tilegym-adding-cutile-kernel
Add a new cuTile GPU kernel operator to TileGym. Covers dispatch registration in ops.py, cuTile backend implementation, __init__.py exports, test creation, and benchmark in tests/benchmark. Use when adding, creating, or implementing a new cuTile operator/kernel in TileGym, or when asking how to register a new cuTile op.
npx skills add NVIDIA/skills --skill tilegym-adding-cutile-kernel --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Adding a cuTile Kernel to TileGym End-to-end workflow for adding a new operator (e.g., `my_op`) with cuTile backend. ## Execution Rules **MUST follow these rules strictly:** 1. Use TodoWrite to create the checklist below BEFORE writing any code 2. Execute steps **in order** — do NOT skip ahead or combine steps 3. Mark each todo as `completed` after finishing, `in_progress` when starting 4. If a
What does the tilegym-adding-cutile-kernel skill do?
Add a new cuTile GPU kernel operator to TileGym. Covers dispatch registration in ops.py, cuTile backend implementation, __init__.py exports, test creation, and benchmark in tests/benchmark. Use when adding, creating, or implementing a new cuTile operator/kernel in TileGym, or when asking how to register a new cuTile op.
How do I install it?
Run `npx skills add NVIDIA/skills --skill tilegym-adding-cutile-kernel --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From NVIDIA/skills, a repository with 2,789 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.