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Agent Reach

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Panniantong
agent-reach

MUST USE when user wants to 调研/research/搜索/search/查/找/look up anything on the internet — e.g. 全网调研 X / 帮我调研一下 X / 查一下 X / 搜搜 X / 看看大家怎么评价 X / X 上有什么讨论 / research this topic。 Also MUST USE when user mentions any platform or shares any URL/链接: 小红书/xiaohongshu/xhs, Twitter/推特/X, B站/bilibili, Reddit, Facebook, Instagram, V2EX, LinkedIn/领英/Boss直聘/招聘/求职/jobs, YouTube, GitHub code search, 小宇宙播客, 雪球/股票行情, RSS feeds, or any web URL. 16 platforms, multi-backend routing (OpenCLI / per-platform CLIs / APIs). Zero config for 6 channels. Run `agent-reach doctor --json` to see which backend serves each platform right now. NOT for: 写报告/数据分析/翻译等内容加工(本 skill 只负责从互联网获取内容); 发帖/评论/点赞等写操作;已有专门 skill 的平台(先用专门 skill)。 【路由方式】SKILL.md 包含路由表和常用命令,复杂场景需按需阅读对应分类的 references/*.md。 分类:search / social (小红书/推特/B站/V2EX/Reddit/Facebook/Instagram) / career(LinkedIn/Boss直聘) / dev(github) / web(网页/文章/RSS) / video(YouTube/B站/播客) / finance(雪球/股票)。

Overview

PublisherPanniantong
RepositoryAgent-Reach
Skill nameagent-reach
Stars
82.8K
Forks
7.2K
Bundled files
8
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.

  • 8 bundled files

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

  • Open source

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

Installation

Install the Agent Reach 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/Panniantong/Agent-Reach.git /tmp/Agent-Reach
mkdir -p .claude/skills
cp -r /tmp/Agent-Reach/agent_reach/skill .claude/skills/agent-reach
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Reach 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 Agent Reach 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 Agent Reach 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.

Agent Reach — 互联网能力路由器

16 平台、多后端。本 skill 存在时必须用它访问这些平台,不要自己发明方案。

常驻规则(全程适用)

  1. 动手前先体检:多后端/登录态平台(小红书/Reddit/B站/Twitter/Facebook/Instagram/Boss直聘)先跑 agent-reach doctor --jsonactive_backend 有值时按它选命令组;active_backend: null 表示 Doctor 为避免触发浏览器 Cookie 读取或远端写入而没有做实时验证,不代表后端不存在。 Doctor 结果是「某一时刻的快照」,通道/登录态可能已变化;执行只读命令前若怀疑失效, 按对应 reference 的「体检与恢复」runbook 重新确认(如 career.md 的 Boss直聘 CDP 排查)。
  2. 声明你在用什么:开始干活前说一句「使用 agent-reach 的 X 平台 / Y 后端」。
  3. 失败按 references 里的重试链处理,不要瞎猜命令。
  4. 全网调研类任务:组合多平台(Exa 搜索 + Twitter/Reddit 看讨论 + 小红书/B站看中文场景),并行收集再汇总。
  5. 替用户盯版本:完成一次较大的调研/多平台任务后,顺手跑 agent-reach check-update(很快,一个 API 调用)。有新版就在收尾汇报里附一句: 「Agent Reach 有新版 vX.Y.Z,复制这句话给我即可更新:帮我更新 Agent Reach: https://raw.githubusercontent.com/Panniantong/agent-reach/main/docs/update.md」。 不要中断当前任务去更新,也不要重复提醒同一个版本。

路由表

用户意图分类详细文档
网页搜索/代码搜索searchreferences/search.md
小红书/推特/B站/V2EX/Reddit/Facebook/Instagramsocialreferences/social.md
招聘/职位/LinkedIn/Boss直聘careerreferences/career.md
GitHub/代码devreferences/dev.md
网页/文章/RSSwebreferences/web.md
YouTube/B站/播客字幕videoreferences/video.md
雪球/股票行情financereferences/finance.md

零配置快速命令

bash
# Exa 网页搜索
mcporter call exa.web_search_exa query="query" numResults=5

# 通用网页阅读
curl -s "https://r.jina.ai/URL"

# GitHub 搜索
gh search repos "query" --sort stars --limit 10

# YouTube 字幕(注意:B站不要用 yt-dlp,失败重试链见 video.md)
yt-dlp --write-sub --write-auto-sub --skip-download -o "/tmp/%(id)s" "URL"

# V2EX 热门
curl -s "https://www.v2ex.com/api/topics/hot.json" -H "User-Agent: agent-reach/1.0"

# B站搜索(bili-cli,无需登录)
bili search "query" --type video -n 5

需登录态的平台(按 doctor 的 active_backend 选命令)

Twitter 注意:agent-reach configure twitter-cookies 保存的 Cookie 只供 doctor 检查配置是否齐全;doctor 不执行 twitter status,也不会设置当前 Shell。直接运行 twitter 前,必须在子进程环境中显式提供 TWITTER_AUTH_TOKENTWITTER_CT0,不得在日志或命令回显中暴露值。

