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Dingyi Edu Radar

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dingyi-edu-radar

查询教育邮箱(.edu 邮箱)相关两类信息:(1) 用 edu 邮箱能享受哪些产品/服务的教育优惠、学生折扣或免费福利;(2) 各大学/院校的 edu 邮箱怎么申请。当用户询问某个网站/软件/AI 产品有没有学生优惠、教育优惠、免费教育版,或反过来问"有哪些教育邮箱能用 X"、"edu 邮箱能享受哪些产品"、"学生认证怎么做",或问"美国/某地有哪些大学能申请 edu 邮箱"、"XX 大学的 edu 邮箱怎么拿"、"校友邮箱怎么申请"时使用本 skill。覆盖 Replit、Notion、Figma、JetBrains、GitHub Copilot、ChatGPT、Grok、Gemini、MATLAB、Adobe、Perplexity 等 150+ 产品优惠,以及 70+ 所美国院校(含社区大学、州立大学、校友邮箱)和加澳澳德日台越等地院校的 edu 邮箱申请方法。数据来源于 https://www.edumails.cn/us 和 https://www.edumails.cn/edu 。本 skill 仅提供官方教育优惠与合法 edu 邮箱申请的信息查询,不提供任何盗用身份、伪造学生资格或规避认证的内容。

Overview

Publisherdingyi
Repositorydingyi-edu-radar-skill
Skill namedingyi-edu-radar
Stars
90
Forks
9
Bundled files
253
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.

  • 253 bundled files

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

  • Open source

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

Installation

Install the Dingyi Edu Radar 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/dingyi/dingyi-edu-radar-skill/tree/main/skills/dingyi-edu-radar
  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/dingyi/dingyi-edu-radar-skill.git /tmp/dingyi-edu-radar-skill
mkdir -p .claude/skills
cp -r /tmp/dingyi-edu-radar-skill/skills/dingyi-edu-radar .claude/skills/dingyi-edu-radar
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dingyi Edu Radar 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 Dingyi Edu Radar 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 Dingyi Edu Radar 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.

edu-rader — 教育邮箱优惠查询

本 skill 内置了 edumails.cn 两个分类下 249 篇图文教程的完整内容(每周自动刷新):

  • /us(edu 国外优惠):用 .edu 邮箱能享受的产品优惠——AI 工具、开发工具、设计软件、效率办公、学术科研、影音、购物等。
  • /edu(edu 邮箱申请):各大学/院校的 edu 邮箱申请方法——含 70+ 所美国院校(社区大学、州立大学、校友邮箱等),以及加拿大、澳大利亚、德国、日本、台湾、越南等地的院校。

你的任务

用户通常会问三类问题:

  1. 优惠查询:「Replit 有没有教育优惠?」「edu 邮箱能用 Notion 吗?」「学生怎么免费拿 ChatGPT?」—— 给出该产品具体的优惠方案、价格、申请/认证步骤。
  2. 反向查询:「edu 邮箱能享受哪些 AI 工具?」「有哪些教育邮箱能用的编程工具?」—— 列出该类别下可用的产品及优惠。
  3. edu 邮箱申请查询:「美国有哪些大学能申请 edu 邮箱?」「怎么拿加州大学的 edu 邮箱?」「校友邮箱怎么申请?」—— 列出可申请的院校 + 各自的申请方法(学校官网、申请入口、邮箱后缀、审核速度、附赠权益如 Office/OneDrive)。

工作流程

第 1 步:定位文章

先读取 catalog.json(249 条,含 slug / title / kw / file)。根据用户提到的产品名、网站名、公司名、院校名或类别关键词,匹配一条或多条记录。匹配要点:

  • 产品名有多种写法,做宽松匹配:github copilot ↔ copilot;谷歌 ↔ google ↔ gemini;印象笔记 ↔ evernote;可画 ↔ canva。
  • 用户说类别(如"AI 工具""编程工具""设计软件")时,按 kw 字段里的类别词筛选多条。
  • 找不到精确匹配时,按产品所属公司/领域联想,并在 catalog.json 里搜索相关关键词(如用户问"音乐 AI",匹配 suno、udio)。

第 2 步:读取详情

对匹配到的每条记录,读取 references/<slug>.md 拿到完整的优惠方案、价格、注册与认证步骤、常见问题、注意事项。

如果一条都不匹配,不要编造——明确告诉用户该产品/院校不在已收录的内容内,可建议去 https://www.edumails.cn/us 或 https://www.edumails.cn/edu 直接搜索,或改用通用学生认证平台(SheerID / UNiDAYS / Student Beans)尝试。

第 3 步:组织回答

回答要点(基于文章实际内容,不要发挥):

