn":456,"description":457,"org":458,"tags":459,"stars":111,"repoUrl":110,"updatedAt":466},"aws-step-functions","build workflows with AWS Step Functions","Build workflows with AWS Step Functions state machines using the JSONata query language. Covers Amazon States Language (ASL) structure, state types, variables, data transformation, error handling, AWS service integration, and migrating from the JSONPath to the JSONata query language.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[460,461,462,463],{"name":145,"slug":144,"type":343},{"name":31,"slug":30,"type":343},{"name":308,"slug":307,"type":343},{"name":464,"slug":465,"type":343},"Workflow Automation","workflow-automation","2026-07-12T08:39:01.448557",{"slug":468,"name":468,"fn":469,"description":470,"org":471,"tags":472,"stars":111,"repoUrl":110,"updatedAt":59},"aws-transform","migrate and modernize codebases to AWS","Migrate, modernize, and upgrade codebases to AWS. Run analysis on repos for tech debt, security vulnerabilities, and modernization opportunities. Transforms .NET Framework to .NET 8\u002F10, mainframe COBOL to Java, VMware VMs to EC2, SQL Server to Aurora, and upgrades Java\u002FPython\u002FNode.js versions and AWS SDKs. Use when the user says \"migrate .NET to AWS\", \"upgrade Java to 17\u002F21\", \"modernize COBOL\", \"modernize mainframe\", \"move VMware to EC2\", \"convert SQL Server to Aurora\", \"upgrade Python version\", \"migrate AWS SDK\", \"transform this codebase\", \"analyze for issues\", \"find tech debt\", \"what tech debt\", \"security vulnerabilities\", \"CVEs\", \"what's wrong with my code\", \"assess my repos\", \"where do I start\", \"find what's outdated\", \"analyze my repos\", \"AWS Transform - continuous modernization\", \"continuous modernization\" or \"continuous-modernization\". Don't use for infrastructure provisioning, CI\u002FCD pipelines, or general coding tasks.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[473,474,475,476,479],{"name":31,"slug":30,"type":343},{"name":58,"slug":57,"type":343},{"name":183,"slug":182,"type":343},{"name":477,"slug":478,"type":343},"Modernization","modernization",{"name":75,"slug":74,"type":343},{"slug":481,"name":481,"fn":482,"description":483,"org":484,"tags":485,"stars":111,"repoUrl":110,"updatedAt":497},"dataset-evaluation","validate datasets for SageMaker fine-tuning","Validates dataset formatting and quality for SageMaker model fine-tuning (SFT, DPO, or RLVR). Use when the user says \"is my dataset okay\", \"evaluate my data\", \"check my training data\", \"I have my own data\", or before starting any fine-tuning job. Detects file format, checks schema compliance against the selected model and technique, and reports whether the data is ready for training or evaluation.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[486,487,490,493,494],{"name":31,"slug":30,"type":343},{"name":488,"slug":489,"type":343},"Data Quality","data-quality",{"name":491,"slug":492,"type":343},"Datasets","datasets",{"name":126,"slug":125,"type":343},{"name":495,"slug":496,"type":343},"QA","qa","2026-07-12T08:39:18.030117",{"slug":499,"name":499,"fn":500,"description":501,"org":502,"tags":503,"stars":111,"repoUrl":110,"updatedAt":508},"dataset-transformation","transform datasets for ML model training","Generates code that transforms datasets between ML schemas for model training or evaluation. Use when the user says \"transform\", \"convert\", \"reformat\", \"change the format\", or when a dataset's schema needs to change to match the target format — always use this skill for format changes rather than writing inline transformation code. Supports OpenAI chat, SageMaker SFT\u002FDPO\u002FRLVR\u002FRLAIF, HuggingFace preference, Bedrock Nova, VERL, and custom JSONL formats from local files or S3.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[504,505,506,507],{"name":276,"slug":275,"type":343},{"name":279,"slug":278,"type":343},{"name":491,"slug":492,"type":343},{"name":451,"slug":299,"type":343},"2026-07-12T08:39:27.993604",{"slug":510,"name":510,"fn":511,"description":512,"org":513,"tags":514,"stars":111,"repoUrl":110,"updatedAt":519},"deploy","deploy applications to AWS","Deploy applications to AWS. Triggers on phrases like: deploy to AWS, host on AWS, run this on AWS, AWS architecture, estimate AWS cost, generate infrastructure. Analyzes any codebase and deploys to optimal AWS services.