Catlass Operator Design

Organization

Ascend

catlass-operator-design

将用户基于CATLASS开发算子的需求转变为具体的设计文档

Overview

Publisher	Ascend
Repository	`agent-skills`
Skill name	`catlass-operator-design`
Stars	54
Forks	4
Bundled files	6
License	MulanPSL-2.0
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
6 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by Ascend on GitHub. Read the source before you install it.

Installation

Install the Catlass Operator Design AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Ascend/agent-skills/tree/master/skills/catlass-operator-design
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/Ascend/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/skills/catlass-operator-design .claude/skills/catlass-operator-design

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Catlass Operator Design in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Catlass Operator Design on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Catlass Operator Design is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CATLASS 算子设计

核心工作流


需求分析 → 阅读 catlass 仓库 → 组件选型 → 输出设计文档

前置条件

检查项	说明
catlass 仓库	须在 OPS_PROJECT_ROOT 下可访问 `catlass/`（含 `include/`、`examples/`）
必读参考	设计前必须阅读本 skill 的 `references/` 文件

必读参考

文件	用途
design-document.md	设计文档模板
matmul-templates.md	模板清单与选型指南
epilogue-components.md	Epilogue 组件分类与组合模式
custom-epilogue.md	自定义 Epilogue 契约

算子命名（强制）

op_name（snake_case）必须包含子串 catlass，例如：catlass_matmul_add、catlass_fused_gemm_bias
禁止单独使用易与框架或其它厂商算子冲突的短名（如 matmul_add、gemm_add）
OpDef / 类名（CamelCase） 与目录名一致映射，如 CatlassMatmulAdd、ops/catlass_matmul_add/

选型与适配原则

从 catlass example 和 include 中确定要用的模板，不是把 example 整份粘贴到算子工程
大部分算子工程基于 msopgen 小工程，example 中的 Host 调用代码需要改写为工程中的 op_host/op_kernel 分离结构
设计阶段只产出选型决策，代码由 code-gen 生成

NEVER / ALWAYS

NEVER：使用不含 catlass 的算子名定稿设计；把 example 整份照抄；设计文档中写大量代码块；在信息不足时臆测需求

ALWAYS：算子名含 catlass，目录名与类名一致映射；条件不明则追问；设计前存在 catlass 仓库并阅读其文档与代码；设计文档用选型表格描述组件

需求输入

用户可能直接说出需求，也可能不说。执行本 skill 时：若认为信息不足，则继续追问。

需确认的信息：op_name（须含 catlass）、功能要点、I/O 与 dtype、布局、目标 SoC、参考 example（如有）、约束条件。

需求分析

确定 op_name：须含 catlass
提取：算子功能、数学公式、I/O、dtype、布局、目标 SoC、约束

阅读 catlass 并选型

阅读 catlass 仓库：examples/、include/ 下的文档与代码
在 examples/ 中按功能找相似示例，在设计文档中写明：选中的 example 路径、选型理由
若无完全匹配：基于 matmul-templates.md 与仓库中现有样例，说明变通方案
Epilogue：在 epilogue-components.md 与 catlass/include/catlass/epilogue/tile/ 中检索；无现成 Tile 时按 custom-epilogue.md 先写设计契约

组件选型

选型结果用概念表格记录在设计文档中，不写代码。

设计文档须显式写出选型表格：ArchTag、BlockMmad（L1/L0 TileShape、数据类型）、BlockEpilogue（各环节 Tile/Block 组件）、BlockScheduler、Kernel 类型。

输出设计文档

文档章节要求

概述：功能、场景、数学公式
输入输出信息表：变量名、数据类型、Shape、布局、描述
核心组件选型：用选型表格描述各层组件
参考 Example 与模板选型：选中的 example、选型理由
TilingKey 分支设计：各 key 对应的条件和 Kernel 分支内容
Workspace：大小计算逻辑来源
接口与使用：aclnn 接口、Host Tiling 流程、Kernel 入口概念
扩展性：可替换的组件
实现方案纲要：Host 侧与 Kernel 侧要点

输出格式

设计文档须为独立 Markdown 文件，命名建议 design_<op_name>.md，存放于 USER_OP_PROJECT 或用户指定路径。

质量验证

设计文档检查清单

算子名含 catlass，snake_case 目录名与 CamelCase 类名一致
含完整的输入输出信息表
核心组件选型已明确：ArchTag、BlockMmad、BlockEpilogue、BlockScheduler、Kernel
参考 example 已写明，选型理由清晰
TilingKey 分支设计已列出
交付路径 USER_OP_PROJECT 已明确

参考资料

文件	用途
design-document.md	设计文档模板与章节规范
matmul-templates.md	模板清单与选型指南
epilogue-components.md	Epilogue 组件分类与选型
custom-epilogue.md	自定义 Tile Epilogue 的设计契约
catlass/examples/	开发形式与多种模板参考
catlass/docs/3_API/gemm_api.md	Gemm API 分层模型、组件对照表

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Catlass Operator Design AI skill do?

将用户基于CATLASS开发算子的需求转变为具体的设计文档

Why use Catlass Operator Design on TypingMind?

Because you install it once and use it with any model. Catlass Operator Design is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Catlass Operator Design in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Ascend/agent-skills/tree/master/skills/catlass-operator-design. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Catlass Operator Design?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Catlass Operator Design?

As many as you like. As long as a model supports skills, you can use Catlass Operator Design with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Catlass Operator Design AI skill free?

Yes. It is published on GitHub by Ascend under the MulanPSL-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

CATLASS 算子设计

核心工作流

前置条件

必读参考

算子命名（强制）

选型与适配原则

NEVER / ALWAYS

需求输入

需求分析

阅读 catlass 并选型

组件选型

输出设计文档

文档章节要求

输出格式

质量验证

设计文档检查清单

参考资料

Bundled files

Frequently asked questions

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