docs: update all remaining references to use upstream tools directly
- docs/README_en.md: update FAQ, Works Out of the Box, Design Philosophy - docs/troubleshooting.md: Exa fallback uses mcporter directly - agent_reach/guides/setup-exa.md: test with mcporter call - agent_reach/guides/setup-wechat.md: test with Jina Reader
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Panniantong
+21
-17
@@ -108,14 +108,14 @@ After the Skill is installed, the Agent will auto-detect whether `agent-reach` C
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No configuration needed — just tell your Agent:
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- "Read this link" → any web page
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- "What's this GitHub repo about?" → repos, issues, code
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- "What does this video cover?" → YouTube / Bilibili subtitles
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- "Read this tweet" → Twitter posts
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- "Subscribe to this RSS" → RSS / Atom feeds
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- "Search GitHub for LLM frameworks" → GitHub search
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- "Read this link" → `curl https://r.jina.ai/URL` for any web page
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- "What's this GitHub repo about?" → `gh repo view owner/repo`
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- "What does this video cover?" → `yt-dlp --dump-json URL` for subtitles
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- "Read this tweet" → `bird read URL --json`
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- "Subscribe to this RSS" → `feedparser` to parse feeds
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- "Search GitHub for LLM frameworks" → `gh search repos "LLM framework"`
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**No commands to remember.** The Agent knows what to call.
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**No commands to remember.** The Agent reads SKILL.md and knows what to call.
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---
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@@ -171,26 +171,30 @@ Every time you spin up a new Agent, you spend time finding tools, installing dep
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Agent Reach does one simple thing: **it makes those tool selection and configuration decisions for you.**
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After installation, your Agent calls the upstream tools directly (bird CLI, yt-dlp, mcporter, gh CLI, etc.) — no wrapper layer in between.
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### 🔌 Every Channel is Pluggable
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Each platform is a single Python file implementing a unified interface. **Backends can be swapped anytime** — when a better tool comes along, change one file and nothing else breaks.
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Each platform maps to an upstream tool. **Don't like one? Swap it out.**
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```
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channels/
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├── web.py → Jina Reader ← swap to Firecrawl, Crawl4AI…
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├── twitter.py → bird ← swap to Nitter, official API…
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├── youtube.py → yt-dlp ← swap to YouTube API, Whisper…
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├── twitter.py → bird ← swap to Nitter, official API…
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├── youtube.py → yt-dlp ← swap to YouTube API, Whisper…
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├── github.py → gh CLI ← swap to REST API, PyGithub…
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├── bilibili.py → yt-dlp ← swap to bilibili-api…
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├── bilibili.py → yt-dlp ← swap to bilibili-api…
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├── reddit.py → JSON API + Exa ← swap to PRAW, Pushshift…
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├── xiaohongshu.py → mcporter MCP ← swap to other XHS tools…
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├── linkedin.py → linkedin-mcp ← swap to LinkedIn API…
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├── bosszhipin.py → mcp-bosszp ← swap to other job tools…
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├── rss.py → feedparser ← swap to atoma…
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├── rss.py → feedparser ← swap to atoma…
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├── exa_search.py → mcporter MCP ← swap to Tavily, SerpAPI…
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└── __init__.py → Channel registry
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└── __init__.py → Channel registry (for doctor checks)
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```
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Each channel file only checks whether its upstream tool is installed and working (`check()` method for `agent-reach doctor`). The actual reading and searching is done by calling the upstream tools directly.
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### Current Tool Choices
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| Scenario | Tool | Why |
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@@ -226,13 +230,13 @@ This project was entirely vibe-coded 🎸 There might be rough edges here and th
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<details>
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<summary><strong>How to search Twitter/X with AI agent without paying for API?</strong></summary>
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Agent Reach uses the [bird CLI](https://www.npmjs.com/package/@steipete/bird) with cookie-based authentication — completely free, no Twitter API subscription needed. After installing Agent Reach, export your Twitter cookies using the Cookie-Editor Chrome extension, run `agent-reach configure twitter-cookies "your_cookies"`, and your agent can search with `agent-reach search-twitter "query"`.
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Agent Reach uses the [bird CLI](https://www.npmjs.com/package/@steipete/bird) with cookie-based authentication — completely free, no Twitter API subscription needed. After installing Agent Reach, export your Twitter cookies using the Cookie-Editor Chrome extension, run `agent-reach configure twitter-cookies "your_cookies"`, and your agent can search with `bird search "query" --json`.
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</details>
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<details>
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<summary><strong>How to get YouTube video transcripts / subtitles for AI agent?</strong></summary>
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Simply run `agent-reach read https://youtube.com/watch?v=xxx`. It automatically extracts transcripts using yt-dlp. Supports multiple languages, no API key required.
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`yt-dlp --dump-json "https://youtube.com/watch?v=xxx"` extracts video metadata; `yt-dlp --write-sub --skip-download "URL"` extracts subtitles. Supports multiple languages, no API key required.
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</details>
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<details>
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@@ -244,7 +248,7 @@ Reddit blocks datacenter IPs. Configure a residential proxy: `agent-reach config
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<details>
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<summary><strong>Does Agent Reach work with Claude Code / Cursor / Windsurf / OpenClaw?</strong></summary>
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Yes! Agent Reach is a standard CLI tool. Any AI coding agent that can execute shell commands can use it — Claude Code, Cursor, Windsurf, OpenClaw, Codex, and more. Just `pip install agent-reach` and start using it.
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Yes! Agent Reach is an installer + configuration tool. Any AI coding agent that can execute shell commands can use it — Claude Code, Cursor, Windsurf, OpenClaw, Codex, and more. Just `pip install agent-reach`, run `agent-reach install`, and the agent can start using the upstream tools immediately.
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</details>
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<details>
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@@ -262,7 +266,7 @@ Agent Reach uses bird CLI which accesses Twitter via cookie auth — same as you
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<details>
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<summary><strong>How to read XiaoHongShu / 小红书 content programmatically?</strong></summary>
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Agent Reach integrates with xiaohongshu-mcp (runs in Docker). After setup, use `agent-reach read <xiaohongshu_url>` or `agent-reach search-xhs "query"` to search and read XiaoHongShu notes.
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Agent Reach integrates with xiaohongshu-mcp (runs in Docker). After setup, use `mcporter call 'xiaohongshu.get_feed_detail(...)'` to read notes or `mcporter call 'xiaohongshu.search_feeds(keyword: "query")'` to search.
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</details>
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---
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