Docs Lookup logo

Docs Lookup

Community
ProgrammerAnthony
docs-lookup

通过 Context7 MCP 获取库和框架的实时最新文档,而非依赖训练数据,防止 API 幻觉。适用于查询任何库或框架的用法、配置、示例代码。触发词:怎么用、怎么配置、API参考、文档、示例代码、用法、接口、库文档、框架文档、documentation、docs、how to use、API reference、setup、configure、React怎么用、Next.js配置、Prisma查询、Vue用法、Express路由、Tailwind类名、Supabase认证、TypeScript类型、Zod验证、shadcn组件、Drizzle ORM、tRPC、Fastify、NestJS、Astro、SvelteKit、Nuxt、Vite、Vitest、Playwright。

Overview

PublisherProgrammerAnthony
RepositoryExpert-Coding-Harness
Skill namedocs-lookup
Stars
236
Forks
77
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 ProgrammerAnthony on GitHub. Read the source before you install it.

Installation

Install the Docs Lookup 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.
  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/ProgrammerAnthony/Expert-Coding-Harness.git /tmp/Expert-Coding-Harness
mkdir -p .claude/skills
cp -r /tmp/Expert-Coding-Harness/skills/docs-lookup .claude/skills/docs-lookup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Docs Lookup 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 Docs Lookup 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 Docs Lookup 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.

文档查询

铁律:查文档,不靠记忆。 当用户询问任何库、框架或 API 的用法时,必须通过 Context7 MCP 获取实时文档,而非依赖训练数据给出可能已过时的答案。

何时触发

  • 用户询问某个库或框架的用法("React 的 useEffect 怎么用?")
  • 用户要求生成依赖特定库的代码("帮我写一个 Prisma 查询")
  • 用户询问 API 参考或配置方式("Next.js middleware 怎么配置?")
  • 用户提到了具体的库名(React、Vue、Next.js、Prisma、Supabase、Tailwind 等)
  • 用户询问某个库的特定版本行为("Next.js 15 的 App Router")

工作流

第一步:解析库 ID

调用 Context7 MCP 的 resolve-library-id 工具:

  • libraryName:从用户问题中提取的库名(如 Next.jsPrismaSupabase
  • query:用户的完整问题(提升匹配相关性)

必须先获得有效的 Context7 库 ID(格式为 /org/project)才能进入下一步,禁止直接调用 query-docs。

第二步:选择最佳匹配

从解析结果中按以下优先级选择:

优先级判断依据
1名称与用户所问库完全匹配
2Benchmark 分数更高(100 分为满分)
3Source reputation 为 High 或 Medium
4若用户指定了版本号,优先选版本专属 ID

第三步:获取文档

调用 Context7 MCP 的 query-docs 工具:

  • libraryId:第二步选出的库 ID(如 /vercel/next.js
  • query:用户的具体问题,越具体越好

限制:每个问题最多调用 query-docs 3 次。3 次后仍不确定,说明情况并用已有最佳信息作答,不得猜测。

第四步:回答用户

  • 用获取到的实时文档内容回答问题
  • 包含文档中的相关代码示例
  • 涉及版本差异时明确标注(如"在 Next.js 15 中...")

示例

示例 1:Next.js middleware 配置

  1. 调用 resolve-library-idlibraryName: "Next.js"query: "Next.js middleware 怎么配置?"
  2. 从结果中选 /vercel/next.js(名称匹配 + 高分)
  3. 调用 query-docslibraryId: "/vercel/next.js"query: "middleware configuration"
  4. 用返回的文档和 middleware.ts 示例回答

示例 2:Prisma 关联查询

  1. 调用 resolve-library-idlibraryName: "Prisma"query: "如何查询关联关系?"
  2. /prisma/prisma
  3. 调用 query-docsquery: "query with relations include select"
  4. 返回 Prisma Client 的 include / select 模式与代码示例

示例 3:Supabase 认证方式

  1. 调用 resolve-library-idlibraryName: "Supabase"query: "Supabase 有哪些认证方式?"
  2. 选 Supabase 官方库 ID
  3. 调用 query-docs,汇总认证方法并给出最小示例

最佳实践

原则说明
具体查询用用户完整问题作为 query,比通用词更准确
版本感知用户提到版本时,优先选版本专属库 ID
官方优先多个匹配时优先选官方/主包,而非社区 fork
不传密钥在调用 resolve-library-id 或 query-docs 前,移除问题中的 API Key、密码、Token 等敏感信息

反模式

反模式后果
跳过 resolve-library-id 直接猜测库 IDquery-docs 返回错误或无关文档
用训练数据直接回答库 API 问题给出已过时或错误的 API 用法
query 过于模糊(如只写库名)返回的文档片段不相关
超过 3 次仍继续调用浪费 context,应直接说明不确定性
将含敏感数据的问题原文发送 Context7泄露用户凭证

Frequently asked questions

What does the Docs Lookup AI skill do?

通过 Context7 MCP 获取库和框架的实时最新文档,而非依赖训练数据,防止 API 幻觉。适用于查询任何库或框架的用法、配置、示例代码。触发词:怎么用、怎么配置、API参考、文档、示例代码、用法、接口、库文档、框架文档、documentation、docs、how to use、API reference、setup、configure、React怎么用、Next.js配置、Prisma查询、Vue用法、Express路由、Tailwind类名、Supabase认证、TypeScript类型、Zod验证、shadcn组件、Drizzle ORM、tRPC、Fastify、NestJS、Astro、SvelteKit、Nuxt、Vite、Vitest、Playwright。

Why use Docs Lookup on TypingMind?

Because you install it once and use it with any model. Docs Lookup 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 Docs Lookup in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ProgrammerAnthony/Expert-Coding-Harness/tree/master/skills/docs-lookup. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Docs Lookup?

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 Docs Lookup?

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

Is the Docs Lookup AI skill free?

Yes. It is published on GitHub by ProgrammerAnthony 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