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[515,516,517,518],{"name":31,"slug":30,"type":343},{"name":308,"slug":307,"type":343},{"name":40,"slug":39,"type":343},{"name":43,"slug":42,"type":343},"2026-07-12T08:37:07.842148",{"slug":521,"name":521,"fn":522,"description":523,"org":524,"tags":525,"stars":111,"repoUrl":110,"updatedAt":533},"directory-management","organize project directories and artifacts","Manages project directory setup and artifact organization. Use when starting a new project, resuming an existing one, or when a PLAN.md needs to be associated with a project directory. Creates the project folder structure (specs\u002F, scripts\u002F, notebooks\u002F, manifests\u002F, agent_memory\u002F) and resolves project naming.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[526,527,530],{"name":58,"slug":57,"type":343},{"name":528,"slug":529,"type":343},"Operations","operations",{"name":531,"slug":532,"type":343},"Process Documentation","process-documentation","2026-07-12T08:39:23.336947",{"slug":535,"name":535,"fn":536,"description":537,"org":538,"tags":539,"stars":111,"repoUrl":110,"updatedAt":547},"document-service","generate technical documentation for services","This skill should be used when the user asks to \"analyze this codebase\", \"document this service\", \"generate technical docs\", \"I inherited this code\", \"help me understand this system\", \"create docs for this project\", \"what does this system look like\", \"onboard me to this codebase\", \"this codebase has no docs\", \"visualize the architecture from code\", or any explicit request to produce structured documentation or architecture diagrams from an existing codebase. Specifically optimized for AWS workloads (CDK, CloudFormation, Terraform) with source-of-truth citations. Do NOT activate for code reviews, single-function explanations, generating new code, or general coding tasks.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[540,541,544],{"name":237,"slug":232,"type":343},{"name":542,"slug":543,"type":343},"Documentation","documentation",{"name":545,"slug":546,"type":343},"Technical Writing","technical-writing","2026-07-12T08:39:44.980705",{"slug":549,"name":549,"fn":550,"description":551,"org":552,"tags":553,"stars":111,"repoUrl":110,"updatedAt":557},"elastic-beanstalk","deploy applications to AWS Elastic Beanstalk","Deploy to AWS Elastic Beanstalk. Triggers on: elastic beanstalk, EB, managed EC2 platform, web app with managed patching, worker on EC2, Heroku alternative, don't want to manage servers or container orchestration, migrate from Heroku, managed operational lifecycle. Covers Elastic Beanstalk on EC2 for web and worker applications.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[554,555,556],{"name":31,"slug":30,"type":343},{"name":308,"slug":307,"type":343},{"name":40,"slug":39,"type":343},"2026-07-12T08:37:09.102311",{"slug":559,"name":559,"fn":560,"description":561,"org":562,"tags":563,"stars":111,"repoUrl":110,"updatedAt":572},"finetuning","fine-tune models with SageMaker","Generates code that fine-tunes a base model using SageMaker serverless training jobs. Use when the user says \"start training\", \"fine-tune my model\", \"I'm ready to train\", or when the plan reaches the finetuning step. Supports SFT, DPO, RLVR, and RLAIF trainers, including RLVR Lambda reward function and RLAIF custom prompt creation.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[564,567,568,569],{"name":565,"slug":566,"type":343},"AI Infrastructure","ai-infrastructure",{"name":31,"slug":30,"type":343},{"name":126,"slug":125,"type":343},{"name":570,"slug":571,"type":343},"Machine Learning","machine-learning","2026-07-12T08:39:37.178051",{"slug":574,"name":574,"fn":575,"description":576,"org":577,"tags":578,"stars":111,"repoUrl":110,"updatedAt":582},"finetuning-technique","select model fine-tuning techniques","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. Use when the user has decided to finetune and needs to choose a technique, or when the technique needs to be validated against a model. Requires a base model to already be selected (via model-selection