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add-uint-support添加 uint 支持

Agent Skill

add-uint-support 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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594

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208
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:add-uint-support(添加 uint 支持)
来源仓库:https://github.com/microck/ordinary-claude-skills
仓库路径:skills/add-uint-support
安装命令:
npx skills add microck/ordinary-claude-skills --skill "add-uint-support"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add microck/ordinary-claude-skills --skill "add-uint-support"

简介

发现并安装AI代理的技能工具集合。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

  • 适用于多宿主环境的技能扩展需求。add-uint-support 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 通过npx命令快速集成指定技能模块。
  • 安装前需评估技能来源与维护状态可靠性。
  • 注意不同宿主对技能权限和网络访问的限制差异。

SKILL.md

name
add-uint-support
description
Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.

Add Unsigned Integer (uint) Support to Operators

This skill helps add support for unsigned integer types (uint16, uint32, uint64) to PyTorch operators by updating their AT_DISPATCH macros.

When to use this skill

Use this skill when:

  • Adding uint16, uint32, or uint64 support to an operator
  • User mentions "unsigned types", "uint support", "barebones unsigned types"
  • Enabling support for kUInt16, kUInt32, kUInt64 in kernels
  • Working with operator implementations that need expanded type coverage

Quick reference

Add unsigned types to existing dispatch:

// Before
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
  kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES));

// After (method 1: add unsigned types explicitly)
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
  kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES));

// After (method 2: use V2 integral types if AT_INTEGRAL_TYPES present)
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
  kernel<scalar_t>();
}), AT_EXPAND(AT_INTEGRAL_TYPES_V2), AT_EXPAND(AT_FLOATING_TYPES));

Type group reference

Unsigned type groups:

  • AT_BAREBONES_UNSIGNED_TYPES: kUInt16, kUInt32, kUInt64
  • AT_INTEGRAL_TYPES_V2: AT_INTEGRAL_TYPES + AT_BAREBONES_UNSIGNED_TYPES

Relationship:

AT_INTEGRAL_TYPES          // kByte, kChar, kInt, kLong, kShort
AT_BAREBONES_UNSIGNED_TYPES  // kUInt16, kUInt32, kUInt64
AT_INTEGRAL_TYPES_V2       // INTEGRAL_TYPES + BAREBONES_UNSIGNED_TYPES

Instructions

Step 1: Determine if conversion to V2 is needed

Check if the file uses AT_DISPATCH_V2:

If using old AT_DISPATCH:

  • First convert to AT_DISPATCH_V2 using the at-dispatch-v2 skill
  • Then proceed with adding uint support

If already using AT_DISPATCH_V2:

  • Proceed directly to Step 2

Step 2: Analyze the current dispatch macro

Identify what type groups are currently in use:

AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
  // body
}), AT_EXPAND(AT_ALL_TYPES), kHalf, kBFloat16);
    ^^^^^^^^^^^^^^^^^^^^^^^^^
    Current type coverage

Common patterns:

  • AT_EXPAND(AT_ALL_TYPES) → includes AT_INTEGRAL_TYPES + AT_FLOATING_TYPES
  • AT_EXPAND(AT_INTEGRAL_TYPES) → signed integers only
  • AT_EXPAND(AT_FLOATING_TYPES) → floating point types

Step 3: Choose the uint addition method

Two approaches:

Method 1: Add AT_BAREBONES_UNSIGNED_TYPES explicitly

  • Use when: You want to be explicit about adding uint support
  • Add AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES) to the type list

Method 2: Substitute AT_INTEGRAL_TYPES with AT_INTEGRAL_TYPES_V2

  • Use when: The dispatch already uses AT_EXPAND(AT_INTEGRAL_TYPES)
  • More concise: replaces one type group with its superset
  • Only applicable if AT_INTEGRAL_TYPES is present

Step 4: Apply the transformation

Method 1 example:

// Before
AT_DISPATCH_V2(
    dtype,
    "min_values_cuda",
    AT_WRAP([&]() {
      kernel_impl<scalar_t>(iter);
    }),
    AT_EXPAND(AT_ALL_TYPES),
    kBFloat16, kHalf, kBool
);

// After (add unsigned types)
AT_DISPATCH_V2(
    dtype,
    "min_values_cuda",
    AT_WRAP([&]() {
      kernel_impl<scalar_t>(iter);
    }),
    AT_EXPAND(AT_ALL_TYPES),
    AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES),
    kBFloat16, kHalf, kBool
);

Method 2 example:

// Before
AT_DISPATCH_V2(
    dtype,
    "integral_op",
    AT_WRAP([&]() {
      kernel<scalar_t>();
    }),
    AT_EXPAND(AT_INTEGRAL_TYPES)
);

// After (substitute with V2)
AT_DISPATCH_V2(
    dtype,
    "integral_op",
    AT_WRAP([&]() {
      kernel<scalar_t>();
    }),
    AT_EXPAND(AT_INTEGRAL_TYPES_V2)
);

Step 5: Handle AT_ALL_TYPES vs individual type groups

If the dispatch uses AT_EXPAND(AT_ALL_TYPES):

  • AT_ALL_TYPES = AT_INTEGRAL_TYPES + AT_FLOATING_TYPES
  • To add uint: add AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES) to the list

