agentsclimarketplace

Agent reach

Skill Ootto-AI/claude-content-skills/skills/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, V2EX, LinkedIn/领英/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. 13 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) / career(LinkedIn) / dev(github) / web(网页/文章/RSS) / video(YouTube/B站/播客)。From its SKILL.md

Install
npx -y skills add Ootto-AI/claude-content-skills --skill agent-reach

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

3 things to look at

  • 19 stars19 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
  • runs commandsInstructs the agent to run 8 commands, including `agent-reach doctor --json` and 7 more.
  • fetches URLsInstructs the agent to fetch 3 URLs, including https://r.jina.ai/URL and 2 more.

What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

6.8 KB, ~1.6k tokens by cl100k_base, as published. Nobody here has run it

Agent Reach — 互联网能力路由器

13 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。

Bundled with the Ootto content skills as the factory's research · scrape · download engine — the FIND step that feeds reel-analyzer. Vendored from Panniantong/Agent-Reach (MIT — full credit to the author). It's a router: don't load everything, read only the reference (the "checkpoint") for the capability you need. For the content factory you mainly use three:

The other platforms (小红书 / B站 / V2EX / 雪球) are optional extras. First-time channel setup: follow https://raw.githubusercontent.com/Panniantong/agent-reach/main/docs/install.md — Reddit, web, Exa search and YouTube subtitles work zero-config; only logged-in platforms (Twitter, 小红书) need cookies.

常驻规则(全程适用)

  1. 动手前先体检:多后端平台(小红书/Reddit/B站/Twitter)先跑 agent-reach doctor --json,按各平台 active_backend 字段选命令组。
  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/Redditsocialreferences/social.md
招聘/职位/LinkedIncareerreferences/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

零配置快速命令

# 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,见 video.md)
yt-dlp --write-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 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

环境检查

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

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。

What ships with it: 6 files

15.4 KB alongside SKILL.md

references/

Gives 0 of the 12 instructions most context ai engineering skills give in ~1.6k tokens

Counted across 1,328 of the 2,349 authors here whose files we hold, read 2026-09-06

  • Dispatch a fresh subagent for each taskin 76 of 1328, across 59 files
  • Perform spec compliance review before code quality reviewin 44 of 1328, across 34 files
  • Dispatch a final code reviewer after all tasksin 38 of 1328, across 26 files
  • Answer subagent questions before allowing implementationin 36 of 1328, across 26 files
  • Use the least powerful model capable of the taskin 33 of 1328, across 26 files
  • Create a TodoWrite list for all tasksin 32 of 1328, across 22 files
  • Perform a task review after each implementationin 31 of 1328, across 24 files
  • Extract all tasks and context from the planin 29 of 1328, across 20 files
  • Provide full task text to subagentsin 28 of 1328, across 20 files
  • Use git worktrees for isolated workspacesin 25 of 1328, across 20 files
  • Specify the model explicitly when dispatching a subagentin 23 of 1328, across 18 files
  • Execute all tasks from the plan without stoppingin 21 of 1328, across 16 files

Said here and by no other author read

  • run agent-reach doctor before using platforms
  • declare the platform and backend before starting
  • use agent-reach for all supported platform access
  • follow retry chains in references for failures
  • combine multiple platforms for comprehensive research
  • run agent-reach check-update after large tasks

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.