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Agent Skill · 开发

litestar-dto(莱特星 DTO)

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

litestar-dto 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 21,708。

总安装 18周安装 17GitHub Stars 5下载 140核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:litestar-dto(莱特星 DTO)
来源仓库:https://github.com/alti3/litestar-skills
仓库路径:skills/litestar-dto
安装命令:
npx skills add https://github.com/alti3/litestar-skills --skill litestar-dto
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。

skills.shnpx skills
npx skills add https://github.com/alti3/litestar-skills --skill litestar-dto

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于辅助测试设计、自动化测试、用例整理和回归验证。适合编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需确认项目测试框架、运行命令和夹具数据,避免误改真实逻辑。涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。安装方式:通过 GitHub 仓库添加,需确认权限与操作边界。

来源仓库内路径:skills/litestar-dto

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/alti3/litestar-skills --skill litestar-dto;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

litestar-dto 怎么安装?

在终端执行 npx skills add https://github.com/alti3/litestar-skills --skill litestar-dto。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

litestar-dto 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

litestar-dto 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

litestar-dto 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

litestar-dto 用的人多吗?

公开数据是累计安装 18 次,近一周安装 17 次,下载 140 次,GitHub 5 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

litestar-dto 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
litestar-dto

莱特星 DTO · 本页

185需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

DTO

Use this skill when request and response payloads need explicit shape control, field-level policy, or DTO factory customization.

Execution Workflow

  1. Start with the handler contract: define inbound (dto) and outbound (return_dto) behavior explicitly.
  2. Choose DTO factory type for your model ecosystem (for example, DataclassDTO, SQLAlchemyDTO, or plugin-provided DTOs).
  3. Define policy with DTOConfig (exclude, rename, nesting depth, unknown-field handling, PATCH behavior).
  4. Apply DTOs at the correct layer (handler, controller, router, or app) and rely on closest-layer precedence.
  5. Use DTOData[T] in write/update handlers when you need controlled instantiation and patching semantics.
  6. Validate wrappers and envelopes (Response[T], pagination, generic wrappers) to ensure DTO transformation is still applied.
  7. Implement a custom AbstractDTO only when factory DTOs cannot express required behavior.

Implementation Rules

  • Keep read and write DTOs separate when policies differ.
  • Keep DTO configuration explicit and reviewable; avoid implicit field exposure.
  • Treat nested serialization depth as an API and performance control, not a default.
  • Reject unknown fields (forbid_unknown_fields=True) in stricter API surfaces.
  • Use DTOs to enforce immutability and server-owned fields (id, audit fields).
  • Keep handler logic focused on business behavior, not ad-hoc payload transformation.

DTO Basics: Layering and Parameters

Litestar exposes two DTO parameters on each app layer:

  • dto: inbound parsing for handler data; if return_dto is not set, this is also used for outbound serialization.
  • return_dto: outbound serialization policy only.

DTOs can be declared on handler, controller, router, or application. The DTO closest to the handler in the ownership chain applies.

Common pattern:

  • dto=WriteDTO to parse inbound payloads.
  • return_dto=ReadDTO to serialize outbound payloads.
  • return_dto=None on handlers where DTO serialization should be disabled (for example, DELETE -> None).

DTOConfig Policy Guide

Use DTOConfig to define stable contract rules:

  • exclude={...}: remove fields (supports nested paths, including list-item paths such as "pets.0.id").
  • rename_fields={...}: rename specific fields.
  • rename_strategy="camel" (or callback): apply systematic renaming.
  • max_nested_depth: control nested parsing/serialization depth (1 default shown in docs).
  • forbid_unknown_fields=True: reject extra payload fields instead of silently ignoring them.
  • partial=True: PATCH-friendly DTO behavior.
  • leading_underscore_private=False only when you intentionally want underscore-prefixed fields treated as public.
  • experimental_codegen_backend=False to selectively disable codegen backend behavior.

Important behavior:

  • Explicit rename_fields mappings are not further transformed by rename_strategy.