skill).",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[579,580,581],{"name":46,"slug":45,"type":343},{"name":565,"slug":566,"type":343},{"name":126,"slug":125,"type":343},"2026-07-12T08:39:21.94401",{"slug":584,"name":584,"fn":585,"description":586,"org":587,"tags":588,"stars":111,"repoUrl":110,"updatedAt":596},"hyperpod-cluster-debugger","diagnose and remediate HyperPod cluster failures","Diagnose and remediate cluster-wide HyperPod (EKS or Slurm) problems — creation \u002F deployment failures (CloudFormation, EFA health check, lifecycle scripts, capacity), EKS access, node replacement, CloudFormation nested-stack errors, post-maintenance rollback state, dangling nodes, autoscaler conflicts. Includes `--validate` pre-flight. Read-only.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[589,590,591,592,595],{"name":31,"slug":30,"type":343},{"name":123,"slug":122,"type":343},{"name":43,"slug":42,"type":343},{"name":593,"slug":594,"type":343},"Kubernetes","kubernetes",{"name":528,"slug":529,"type":343},"2026-07-12T08:39:33.335106",{"slug":598,"name":598,"fn":599,"description":600,"org":601,"tags":602,"stars":111,"repoUrl":110,"updatedAt":607},"hyperpod-issue-report","generate diagnostic reports for HyperPod clusters","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.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[603,604,605,606],{"name":31,"slug":30,"type":343},{"name":123,"slug":122,"type":343},{"name":43,"slug":42,"type":343},{"name":129,"slug":128,"type":343},"2026-07-12T08:39:24.586806",{"slug":609,"name":609,"fn":610,"description":611,"org":612,"tags":613,"stars":111,"repoUrl":110,"updatedAt":618},"hyperpod-nccl","diagnose NCCL and GPU training cluster failures","Diagnose NCCL failures and adjacent training-pod failures on HyperPod GPU clusters (EKS or Slurm) — training hangs, AllReduce \u002F collective-op timeouts, EFA or libfabric errors, rendezvous failures, EFA TCP fallback, \u002Fdev\u002Fshm or memlock issues, NCCL version mismatch across pods, container OOM \u002F exit-137 \u002F OOMKilled, GPU OOM (CUDA out of memory), CrashLoopBackOff \u002F Pending pods, MASTER_ADDR DNS, NetworkPolicy blocking. Not for single-node hardware faults (→ hyperpod-node-debugger § G) or cluster-creation EFA \u002F SSM failures (→ hyperpod-cluster-debugger § A \u002F § F).",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[614,615,616,617],{"name":31,"slug":30,"type":343},{"name":123,"slug":122,"type":343},{"name":58,"slug":57,"type":343},{"name":129,"slug":128,"type":343},"2026-07-12T08:39:12.365564",{"slug":620,"name":620,"fn":621,"description":622,"org":623,"tags":624,"stars":111,"repoUrl":110,"updatedAt":629},"hyperpod-node-debugger","diagnose and remediate HyperPod cluster nodes","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 \u002F accelerator hardware (XID, ECC, NVLink, row-remap, DCGM), Slurm node down\u002Fdrained, disk and memory pressure, per-node lifecycle-script failures, SSM agent, container runtime, kernel panics, pod networking. Read-only. Not for cluster-wide provisioning (→ hyperpod-cluster-debugger), NCCL (→ hyperpod-nccl), or MFU (→ hyperpod-mfu-debugger).",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[625,626,627,628],{"name":31,"slug":30,"type":343},{"name":123,"slug":122,"type":343},{"name":43,"slug":42,"type":343},{"name":129,"slug":128,"type":343},"2026-07-12T08:39:26.704231",{"slug":631,"name":631,"fn":632,"description":633,"org":634,"tags":635,"stars":111,"repoUrl":110,"updatedAt":640},"hyperpod-performance-debugger","debug performance on SageMaker HyperPod clusters","Diagnose performance issues on Amazon SageMaker HyperPod clusters — uneven NCCL bandwidth across nodes and poor filesystem throughput. Read-only. Surfaces host-side signals (Xid, ECC, NVLink, EFA reachability, FSx saturation) and routes to the appropriate sibling skill (hyperpod-node-debugger, hyperpod-nccl, hyperpod-version-checker, hyperpod-issue-report) for any remediation. Triggers on uneven NCCL across nodes, straggler node, FSx slow, checkpoint slow, dataloader slow, filesystem bottleneck, FSx throughput, cross-AZ latency, topology mismatch.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[636,637,638,639],{"name":31,"slug":30,"type":343},{"name":123,"slug":122,"type":343},{"name":129,"slug":128,"type":343},{"name":282,"slug":281,"type":343},"2026-07-12T08:39:34.626279"]