Backlink Discovery

Q: What does the Backlink Discovery AI skill do?

外链机会发现引擎。用户输入目标网址，立即用 web_search 开始多轮关键词派生搜索， 目标发现 300 个相关平台后自动停止，结果存入该网址专属数据库。 不限外链方式（论坛/GitHub/Wiki/目录等），只发现不执行。 触发：用户提供网址，说"发现外链"、"找外链机会"、"发现外链机会"。

Q: Why use Backlink Discovery on TypingMind?

Because you install it once and use it with any model. Backlink Discovery 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.

Q: How do I install Backlink Discovery in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kennyzir/7deer_skills/tree/main/backlink-discovery. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Q: Which AI models can use Backlink Discovery?

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.

Q: How many AI models can I use with Backlink Discovery?

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

Q: Is the Backlink Discovery AI skill free?

Yes. It is published on GitHub by kennyzir under the MIT license. You only pay your own AI provider for the tokens you use.

Q: 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.

Q: 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.

Community

kennyzir

backlink-discovery

外链机会发现引擎。用户输入目标网址，立即用 web_search 开始多轮关键词派生搜索，目标发现 300 个相关平台后自动停止，结果存入该网址专属数据库。不限外链方式（论坛/GitHub/Wiki/目录等），只发现不执行。触发：用户提供网址，说"发现外链"、"找外链机会"、"发现外链机会"。

Overview

Publisher	kennyzir
Repository	`7deer_skills`
Skill name	`backlink-discovery`
Stars	329
Forks	143
Bundled files	4
License	MIT
Links	Skill source Repository Homepage

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.
4 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by kennyzir on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/kennyzir/7deer_skills/tree/main/backlink-discovery
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.

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/kennyzir/7deer_skills.git /tmp/7deer_skills
mkdir -p .claude/skills
cp -r /tmp/7deer_skills/backlink-discovery .claude/skills/backlink-discovery

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Backlink Discovery 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 Backlink Discovery 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 Backlink Discovery 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.

Backlink Discovery — 外链机会发现引擎

核心逻辑

每个 URL = 独立发现任务，目标 300 个平台。


用户输入 https://xxx.com
  → 立即用 web_search 开始前台搜索
  → 多轮关键词派生，持续发现
  → 达到 300 个平台后停止
  → 结果存入数据库

下次输入 https://yyy.com
  → 新的独立发现任务
  → 各自数据库，互不干扰

触发方式


发现 https://xxx.com 的外链机会（目标300个）

执行流程（前台 web_search）

Step 1：接收任务，提取种子关键词

解析目标 URL，实时提取种子关键词（不写死）：


https://robloxcalc.com
  ↓
种子关键词：roblox, calculator, math, lua, game, game calculator, gaming, education, tool

Step 2：多轮 web_search（前台执行）

每轮用 web_search 搜索 8-12 个查询，从结果提取平台域名 → 分类 → 判断相关度。

搜索词思路要宽，不要只搜"xxx alternatives"：

竞品 + "free tools list"
竞品 + "directory submit"
竞品 + "community"
竞品 + "tutorial resources"
竞品 + "wiki"
竞品 + "github awesome list"
竞品 + "for kids/math/education"
竞品 + "game dev"
竞品 + "fan sites blogs"
竞品 + "similar games"
竞品 + "submit free"

每轮结束后从发现结果中派生新关键词 → 进入下一轮。

停止条件：

达到 300 个平台 → 停止
连续 2 轮无新发现 → 停止

Step 3：结果写入数据库

每个 URL 独立数据库目录：


memory/backlink-discovery/{提取的域名}/
├── platforms.json      # 所有发现平台（含相关度、方式分类）
└── summary.md         # 汇总报告

Step 4：返回结果

发现完成后返回：

总平台数 + P0/P1/P2 分布
外链方式分布
Top 10 高相关平台
数据存放路径

用户查询时读数据库返回最新状态。

数据库读取


查询 https://xxx.com 的外链发现结果
→ 读 memory/backlink-discovery/xxx_com/platforms.json
→ 返回 P0/P1/P2 分类 + 外链方式分布 + 完成状态

平台分类体系

分类	相关度	说明
🔴 P0	≥0.7	主题高度相关，明显外链机会
🟡 P1	0.4-0.7	较相关，可尝试
🟢 P2	<0.4	关联一般

外链方式分类

方式	适用平台
forum_post	Reddit、Discord、GameFAQs 等社区
github_pr	GitHub Awesome Lists、资源列表
wiki_edit	Wikipedia、Fandom Wiki
alternatives_article	Alternatives/对比文章站
directory_submit	目录站、产品提交页
guest_post	Dev.to、Hashnode、技术博客
email_outreach	有联系邮箱的任意平台
social_post	Twitter、LinkedIn
manual_review	其他方式

输出格式


# {网站} 外链机会发现报告

## 发现状态
- 状态：已完成
- 平台库：X / 300 个
- 发现时间：时间

## 🔴 P0 高相关平台（X 个）
[表格]

## 🟡 P1 中相关平台（X 个）
[按类型分组列出]

## 🟢 P2 低相关平台（X 个）

## 📊 外链方式分布
- Forum 发帖：X 个
- GitHub PR：X 个
- Alternatives Outreach：X 个
- 目录提交：X 个
- 其他：X 个

## 🔄 下一步
建议执行 backlink-executor 处理 P0 平台

注意事项

前台执行 — 用 web_search 直接跑，不用 sessions_spawn（Playwright 会被搜索引擆拦截）
思路要宽 — 游戏、教育、工具、社区、博客、GitHub、Wiki 都是外链来源
不要笃定"到顶了" — 相关平台数量往往比第一眼预估的多很多
每个 URL 独立任务 — 不同 URL 互不干扰
目标 300 个平台 — 达到后自动停止
只发现不执行 — 执行放 backlink-executor
长期积累 — 数据库不覆盖，持续追加

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 Backlink Discovery AI skill do?

Why use Backlink Discovery on TypingMind?

Because you install it once and use it with any model. Backlink Discovery 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 Backlink Discovery in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kennyzir/7deer_skills/tree/main/backlink-discovery. 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 Backlink Discovery?

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 Backlink Discovery?

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

Is the Backlink Discovery AI skill free?

Yes. It is published on GitHub by kennyzir 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Backlink Discovery — 外链机会发现引擎

核心逻辑

触发方式

执行流程（前台 web_search）

Step 1：接收任务，提取种子关键词

Step 2：多轮 web_search（前台执行）

Step 3：结果写入数据库

Step 4：返回结果

数据库读取

平台分类体系

外链方式分类

输出格式

注意事项

Bundled files

Frequently asked questions

Related AI Skills

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