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Debug Helper

Community
JackyST0
debug-helper

Help debug code by analyzing error messages, identifying root causes, and providing fix suggestions.

Overview

PublisherJackyST0
Repositoryawesome-agent-skills
Skill namedebug-helper
Stars
651
Forks
145
Bundled files
1
LicenseCC0-1.0
Links
  • 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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by JackyST0 on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/JackyST0/awesome-agent-skills/tree/main/examples/debug-helper
  4. 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.
2

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/JackyST0/awesome-agent-skills.git /tmp/awesome-agent-skills
mkdir -p .claude/skills
cp -r /tmp/awesome-agent-skills/examples/debug-helper .claude/skills/debug-helper
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Debug Helper 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 Debug Helper 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 Debug Helper 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.

Debug Helper

帮助调试代码,分析错误信息,定位问题根源,提供修复建议。

Help debug code by analyzing error messages, identifying root causes, and providing fix suggestions.

When to Use

当用户请求以下操作时使用此 skill:

  • 调试代码 / Debug code
  • 分析错误信息 / Analyze error messages
  • 修复 bug / Fix bugs
  • 理解异常原因 / Understand exception causes
  • 排查问题 / Troubleshoot issues

Instructions

调试步骤 / Debugging Steps

  1. 收集信息 - 获取错误信息、堆栈跟踪、相关代码
  2. 分析错误 - 理解错误类型和消息含义
  3. 定位根源 - 找到导致问题的代码位置
  4. 提供解决方案 - 给出具体的修复建议
  5. 预防建议 - 提供避免类似问题的建议

常见错误类型 / Common Error Types

错误类型可能原因
TypeError类型不匹配、空值操作
ReferenceError未定义变量、作用域问题
SyntaxError语法错误、缺少括号/引号
RuntimeError运行时逻辑错误
NetworkError网络请求失败、超时

分析框架 / Analysis Framework

对于每个错误,需要分析:

  • What: 发生了什么错误
  • Where: 错误发生在哪里
  • Why: 为什么会发生
  • How: 如何修复

输出格式 / Output Format

使用 templates/debug-report.md 模板格式化输出。

Use the templates/debug-report.md template to format output.

markdown
## 调试分析报告 / Debug Analysis Report

### 错误概述 / Error Summary
[错误类型和简要描述]

### 根本原因 / Root Cause
[详细分析]

### 修复方案 / Fix
[具体代码修改]

### 预防建议 / Prevention
[如何避免类似问题]

Examples

输入 / Input

错误信息:

TypeError: Cannot read properties of undefined (reading 'map')
    at UserList (UserList.jsx:15:23)
    at renderWithHooks (react-dom.development.js:14985:18)

相关代码:

jsx
function UserList({ users }) {
  return (
    <ul>
      {users.map(user => (
        <li key={user.id}>{user.name}</li>
      ))}
    </ul>
  );
}

输出 / Output

调试分析报告

错误概述

TypeError: Cannot read properties of undefined (reading 'map')

在 UserList 组件第 15 行调用 .map() 时,users 变量为 undefined。

根本原因

  1. 直接原因: 尝试在 undefined 上调用 .map() 方法
  2. 深层原因:
    • 父组件可能没有传递 users prop
    • 数据获取尚未完成时组件已渲染
    • API 返回格式与预期不符

修复方案

方案 1: 添加默认值(推荐)

jsx
function UserList({ users = [] }) {
  return (
    <ul>
      {users.map(user => (
        <li key={user.id}>{user.name}</li>
      ))}
    </ul>
  );
}

方案 2: 条件渲染

jsx
function UserList({ users }) {
  if (!users || users.length === 0) {
    return <p>No users found</p>;
  }

  return (
    <ul>
      {users.map(user => (
        <li key={user.id}>{user.name}</li>
      ))}
    </ul>
  );
}

方案 3: 可选链操作符

jsx
function UserList({ users }) {
  return (
    <ul>
      {users?.map(user => (
        <li key={user.id}>{user.name}</li>
      ))}
    </ul>
  );
}

预防建议

  1. 使用 TypeScript - 添加类型检查

    typescript
    interface Props {
      users: User[];
    }
  2. 添加 PropTypes - 运行时类型检查

    jsx
    UserList.propTypes = {
      users: PropTypes.array.isRequired
    };
  3. 检查数据源 - 确保父组件正确传递数据

  4. 处理加载状态 - 在数据获取期间显示加载指示器

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 Debug Helper AI skill do?

Help debug code by analyzing error messages, identifying root causes, and providing fix suggestions.

Why use Debug Helper on TypingMind?

Because you install it once and use it with any model. Debug Helper 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 Debug Helper in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/JackyST0/awesome-agent-skills/tree/main/examples/debug-helper. 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 Debug Helper?

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 Debug Helper?

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

Is the Debug Helper AI skill free?

Yes. It is published on GitHub by JackyST0 under the CC0-1.0 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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