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Search First

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xu-xiang
search-first

研究优先于编码的工作流程。在编写自定义代码之前,搜索现有的工具、库和模式。调用研究员代理。

Overview

Publisherxu-xiang
Repositoryeverything-claude-code-zh
Skill namesearch-first
Stars
2K
Forks
325
Bundled files
Instructions only
LicenseMIT
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by xu-xiang on GitHub. Read the source before you install it.

Installation

Install the Search First 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/xu-xiang/everything-claude-code-zh/tree/main/docs/zh-CN/skills/search-first
  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/xu-xiang/everything-claude-code-zh.git /tmp/everything-claude-code-zh
mkdir -p .claude/skills
cp -r /tmp/everything-claude-code-zh/docs/zh-CN/skills/search-first .claude/skills/search-first
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Search First 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 Search First 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 Search First 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.

/search-first — 编码前先研究

系统化“在实现之前先寻找现有解决方案”的工作流程。

触发时机

在以下情况使用此技能:

  • 开始一项很可能已有解决方案的新功能
  • 添加依赖项或集成
  • 用户要求“添加 X 功能”而你准备开始编写代码
  • 在创建新的实用程序、助手或抽象之前

工作流程

┌─────────────────────────────────────────────┐
│  1. NEED ANALYSIS                           │
│     Define what functionality is needed      │
│     Identify language/framework constraints  │
├─────────────────────────────────────────────┤
│  2. PARALLEL SEARCH (researcher agent)      │
│     ┌──────────┐ ┌──────────┐ ┌──────────┐  │
│     │  npm /   │ │  MCP /   │ │  GitHub / │  │
│     │  PyPI    │ │  Skills  │ │  Web      │  │
│     └──────────┘ └──────────┘ └──────────┘  │
├─────────────────────────────────────────────┤
│  3. EVALUATE                                │
│     Score candidates (functionality, maint, │
│     community, docs, license, deps)         │
├─────────────────────────────────────────────┤
│  4. DECIDE                                  │
│     ┌─────────┐  ┌──────────┐  ┌─────────┐  │
│     │  Adopt  │  │  Extend  │  │  Build   │  │
│     │ as-is   │  │  /Wrap   │  │  Custom  │  │
│     └─────────┘  └──────────┘  └─────────┘  │
├─────────────────────────────────────────────┤
│  5. IMPLEMENT                               │
│     Install package / Configure MCP /       │
│     Write minimal custom code               │
└─────────────────────────────────────────────┘

决策矩阵

信号行动
完全匹配,维护良好,MIT/Apache 许可证采纳 — 直接安装并使用
部分匹配,基础良好扩展 — 安装 + 编写薄封装层
多个弱匹配组合 — 组合 2-3 个小包
未找到合适的构建 — 编写自定义代码,但需基于研究

使用方法

快速模式(内联)

在编写实用程序或添加功能之前,在脑中过一遍:

  1. 这是常见问题吗? → 搜索 npm/PyPI
  2. 有相关的 MCP 吗? → 检查 ~/.claude/settings.json 并搜索
  3. 有相关的技能吗? → 检查 ~/.claude/skills/
  4. 有 GitHub 模板吗? → 搜索 GitHub

完整模式(代理)

对于非平凡的功能,启动研究员代理:

Task(subagent_type="general-purpose", prompt="
  Research existing tools for: [DESCRIPTION]
  Language/framework: [LANG]
  Constraints: [ANY]

  Search: npm/PyPI, MCP servers, Claude Code skills, GitHub
  Return: Structured comparison with recommendation
")

按类别搜索快捷方式

开发工具

  • Linting → eslint, ruff, textlint, markdownlint
  • Formatting → prettier, black, gofmt
  • Testing → jest, pytest, go test
  • Pre-commit → husky, lint-staged, pre-commit

AI/LLM 集成

  • Claude SDK → 使用 Context7 获取最新文档
  • 提示词管理 → 检查 MCP 服务器
  • 文档处理 → unstructured, pdfplumber, mammoth

数据与 API

  • HTTP 客户端 → httpx (Python), ky/got (Node)
  • 验证 → zod (TS), pydantic (Python)
  • 数据库 → 首先检查是否有 MCP 服务器

内容与发布

  • Markdown 处理 → remark, unified, markdown-it
  • 图片优化 → sharp, imagemin

集成点

与规划器代理

规划器应在阶段 1(架构评审)之前调用研究员:

  • 研究员识别可用的工具
  • 规划器将它们纳入实施计划
  • 避免在计划中“重新发明轮子”

与架构师代理

架构师应向研究员咨询:

  • 技术栈决策
  • 集成模式发现
  • 现有参考架构

与迭代检索技能

结合进行渐进式发现:

  • 循环 1:广泛搜索 (npm, PyPI, MCP)
  • 循环 2:详细评估顶级候选方案
  • 循环 3:测试与项目约束的兼容性

示例

示例 1:“添加死链检查”

Need: Check markdown files for broken links
Search: npm "markdown dead link checker"
Found: textlint-rule-no-dead-link (score: 9/10)
Action: ADOPT — npm install textlint-rule-no-dead-link
Result: Zero custom code, battle-tested solution

示例 2:“添加 HTTP 客户端包装器”

Need: Resilient HTTP client with retries and timeout handling
Search: npm "http client retry", PyPI "httpx retry"
Found: got (Node) with retry plugin, httpx (Python) with built-in retry
Action: ADOPT — use got/httpx directly with retry config
Result: Zero custom code, production-proven libraries

示例 3:“添加配置文件 linter”

Need: Validate project config files against a schema
Search: npm "config linter schema", "json schema validator cli"
Found: ajv-cli (score: 8/10)
Action: ADOPT + EXTEND — install ajv-cli, write project-specific schema
Result: 1 package + 1 schema file, no custom validation logic

反模式

  • 直接跳转到编码:不检查是否存在就编写实用程序
  • 忽略 MCP:不检查 MCP 服务器是否已提供该能力
  • 过度定制:对库进行如此厚重的包装以至于失去了其优势
  • 依赖项膨胀:为了一个小功能安装一个庞大的包

Frequently asked questions

What does the Search First AI skill do?

研究优先于编码的工作流程。在编写自定义代码之前,搜索现有的工具、库和模式。调用研究员代理。

Why use Search First on TypingMind?

Because you install it once and use it with any model. Search First 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 Search First in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/xu-xiang/everything-claude-code-zh/tree/main/docs/zh-CN/skills/search-first. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Search First?

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 Search First?

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

Is the Search First AI skill free?

Yes. It is published on GitHub by xu-xiang under the MIT 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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