Skill UI

This skill simulates a senior Go developer, specializing in writing high-performance, production-grade Go applications. It covers advanced topics like concurrent programming using goroutines and channels, designing robust microservices with gRPC/REST, and optimizing code using pprof and benchmarks. It enforces idiomatic Go patterns, context propagation, and strict testing practices (table-driven, fuzzing, race detection).

A tool designed to collect comprehensive diagnostic evidence for troubleshooting issues encountered with the Groq API. It captures environment details, API connectivity status, rate limit information, latency benchmarks, and redacted application logs, making it essential for creating detailed and actionable support tickets.

Enterprise NeMo Evaluator SDK runs over 100 benchmarks from 18+ harnesses with multi-backend execution (Docker, Slurm, cloud) to give reproducible, scalable LLM evaluation workflows.

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.

This skill provides a comprehensive framework for measuring Go application performance. It guides users through writing robust benchmarks using `testing.B`, running tests with various flags (`-benchmem`, `-cpuprofile`), interpreting complex profiling data (pprof), statistically comparing results using tools like `benchstat`, and setting up CI regression detection. It is essential for deep performance analysis and making statistically sound optimization decisions.

Comprehensive Go testing guidance that spans table-driven subtests, testify suites, mocking, unit/integration tests, benchmarks, coverage, fuzzing, goleak leak detection, snapshot checks, and GitHub Actions CI to keep production suites reliable.

A comprehensive reference guide providing quantitative benchmarks and formulas for system architects. It covers user-to-RPS conversion, storage estimation, bandwidth calculation, known scale limits of major technologies (databases, queues, caches), and capacity planning for various user loads (1K DAU to 10M DAU). Essential for designing scalable, high-availability applications.