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Found 819 Skills
Design optimal cloud architecture based on your platform engineering requirements. Use when planning new services, migrations, or infrastructure changes that must align with organizational standards.
Clarity test infrastructure generation — scaffold vitest configs, test stubs, Clarunit files, and Rendezvous fuzz tests for Clarinet projects.
You are **Performance Benchmarker**, an expert performance testing and optimization specialist who measures, analyzes, and improves system performance across all applications and infrastructure. Yo...
Expert infrastructure specialist focused on system reliability, performance optimization, and technical operations management. Maintains robust, scalable infrastructure supporting business operations with security, performance, and cost efficiency.
Enables internet access for AWS Lambda functions deployed in VPC subnets by creating NAT Gateway infrastructure, configuring public/private subnet routing, and updating security groups. Use when a VPC-attached Lambda function cannot reach the internet.
Azure cloud resources including VMs, VMSS, SQL Database, Storage, AKS, App Service, Functions, VNet networking, load balancers, Event Hubs, Container Apps, and Key Vault. Monitor Azure infrastructure, analyze resource usage, audit security posture, and manage organizational hierarchy across subscriptions and resource groups.
Help users build and scale internal platforms and technical infrastructure. Use when someone is deciding whether to build vs buy tooling, designing developer platforms, creating shared services, or managing technical debt at scale.
Data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, implementing data governance, or troubleshooting data issues.
This skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention running jobs on Hugging Face infrastructure without local setup.
Orchestrates complete project initialization by coordinating agent-folder-init, linter-formatter-init, husky-test-coverage, and other setup skills. Use this skill when starting a new project that needs full AI-first development infrastructure with code quality enforcement.
Visualizes AWS infrastructure from CLI output, CloudFormation, or descriptions. Use when user has AWS resources to diagram.
Meta-agent for creating new custom agents, skills, and MCP integrations. Expert in agent design, MCP development, skill architecture, and rapid prototyping. Activate on 'create agent', 'new skill', 'MCP server', 'custom tool', 'agent design'. NOT for using existing agents (invoke them directly), general coding (use language-specific skills), or infrastructure setup (use deployment-engineer).