小红书注意:Agent Reach 不替用户登录,也不读取浏览器 Cookie。OpenCLI 只用 用户已有且明确控制的 Chrome 会话;没有现成会话时不要自动登录,改用 Cookie-Editor 手工导出后配置 xiaohongshu-mcp / 存量工具。

Boss直聘配置触发:当用户说“帮我配 Boss直聘”时,先读取 references/career.md 的 Boss 章节,然后在获得安装授权后运行 agent-reach install --env=local --system --channels=boss。Agent 负责按系统启动 只绑定 127.0.0.1:9222 的专用 Chrome;拉起后第一步是暂停并让用户肉眼确认 窗口内是已登录状态(右上角有头像),未登录则让用户登录/扫码,用户确认后再运行 boss --cdp-url http://localhost:9222 login --cdpagent-reach doctor 验收。 不要让用户自己研究端口参数。 专用 Chrome profile 必须长期复用,不要每次创建,也不要默认改用日常主 Chrome。

判断 CDP 浏览器登录态不要信 boss status(它只校验本地 session.enc,与 浏览器登录态互不代表),以 agent-reach doctor 的浏览器 cookie 探测(wt2) 为准,并配合用户肉眼确认。绝不用当前页 URL 判断登录态: security-check / zhipin-security / _security_check 安全校验页是 Boss 反爬挑战, 与登录无关——已登录也会出现(带 CDP 调试端口的 Chrome 几乎必现)。看到它不要 当成“未登录”,先跑 agent-reach doctor 看浏览器 cookie,再决定是否需要用户登录。 搜索报 AUTH_EXPIRED 即浏览器未登录的 ground truth:直接走登录流程 + login --cdp, 不要往安全校验方向解释。

执行搜索时必须使用 boss --browser-source existing-browser --cdp-url http://localhost:9222 search ...; 遇到 ENVIRONMENT_RISK 立即停止,不刷新、不重新登录、不自动重试。

bash
# Twitter 搜索(twitter-cli 首选;失败重试链见 social.md)
twitter search "query" -n 10

# Reddit(无零配置路径:OpenCLI 或 rdt-cli,必须登录态)
opencli reddit search "query" -f yaml   # 桌面
rdt search "query" --limit 10            # 存量/服务器

# 小红书(桌面首选 OpenCLI)
opencli xiaohongshu search "query" -f yaml

# Facebook / Instagram(桌面 OpenCLI,复用浏览器登录态)
opencli facebook search "query" -f yaml
opencli facebook groups -f yaml
opencli instagram search "query" -f yaml       # 搜用户
opencli instagram user USERNAME -f yaml        # 读指定用户最近帖子

环境检查

本机 Python 环境默认是 conda dl;若 agent-reach 不在 PATH,用 conda run -n dl agent-reach ... 前缀。

bash
# 检查可用 channel 与每个平台当前激活的后端
conda run -n dl agent-reach doctor --json

OpenCLI 适配器发现

路由表没有覆盖用户需要的平台或命令时,先用 opencli list 查已有适配器,再用 opencli <平台> --help 查看公开命令。发现适配器只证明命令存在,不证明登录态或 目标内容可用;仅在用户任务明确需要该平台时执行只读命令,并以实际非空内容验收。

工作区规则

不要在 agent workspace 创建文件。 使用 /tmp/ 存放临时输出,~/.agent-reach/ 存放持久数据。

详细文档

根据用户需求,阅读对应的详细文档:

配置渠道

如果某个 channel 需要配置,获取安装指南: https://raw.githubusercontent.com/Panniantong/agent-reach/main/docs/install.md

用户只需提供 cookies,其他配置由 agent 完成。

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 Agent Reach AI skill do?

MUST USE when user wants to 调研/research/搜索/search/查/找/look up anything on the internet — e.g. 全网调研 X / 帮我调研一下 X / 查一下 X / 搜搜 X / 看看大家怎么评价 X / X 上有什么讨论 / research this topic。 Also MUST USE when user mentions any platform or shares any URL/链接: 小红书/xiaohongshu/xhs, Twitter/推特/X, B站/bilibili, Reddit, Facebook, Instagram, V2EX, LinkedIn/领英/Boss直聘/招聘/求职/jobs, YouTube, GitHub code search, 小宇宙播客, 雪球/股票行情, RSS feeds, or any web URL. 16 platforms, multi-backend routing (OpenCLI / per-platform CLIs / APIs). Zero config for 6 channels. Run `agent-reach doctor --json` to see which backend serves each pl...

Why use Agent Reach on TypingMind?

Because you install it once and use it with any model. Agent Reach 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 Agent Reach in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Panniantong/Agent-Reach/tree/main/agent_reach/skill. 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 Agent Reach?

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 Agent Reach?

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

Is the Agent Reach AI skill free?

Yes. It is published on GitHub by Panniantong 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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