Real file from a public repo · synced Sep 3, 2026
optimize-for-gpu
GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX, scikit-image, vector-search, image-processing, graph, simulation, or file-I/O workloads; CuPy, cuDF, cuML, cuGraph, cuVS, cuCIM, KvikIO, Warp, Newton, Numba-CUDA, or RAFT questions; and profiling, memory-transfer, kernel, or multi-GPU bottlenecks. Also use when large data-parallel Python code is slow and GPU acceleration is a plausible option, even if the user does not name CUDA.
Works with
Install in three steps
- 1
Download the ZIP
One file per agent, plus INSTALL.md with the exact paths below.
- 2
Claude Code: copy SKILL.md into your skills folder
.claude/skills/optimize-for-gpu/SKILL.md # this project ~/.claude/skills/optimize-for-gpu/SKILL.md # every project
- 3
Other agents: use the matching file
skill.mdc goes in Cursor’s .cursor/rules/. AGENTS.md works as GitHub Copilot instructions, a legacy .cursorrules, or a Codex / Gemini CLI instructions file.

