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litestar-debugging莱特星调试

Agent Skill

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。

总安装

364

周安装

15

GitHub Stars

5

下载量

119
CodexClaudeCursorGemini CLI

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

unknown

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

简介

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。

SKILL.md

Debugging

Execution Workflow

  1. Reproduce the issue with the smallest possible app, route, or test case.
  2. Identify the failing layer first: requests, routing, dependency injection, middleware, auth, responses, exception handling, or lifecycle.
  3. Turn on only the minimum safe diagnostics needed: local debug=True, focused logs, or temporary assertions.
  4. Inspect the boundary where the behavior diverges from expectation.
  5. Fix the root cause, remove temporary diagnostics, and add a regression test.
  6. Re-run the affected tests and re-check the surrounding contract for regressions.

Core Rules

  • Keep debug=True local-only.
  • Prefer deterministic logs, assertions, and focused reproduction apps over ad hoc print debugging.
  • Narrow the failing layer before changing code.
  • Use request and app loggers for evidence, not speculation.
  • Keep debug output free of secrets and sensitive payloads.
  • Remove temporary diagnostics once the root cause is understood.
  • Always codify the fix with a regression test when feasible.

Decision Guide

  • Use a tiny repro app when the existing app is too large to reason about quickly.
  • Use litestar-testing clients when the bug is observable through the HTTP or websocket contract.
  • Use litestar-logging when the main gap is missing evidence rather than a code defect.
  • Use debug=True only when local traceback detail materially shortens the investigation.
  • Hand off to the more specific Litestar skill once the failing subsystem is clear.

Reference Files

Read only the sections you need:

Recommended Defaults

  • Reproduce with the smallest route and the smallest input that still fails.
  • Keep one hypothesis at a time and test it quickly.
  • Add evidence before changing behavior.
  • Use logs to compare expected and actual values at subsystem boundaries.
  • Convert the repro into a stable test once the bug is found.

Anti-Patterns

  • Leaving debug=True or verbose diagnostics enabled after the fix.
  • Changing several subsystems at once before isolating the failure.
  • Catching broad exceptions to hide symptoms instead of understanding them.
  • Assuming a request, auth, or response bug without reproducing the exact contract.
  • Logging secrets, tokens, or raw sensitive request bodies during debugging.

Validation Checklist

  • Confirm the issue reproduces before the fix and stops reproducing after it.
  • Confirm both happy-path and failure-path contracts still behave correctly.
  • Confirm no sensitive values are leaked by temporary or permanent diagnostics.
  • Confirm the regression test fails before the fix and passes after it.
  • Confirm temporary debugging code is removed.

Cross-Skill Handoffs

  • Use litestar-logging when better evidence collection is the main need.
  • Use litestar-testing to codify the repro and lock the fix.
  • Use litestar-requests, litestar-responses, litestar-exception-handling, or litestar-authentication once the failing boundary is known.
  • Use litestar-metrics only after the runtime bug is understood and ongoing visibility is needed.

Litestar References

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

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

展示第三方安全扫描或审计结果

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

Codex

36.61%
按下载量换算44

Claude

30.82%
按下载量换算37

Cursor

16.73%
按下载量换算20

Gemini CLI

8.76%
按下载量换算10

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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