PyGPUkit

Run matmul performance benchmarks. Use when user wants to measure TFLOPS, compare kernel performance, or verify correctness after code changes.

SM120 (Blackwell) CUDA expert. Use for wgmma/mma PTX inline assembly, TMA, narrow precision (FP4/FP6/FP8), and block-scaled GEMM development.

View and analyze build logs. Use when user wants to see build errors, check previous build output, or debug build failures.

Run LLM inference tests with Qwen or other models. Use when testing model loading, inference, CUDA Graph, or generation quality.

Run all checks including lint, typecheck, and tests. Use before creating PRs or for comprehensive validation.

CUDA kernel development workflow. Use when writing, testing, or optimizing GPU kernels. Follows the Edit-Build-Validate-Benchmark-Commit cycle.

Run Ruff linter and formatter on Python code. Use before commits or when checking code style and quality issues.

Run all pre-commit checks (lint + typecheck). Use before every git commit to ensure code quality.

Run pytest test suite. Use to verify functionality after code changes or before commits.

Run Mypy type checker on Python code. Use to verify type annotations and catch type errors before commits.