一个开源的 AI 编码代理计算内核技能文件库。

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核心技能

这是什么

kernel-skills 是一个经过策划的 SKILL.md 文件集合。每个文件都是结构化的工程操作手册，AI 编码代理在编写、优化、调试或移植计算内核时可以遵循。

技能就是产品。仓库还附带一个npm包（@krxgu/kernel-skills），用带有小型CLI和TypeScript API的版本化注册表包裹它们。如果你想用脚本来发现和捆绑技能，可以用npm包;否则直接读或粘贴Markdown就行。

它不是

• 非内核编译器 — 它从未调用nvcc、ptxas或hip-clang
• **非基准工具 ** — 它不运行内核或性能
• 非模型服务运行时
• 不是自主编码代理
• 不执行生成代码

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为什么它存在

当给出模糊的提示时，AI编码代理产生的内核代码明显更差。

An open source library of high quality skill files for AI coding agents working on compute kernels.

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kernel-skills

What it is

kernel-skills is a curated collection of SKILL.md files. Each file is a structured engineering playbook that an AI coding agent can follow when writing, optimizing, debugging, or porting compute kernels.

The skills are the product. The repository also ships an npm package (@krxgu/kernel-skills) that wraps them in a versioned registry with a small CLI and TypeScript API. Use the npm package if you want to script skill discovery and bundling; otherwise just read or paste the Markdown directly.

What it is not

• not a kernel compiler — it never invokes nvcc, ptxas, or hip-clang
• not a benchmark harness — it does not run kernels or measure performance
• not a model-serving runtime
• not an autonomous coding agent
• does not execute generated code

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Why it exists

AI coding agents produce substantially worse kernel code when given vague prompts. They skip constraint gathering, choose incorrect tile strategies, ignore boundary conditions, make unsupported performance claims, and produce code that looks plausible but fails on real hardware.

Structured skill files change this. A well-authored skill forces the agent to:

• gather the right constraints before writing a single line of code
• choose the correct algorithm and memory strategy for the workload
• reason explicitly about correctness risks and edge cases
• avoid cargo-cult optimization and fake performance claims
• explain tradeoffs with technical precision
• know when a custom kernel is not the right answer

This repository exists to provide those skill files at expert quality, openly, for any agent and any workflow.

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Measured impact

Same model. Same prompt. One difference: a kernel skill file. The naive softmax kernel fails on overflow and large shapes. The skill-guided version stays correct and bandwidth-competitive.

Correctness: pass / fail matrix