If the dispatch separately lists INTEGRAL and FLOATING:

// Before
AT_EXPAND(AT_INTEGRAL_TYPES), AT_EXPAND(AT_FLOATING_TYPES)

// After (Method 2 preferred)
AT_EXPAND(AT_INTEGRAL_TYPES_V2), AT_EXPAND(AT_FLOATING_TYPES)

Step 6: Verify all dispatch sites

Check the file for ALL dispatch macros that need uint support:

  • Some operators have multiple dispatch sites (CPU, CUDA, different functions)
  • Apply the transformation consistently across all sites
  • Ensure each gets the same type coverage updates

Step 7: Validate the changes

Check that:

  • [ ] AT_DISPATCH_V2 format is used (not old AT_DISPATCH)
  • [ ] Unsigned types are added via one of the two methods
  • [ ] All relevant dispatch sites in the file are updated
  • [ ] Type groups use AT_EXPAND()
  • [ ] Arguments are properly formatted and comma-separated

Common patterns

Pattern 1: AT_ALL_TYPES + extras

// Before
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
  kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES), kHalf, kBFloat16);

// After
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
  kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES), kHalf, kBFloat16);

Pattern 2: Separate INTEGRAL + FLOATING

// Before
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
  kernel<scalar_t>();
}), AT_EXPAND(AT_INTEGRAL_TYPES), AT_EXPAND(AT_FLOATING_TYPES));

// After
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
  kernel<scalar_t>();
}), AT_EXPAND(AT_INTEGRAL_TYPES_V2), AT_EXPAND(AT_FLOATING_TYPES));

Pattern 3: Old dispatch needs conversion first

// Before (needs v2 conversion first)
AT_DISPATCH_ALL_TYPES_AND2(kHalf, kBFloat16, dtype, "op", [&]() {
  kernel<scalar_t>();
});

// After v2 conversion
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
  kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES), kHalf, kBFloat16);

// After adding uint support
AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
  kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES), kHalf, kBFloat16);

Multiple dispatch sites example

For a file with multiple functions:

void min_values_kernel_cuda(TensorIterator& iter) {
  AT_DISPATCH_V2(iter.dtype(), "min_values_cuda", AT_WRAP([&]() {
    impl<scalar_t>(iter);
  }), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES), kBFloat16, kHalf);
  //                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  //                           Added uint support
}

void min_launch_kernel(TensorIterator &iter) {
  AT_DISPATCH_V2(iter.input_dtype(), "min_cuda", AT_WRAP([&]() {
    gpu_reduce_kernel<scalar_t>(iter);
  }), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES), kBFloat16, kHalf);
  //                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  //                           Added uint support here too
}

Decision tree

Use this decision tree to determine the approach:

Is the file using AT_DISPATCH_V2?
├─ No → Use at-dispatch-v2 skill first, then continue
└─ Yes
   └─ Does it use AT_EXPAND(AT_INTEGRAL_TYPES)?
      ├─ Yes → Replace with AT_EXPAND(AT_INTEGRAL_TYPES_V2)
      └─ No → Add AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES) to type list

Edge cases

Case 1: Dispatch with only floating types

If the operator only supports floating point types, don't add uint support:

// Leave as-is - floating point only operator
AT_DISPATCH_V2(dtype, "float_op", AT_WRAP([&]() {
  kernel<scalar_t>();
}), AT_EXPAND(AT_FLOATING_TYPES), kHalf);

Case 2: Complex types present

Unsigned types work alongside complex types:

AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
  kernel<scalar_t>();
}), AT_EXPAND(AT_ALL_TYPES),
    AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES),
    AT_EXPAND(AT_COMPLEX_TYPES),
    kHalf, kBFloat16);

Case 3: Already has uint support

Check if uint types are already present:

  • If AT_INTEGRAL_TYPES_V2 is used → already has uint support
  • If AT_BAREBONES_UNSIGNED_TYPES is already in list → already has uint support
  • Skip the file if uint support is already present

Workflow

When asked to add uint support:

  1. Read the target file
  2. Check if using AT_DISPATCH_V2:

- If not → use at-dispatch-v2 skill first

  1. Identify all dispatch macro sites
  2. For each dispatch:

- Analyze current type groups - Choose method (add BAREBONES_UNSIGNED or upgrade to V2) - Apply transformation with Edit tool

  1. Show the user the changes
  2. Explain what was modified

Important notes

  • Always check if v2 conversion is needed first
  • Apply changes consistently across all dispatch sites in the file
  • Method 2 (AT_INTEGRAL_TYPES_V2) is cleaner when applicable
  • Method 1 (explicit AT_BAREBONES_UNSIGNED_TYPES) is more explicit
  • Unsigned types are: kUInt16, kUInt32, kUInt64 (not kByte which is uint8)
  • Some operators may not semantically support unsigned types - use judgment

Testing

After adding uint support, the operator should accept uint16, uint32, and uint64 tensors. The user is responsible for functional testing.

适合场景

01

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02

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03

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能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

29.58%
按下载量换算62

Codex

19.81%
按下载量换算41

Antigravity

17.91%
按下载量换算37

windsurf

11.01%
按下载量换算23

Gemini CLI

8.11%
按下载量换算17

OpenCode

3.56%
按下载量换算7

安全审计

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权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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