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optimize-for-gpu

100 / 100 · Low risk

Fine to try.

By hashgraph-online/awesome-codex-plugins (GitHub) · coding · 1,568 stars · scanned at commit 3e1e6b2

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 G…

Works with any agent that supports SKILL.md skills.

What this skill can do

We found nothing in the files we read that matches our rules. That does not prove the skill is safe: see the limits of static scanning.

Install

Paste this into your terminal. It downloads exactly the version we scanned, not whatever is newest.

if [ -e ~/.agents/skills/'optimize-for-gpu' ] || [ -L ~/.agents/skills/'optimize-for-gpu' ]; then echo 'A skill folder named optimize-for-gpu already exists — not replacing it' >&2; false; else d=$(mktemp -d) && git clone --quiet --filter=blob:none --no-checkout 'https://github.com/hashgraph-online/awesome-codex-plugins' "$d" && git -C "$d" checkout --quiet '3e1e6b20ffc28f42923e391f29f075c424e19e64' -- 'plugins/KalarisLabs/research-agent-skills/skills/optimize-for-gpu' && mkdir -p ~/.agents/skills && cp -R "$d"/'plugins/KalarisLabs/research-agent-skills/skills/optimize-for-gpu' ~/.agents/skills/'optimize-for-gpu' && rm -rf "$d"; fi

Codex reads ~/.agents/skills directly. For Claude Code, Cursor, Copilot, Gemini CLI, Antigravity or OpenCode, also link it. For Claude Code: ln -s ~/.agents/skills/'optimize-for-gpu' ~/.claude/skills/'optimize-for-gpu' (other agents: ~/.cursor/skills, ~/.copilot/skills, ~/.gemini/skills, ~/.gemini/config/skills, ~/.config/opencode/skills). Or install through the finder skill, which does both.

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Score history

DateVersionScore
2026-11-133e1e6b2100
2026-11-126d2e63f100
2026-11-114070676100
2026-11-10f620aba100
2026-11-093062ea3100
2026-11-08057d789100
2026-11-06e012fe1100