link-library

# Link Library — Personal Content Knowledge Base Save web content with full original text, generate summaries and tags, retrieve semantically. ## Core Rules 1. **Always save original full text** — summaries are for retrieval, originals are for re-reading 2. **Detect interest, don't demand commands** — if user engages with a link, offer to save 3. **Twitter/X is first-class** — tweets, threads, and articles are fully supported ## Interest Detection When user shares a link, evaluate interest signals: **Auto-save (no confirmation needed):** - User explicitly says save/bookmark/记一下/放进知识库 - User asks "帮我总结一下" (summarize implies save-worthy) **Offer to save (ask once):** - User shares link + positive commentary ("这篇不错", "有意思", "学到了") - User asks follow-up questions about link content - User discusses link content substantively **Don't save:** - User shares link just for quick reference in conversation - User says "不用保存" or similar ## Data Location All entries in `~/.openclaw/workspace-main/library/`: ``` library/ ├── articles/ # Web articles, blog posts, WeChat, Zhihu ├── tweets/ # Twitter/X posts and threads ├── videos/ # YouTube, Bilibili ├── podcasts/ # Podcast episodes ├── papers/ # Academic papers, PDFs ├── images/ # Infographics, visual content └── misc/ # Everything else ``` ## Content Types & Fetch Methods | Type | URL Patterns | Fetch Method | Template | |------|-------------|--------------|----------| | article | Generic web, blog, /post/ | `web_fetch` or `curl -s "https://r.jina.ai/URL"` | `article.md` | | wechat | mp.weixin.qq.com | `cd ~/.agent-reach/tools/wechat-article-for-ai && python3 main.py "URL"` | `article.md` | | tweet | x.com, twitter.com /status/ | `xreach tweet URL --json` | `tweet.md` | | thread | x.com, twitter.com (thread) | `xreach thread URL --json` | `tweet.md` | | video | youtube.com, youtu.be | `yt-dlp --dump-json "URL"` + subtitle extraction | `video.md` | | bilibili | bilibili.com | `yt-dlp --dump-json "URL"` + subtitle extraction | `video.md` | | paper | arxiv.org, .pdf links | `web_fetch` or browser | `paper.md` | | podcast | Podcast platforms | `web_fetch` metadata | `podcast.md` | | image | Image URLs | Download + describe | `image.md` | ### Twitter/X Fetch Details ```bash # Single tweet xreach tweet URL_OR_ID --json # Full thread xreach thread URL_OR_ID --json # User timeline (for context) xreach tweets @username -n 20 --json ``` Extract from JSON: `full_text`, `user.screen_name`, `created_at`, `entities`, media URLs. For threads: concatenate all tweets in order as full content. ### Video Subtitle Extraction ```bash # Download subtitles yt-dlp --write-sub --write-auto-sub --sub-lang "zh-Hans,zh,en" \ --convert-subs vtt --skip-download -o "/tmp/%(id)s" "URL" # Then read the .vtt file as transcript ``` ## Entry Structure Every entry has two parts: ### 1. YAML Frontmatter (structured metadata) ```yaml title: "..." source: "..." # Platform/domain url: "..." # Original URL author: "..." # Author or @handle date_published: "..." # When content was created date_saved: "..." # When we saved it last_updated: "..." # Last modification type: article|tweet|video|podcast|paper|image tags: [tag1, tag2, ...] status: unread|read|reviewed priority: low|normal|high related: [] # Paths to related entries ``` ### 2. Markdown Body (content) ```markdown # {title} ## Summary 2-3 sentence summary. ## Key Points - Point 1 - Point 2 ## Original Content THE FULL ORIGINAL TEXT — not truncated, not summarized. This is the authoritative source for re-reading and quoting. ## Quotes > Notable quotes worth highlighting ## Notes Personal observations, connections, action items. ## Related - [[library/tweets/related-tweet]] - [[library/articles/related-article]] ``` **⚠️ MANDATORY: Always save original full text in "Original Content" section.** Summaries and key points are for quick retrieval. The original text is for accurate re-reading and quoting. Never skip saving the full content. ## Filename Convention `<slugified-title>-<YYYY-MM-DD>.md` Examples: - `library/articles/yc-why-not-work-and-startup-2026-03-12.md` - `library/tweets/garry-tan-on-yc-advice-2026-03-13.md` - `library/videos/how-to-build-agents-2026-03-13.md` ## Save Workflow 1. **Detect URL** — Parse link from user message 2. **Identify type** — Match URL pattern to content type 3. **Check dedup** — `memory_search("URL or title")` to avoid duplicates 4. **Fetch content** — Use appropriate method from table above 5. **Generate metadata** — Title, summary, key points, tags (3-7) 6. **Write entry** — Use template, fill frontmatter + full original text 7. **Confirm** — Tell user: title, tags, and where it's saved ## Search & Retrieval ```python # Semantic search memory_search("创业方法论") memory_search("Garry Tan 的推文") memory_search("AI agent 视频教程") # Read specific entry memory_get("library/tweets/garry-tan-on-yc-2026-03-13.md") ``` When returning search results, show: - Title + source + date - Summary (2 lines max) - Tags - Offer to show full original text ## Writing Reference Mode When user asks to write something using saved content: 1. Search library for relevant entries 2. Read full original text of top matches 3. Synthesize insights, cite sources inline 4. Format citations as `[[library/type/entry-name]]` ## Templates Located in `templates/`: - `article.md` — Web articles, blog posts, newsletters - `tweet.md` — Twitter/X posts and threads - `video.md` — Videos with transcript - `podcast.md` — Podcast episodes - `paper.md` — Academic papers - `image.md` — Visual content ## Best Practices - **Save originals religiously** — summaries lose nuance - **Tag consistently** — reuse existing tags, keep vocabulary tight - **Link related entries** — build a knowledge graph over time - **Don't over-ask** — if interest is clear, just save and confirm