Agent Reach

What it does

When your agent uses it

• User asks to search
• Read any of these platforms
• User shares a URL from any supported platform
• User asks to search the web

Example prompts

• “search twitter”
• “read tweet”
• “youtube transcript”
• “/agent-reach”

Requirements

• Python 3
• Node.js
• Docker

What it can do on your machine

Read from SKILL.md and the folder at commit fc4a1c7. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • curl
  • yt-dlp
  • gh
  • python3
  • npm

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Hosts in commands or code, which the agent is likely to contact:

  • r.jina.ai
  • reddit.com
  • v.douyin.com
  • bilibili.com
  • mp.weixin.qq.com
  • linkedin.com

  Also links to:

  • raw.githubusercontent.com

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Agent Reach loads about 1.3k tokens when it runs. Until then it costs about 230 tokens; SKILL.md has 188 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~230

When it runs · the whole SKILL.md, loaded when a task matches

~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from EdisonChenAI/agent-reach at commit fc4a1c7, republished under its MIT licence (© EdisonChenAI). 188 words, ~1,335 tokens.

name

agent-reach

description

Use the internet: search, read, and interact with 13+ platforms including Twitter/X, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu (小红书), Douyin (抖音), WeChat Articles (微信公众号), LinkedIn, Boss直聘, RSS, Exa web search, and any web page. Use when: (1) user asks to search or read any of these platforms, (2) user shares a URL from any supported platform, (3) user asks to search the web, find information online, or research a topic, (4) user asks to post, comment, or interact on supported platforms, (5) user asks to configure or set up a platform channel. Triggers: "搜推特", "搜小红书", "看视频", "搜一下", "上网搜", "帮我查", "全网搜索", "search twitter", "read tweet", "youtube transcript", "search reddit", "read this link", "看这个链接", "B站", "bilibili", "抖音视频", "微信文章", "公众号", "LinkedIn", "GitHub issue", "RSS", "search online", "web search", "find information", "research", "帮我配", "configure twitter", "configure proxy", "帮我安装".

curl -s "https://r.jina.ai/URL"

mcporter call 'exa.web_search_exa(query: "query", numResults: 5)'
mcporter call 'exa.get_code_context_exa(query: "code question", tokensNum: 3000)'

xreach search "query" -n 10 --json          # search
xreach tweet URL_OR_ID --json                # read tweet (supports /status/ and /article/ URLs)
xreach tweets @username -n 20 --json         # user timeline
xreach thread URL_OR_ID --json               # full thread

yt-dlp --dump-json "URL"                     # video metadata
yt-dlp --write-sub --write-auto-sub --sub-lang "zh-Hans,zh,en" --skip-download -o "/tmp/%(id)s" "URL"
                                             # download subtitles, then read the .vtt file
yt-dlp --dump-json "ytsearch5:query"         # search

yt-dlp --dump-json "https://www.bilibili.com/video/BVxxx"
yt-dlp --write-sub --write-auto-sub --sub-lang "zh-Hans,zh,en" --convert-subs vtt --skip-download -o "/tmp/%(id)s" "URL"

curl -s "https://www.reddit.com/r/SUBREDDIT/hot.json?limit=10" -H "User-Agent: agent-reach/1.0"
curl -s "https://www.reddit.com/search.json?q=QUERY&limit=10" -H "User-Agent: agent-reach/1.0"

gh search repos "query" --sort stars --limit 10
gh repo view owner/repo
gh search code "query" --language python
gh issue list -R owner/repo --state open
gh issue view 123 -R owner/repo

mcporter call 'xiaohongshu.search_feeds(keyword: "query")'
mcporter call 'xiaohongshu.get_feed_detail(feed_id: "xxx", xsec_token: "yyy")'
mcporter call 'xiaohongshu.get_feed_detail(feed_id: "xxx", xsec_token: "yyy", load_all_comments: true)'
mcporter call 'xiaohongshu.publish_content(title: "标题", content: "正文", images: ["/path/img.jpg"], tags: ["tag"])'

mcporter call 'douyin.parse_douyin_video_info(share_link: "https://v.douyin.com/xxx/")'
mcporter call 'douyin.get_douyin_download_link(share_link: "https://v.douyin.com/xxx/")'

python3 -c "
import asyncio
from miku_ai import get_wexin_article
async def s():
    for a in await get_wexin_article('query', 5):
        print(f'{a[\"title\"]} | {a[\"url\"]}')
asyncio.run(s())
"

cd ~/.agent-reach/tools/wechat-article-for-ai && python3 main.py "https://mp.weixin.qq.com/s/ARTICLE_ID"

mcporter call 'linkedin.get_person_profile(linkedin_url: "https://linkedin.com/in/username")'
mcporter call 'linkedin.search_people(keyword: "AI engineer", limit: 10)'

mcporter call 'bosszhipin.get_recommend_jobs_tool(page: 1)'
mcporter call 'bosszhipin.search_jobs_tool(keyword: "Python", city: "北京")'

python3 -c "
import feedparser
for e in feedparser.parse('FEED_URL').entries[:5]:
    print(f'{e.title} — {e.link}')
"

© EdisonChenAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in the repository root of EdisonChenAI/agent-reach.

• SKILL.md
• LICENSE
• README.md

Open the folder on GitHubat commit fc4a1c7

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in EdisonChenAI/agent-reach, which our catalogue first saw on October 7, 2026.

• LeoYeAI/openclaw-master-skillsskills/agent-reach