  • 优惠结论先行:免费 / 几折 / 多少额度 / 多长期限。例:「Replit 用 .edu 邮箱验证后 Core 版 5 折,$10/月(原价 $20/月)」。
  • 关键条件:需要哪种 edu 邮箱(部分要求美国 .edu)、是否需要二验(SheerID)、是否需要绑卡。
  • 申请步骤:按文章里的「注册账号 → 优惠认证 → 常见问题」顺序给出可操作的步骤,附上文章里提到的官方认证链接。
  • 常见坑/失败案例:如果文章里有「失败案例」「常见问题」章节,提炼关键提醒。
  • 给出来源链接(文章里的 来源: URL),方便用户核对。

反向查询("有哪些")时,按类别分组列出产品 + 一句话优惠,不要逐条贴全文。

内容位置

  • catalog.json — 249 条索引(slug / title / kw / file),第一步总是先读它。
  • references/<slug>.md — 每个产品/主题的完整教程,按需读取。
  • CATALOG.md — 目录的人类可读版本(可选参考)。

重要约束

  • 全部内容来自 edumails.cn,优惠可能随时间失效(很多是限时活动)。回答时提醒用户"优惠信息有时效,以官网为准",并附来源链接。
  • 不要混入训练数据里关于这些产品的其他信息——只依据 references 里的内容作答。如果用户追问文章里没有的细节,直说"收录的教程里没提到"。
  • 文章原文是繁简混排的中文,引用步骤时用简体中文转述即可,保留关键英文术语和链接。

合规边界(必须遵守)

本 skill 的目的是查询产品的官方教育优惠、以及查询如何合法申请 edu 邮箱,仅作信息索引。回答时遵守:

  • 只介绍官方教育优惠和合法的 edu 邮箱申请途径(学校官方注册入口、官方学生认证 SheerID/UNiDAYS 等)。
  • 不提供任何盗用他人身份、冒用他人学生资格、伪造学历/学籍、批量注册、买卖来路不明的 edu 邮箱、或规避官方认证审核的内容与方法。
  • 如果用户明确要求上述违规内容(如"怎么伪造学生证""怎么盗用别人的 edu 邮箱""批量刷号教程"),拒绝回答,并说明本 skill 不提供此类信息。
  • references 教程原文中若出现"白嫖""薅羊毛"等口语化措辞,那是源站原文的表述;引用时用中性词转述(如"免费教育版""可享受的优惠"),不渲染、不鼓励违规获取。

内容刷新

本 skill 的内容每周一 03:00 由 macOS launchd 自动增量刷新(任务名 cn.bao.edumails-rader-refresh),日志见 scripts/refresh.log。也可手动刷新:

  • scripts/refresh.sh — 增量更新(只拉新文章,保留现有)
  • scripts/refresh.sh --full — 全量重建

如用户反映某条优惠已失效或缺失,可手动跑一次刷新再核对。如果用户问"数据多久没更新",读 scripts/refresh.log 末尾的时间戳回答。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

and 140 more files.

Frequently asked questions

What does the Dingyi Edu Radar AI skill do?

查询教育邮箱(.edu 邮箱)相关两类信息:(1) 用 edu 邮箱能享受哪些产品/服务的教育优惠、学生折扣或免费福利;(2) 各大学/院校的 edu 邮箱怎么申请。当用户询问某个网站/软件/AI 产品有没有学生优惠、教育优惠、免费教育版,或反过来问"有哪些教育邮箱能用 X"、"edu 邮箱能享受哪些产品"、"学生认证怎么做",或问"美国/某地有哪些大学能申请 edu 邮箱"、"XX 大学的 edu 邮箱怎么拿"、"校友邮箱怎么申请"时使用本 skill。覆盖 Replit、Notion、Figma、JetBrains、GitHub Copilot、ChatGPT、Grok、Gemini、MATLAB、Adobe、Perplexity 等 150+ 产品优惠,以及 70+ 所美国院校(含社区大学、州立大学、校友邮箱)和加澳澳德日台越等地院校的 edu 邮箱申请方法。数据来源于 https://www.edumails.cn/us 和 https://www.edumails.cn/edu 。本 skill 仅提供官方教育优惠与合法 edu 邮箱申请的信息查询,不提供任何盗用身份、伪造学生资格或规避认证的内容。

Why use Dingyi Edu Radar on TypingMind?

Because you install it once and use it with any model. Dingyi Edu Radar 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 Dingyi Edu Radar in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dingyi/dingyi-edu-radar-skill/tree/main/skills/dingyi-edu-radar. 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 Dingyi Edu Radar?

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 Dingyi Edu Radar?

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

Is the Dingyi Edu Radar AI skill free?

Yes. It is published on GitHub by dingyi 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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