Skill UI

Automates creation of unittest-based test suites by guiding developers through industry best practices for unit and integration testing, mocking, and framework setup while validating outputs against common standards.

This guide details how to integrate Vast.ai's GPU provisioning capabilities into automated CI/CD pipelines, such as GitHub Actions. It enables developers to run GPU-accelerated tests, model benchmarks, and validations automatically. Key features include robust instance lifecycle management (provisioning, running, and cleanup) and advanced cost-control mechanisms (e.g., setting budget limits) to ensure reliable and efficient testing in a cloud environment.

A comprehensive guide demonstrating the full lifecycle of GPU resource utilization on Vast.ai. This includes searching for available hardware using CLI and REST APIs, provisioning a dedicated GPU instance (e.g., using PyTorch images), connecting via SSH, running deep learning workloads, and finally, securely destroying the instance to stop billing. Ideal for testing cloud integration or managing ML compute pipelines.

This guide establishes a fast, reproducible local development workflow for GPU workloads using Vast.ai. It covers key practices such as testing Docker images locally (in CPU mode), mocking external APIs like Vast.ai, and implementing robust unit and integration tests. This is essential for minimizing cloud GPU costs and accelerating the iteration cycle for complex AI/ML projects.

Master advanced testing strategies for smart contracts using industry-leading frameworks like Hardhat and Foundry. This skill covers unit testing, integration testing, gas optimization analysis, fuzzing for edge cases, and simulating real-world mainnet interactions via forking. Ideal for ensuring the security and reliability of decentralized applications (DApps).

Provides the official Opentrons Protocol API v2 integration for OT-2 and Flex robots, enabling Python-based automation of liquid handling, module control, labware setup, pipetting flows, and protocol testing before execution.

This skill provisions instant, temporary PostgreSQL databases via Neon. It eliminates the need for user sign-up, logins, or credit cards, making it ideal for rapid local development, API prototyping, and isolated testing environments. Supports multiple methods including REST API calls, CLI commands, and SDK integration.

This advanced pipeline orchestrates complex feature development based on Request for Comments (RFCs). It breaks down monolithic changes into small, independently verifiable work units, managing dependencies through a Directed Acyclic Graph (DAG). It includes multiple quality gates, dedicated unit testing, and a safe merge queue to ensure robust integration and controlled deployment.

Offers testing guidance covering TDD workflows, unit/integration/E2E organization, framework support, mocking strategy, and coverage to help teams deliver reliable, well-structured test suites.

A comprehensive set of architectural patterns for building robust and maintainable HTTP servers using Kotlin Coroutines and the Ktor framework. It covers essential topics including REST routing DSL, plugin configuration (Authentication, CORS, StatusPages), Dependency Injection (Koin), serialization, WebSockets, and integration testing using testApplication.

A comprehensive guide to writing robust and maintainable tests in Rust. It covers various advanced testing patterns, including Unit, Integration, Async, and Property-Based testing. Learn how to apply the TDD (Test-Driven Development) cycle (RED-GREEN-REFACTOR) to enhance code reliability and ensure high code coverage.

A comprehensive guide and toolkit for advanced network reconnaissance using Nmap. It covers sophisticated techniques including service version detection, vulnerability scanning via Nmap Scripting Engine (NSE), firewall evasion methods (e.g., fragmentation, decoy addressing), and structured output parsing for integration into vulnerability management pipelines. Essential for authorized penetration testing.