Field Marking and Access Control

Use dto_field(...) metadata to mark model fields with DTO semantics:

  • "private": not parsed from inbound data and never serialized in outbound data.
  • "read-only": not parsed from inbound data.

Also note:

  • Fields with leading underscores are implicitly private by default.

DTOData[T]: Controlled Create and Update Flows

Use DTOData[T] for create/update handlers that need controlled model mutation:

  • data.create_instance(...) creates model instances from validated input and can inject server-side values.
  • Nested values can be supplied with double-underscore paths (for example, address__id=...) when excluded nested fields must still be set.
  • data.update_instance(existing) supports partial updates cleanly for PATCH workflows when partial=True.

PATCH pattern:

  • Exclude immutable/server-owned fields (for example, id) in DTO config.
  • Use DTOData.update_instance() to apply only submitted fields.

Wrapper and Envelope Handling

DTO factory types can transform data inside supported wrappers:

  • Generic wrapper dataclasses (for example, WithCount[T]) when one type parameter maps to DTO-supported model data.
  • Litestar pagination wrappers such as ClassicPagination[T] (DTO applies to items).
  • Response[T] wrappers (DTO applies to content).

Performance Notes

DTO codegen backend:

  • Introduced in 2.2.0, stabilized and enabled by default in 2.8.0.
  • Can be toggled per DTO with DTOConfig(experimental_codegen_backend=...).

Use selective override only when debugging compatibility or behavior differences.

AbstractDTO and Custom DTO Classes

Use built-in DTO factories first. Create custom DTO classes only when required behavior is not expressible via existing DTO factories + DTOConfig.

When implementing custom DTOs, you must implement AbstractDTO methods:

  • generate_field_definitions(model_type): yield DTOFieldDefinition objects for DTO-visible fields.
  • detect_nested_field(field_definition): return whether the field represents nested model data.

This is the minimal protocol Litestar requires for custom DTO implementations.

Example Patterns

from litestar import get, patch
from litestar.dto import DTOConfig, DTOData, DataclassDTO

class UserReadDTO(DataclassDTO[User]):
    config = DTOConfig(exclude={"password_hash"})

class UserPatchDTO(DataclassDTO[User]):
    # Patch DTO excludes immutable id and accepts partial payloads.
    config = DTOConfig(exclude={"id"}, partial=True)

@get("/users/{user_id:int}", return_dto=UserReadDTO)
async def get_user(user_id: int) -> User:
    return ...

@patch("/users/{user_id:int}", dto=UserPatchDTO, return_dto=UserReadDTO)
async def patch_user(user_id: int, data: DTOData[User]) -> User:
    user = ...
    return data.update_instance(user)
from litestar.dto import DTOConfig
from litestar.plugins.sqlalchemy import SQLAlchemyDTO

class PublicUserDTO(SQLAlchemyDTO[User]):
    config = DTOConfig(exclude={"password_hash"})

Validation Checklist

  • Confirm dto and return_dto are intentionally selected (or explicitly disabled) per handler.
  • Confirm layer precedence does not accidentally override handler-level DTO intent.
  • Confirm exclude/rename/nesting config generates expected payload shape.
  • Confirm unknown field behavior matches API strictness (forbid_unknown_fields).
  • Confirm private/read-only/underscore fields are not writable by clients.
  • Confirm PATCH handlers use partial=True + DTOData.update_instance() where appropriate.
  • Confirm wrapper responses (Response, pagination, generic envelopes) still apply DTO transformations.
  • Confirm OpenAPI output matches the DTO-shaped contract.

Cross-Skill Handoffs

  • Use litestar-dataclasses, litestar-plugins, or litestar-custom-types for model ecosystem specifics.
  • Use litestar-databases when DTO behavior couples to SQLAlchemy or Piccolo persistence design.
  • Use litestar-openapi to verify generated schema accuracy after DTO changes.
  • Use litestar-requests and litestar-responses for transport-level behavior outside DTO transformation.

Litestar References

平台分布

Codex

36.89%
按下载量换算52

Claude

29.71%
按下载量换算42

Cursor

19.99%
按下载量换算28

Gemini CLI

8.19%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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