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Knowledge Base Collector

ASecurity

Collect and organize a personal knowledge base from URLs (web/X/WeChat) and screenshots. Use when the user says they want to save an URL, ingest a link, archive content to KB, tag/classify notes, store screenshots, or search their saved knowledge in Telegram. Supports WeChat via a connected macOS node when cloud fetch is blocked.

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  • Added September 7, 2026
ai-agentspythonbashnodedatabasesecurity

Works with

  • claude code
  • mcp

Security analysis

A100/100

Pro scans all 7 files and shows the line behind each finding

Scanned September 7, 2026

npx -y skills add modbender/skill-library-mcp --skill knowledge-base-collector --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: knowledge-base-collector
description: Collect and organize a personal knowledge base from URLs (web/X/WeChat) and screenshots. Use when the user says they want to save an URL, ingest a link, archive content to KB, tag/classify notes, store screenshots, or search their saved knowledge in Telegram. Supports WeChat via a connected macOS node when cloud fetch is blocked.
---

## Summary

- Ingest: web URLs, X/Twitter links, WeChat Official Account links (mp.weixin.qq.com), and screenshots
- Store: writes to a shared KB folder with per-item `content.md` + `meta.json` and a global `index.jsonl`
- Organize: tag-first classification with richer tags (e.g. `#agent`, `#coding-agent`, `#claude-code`, `#mcp`, `#rag`, `#prompt-injection`, `#security`, `#pricing`, `#database`)
- WeChat: cloud fetch may be blocked; when a macOS node (e.g. Reed-Mac) is online, prefer node-side fetch to improve success rate; otherwise create a placeholder entry
- Search: designed to support Telegram Q&A / search flows on top of the index and content

把用户发来的链接/截图沉淀到共享知识库(KB),并做标签化整理。

## 默认 KB 位置
- KB Root(可改):`/home/ubuntu/.openclaw/kb`
- 索引:`kb/20_Inbox/urls/index.jsonl`
- 每条内容目录:`kb/20_Inbox/urls/<YYYY-MM>/<item>/content.md + meta.json`

> 目标:**先入库不丢**,再迭代“摘要/标签/检索”。

## 你要做的事(按输入类型)

### 1) 普通网页 / X(Twitter) / 公众号 URL 入库
运行脚本:

```bash
python3 /home/ubuntu/.openclaw/skills/knowledge-base-collector/scripts/ingest_url.py "<URL>" --tags "#optional" --note "context"
```

行为:
- 自动识别来源(web/x/wechat)
- 优先用 `r.jina.ai` 抽取正文(无需登录)
- 公众号遇到风控会写占位条目:`status=blocked_verification` + tag `#needs-manual`
- 对同一 URL 做 key 去重(已存在则跳过)

#### WeChat 更高成功率(推荐路径)
当云端抓取命中“环境异常/验证”时:
- 如果有已连接的 macOS 节点(例如 `Reed-Mac`)且该节点能访问该文章,可用 `nodes.run` 在节点上执行抓取(requests+bs4),然后写入 KB。
- 注意:这条路径依赖节点在线与网络环境;无法承诺 100%。

### 2) 截图/图片入库(含 OCR 文本)
脚本:

```bash
python3 /home/ubuntu/.openclaw/skills/knowledge-base-collector/scripts/ingest_image.py /path/to/image.jpg \
  --text-file /path/to/ocr.txt \
  --title "..." --tags "#ai #product" --note "..."
```

说明:
- `ingest_image.py` 负责“落盘+索引”。OCR 可用:
  - 本机 tesseract(若安装了 `tesseract-ocr` + `chi_sim`)
  - 或用多模态 LLM 抽取文字后写入 `--text-file`

## Telegram 里直接问(检索)
推荐先用脚本(本机/服务器):

```bash
python3 /home/ubuntu/.openclaw/skills/knowledge-base-collector/scripts/search_kb.py --q "claude code" --limit 10
python3 /home/ubuntu/.openclaw/skills/knowledge-base-collector/scripts/search_kb.py --tags "#claude-code #coding-agent" --limit 20
python3 /home/ubuntu/.openclaw/skills/knowledge-base-collector/scripts/search_kb.py --source wechat --since 7d --q "Elys"
```

## 公众号待补抓队列(占位条目)

```bash
python3 /home/ubuntu/.openclaw/skills/knowledge-base-collector/scripts/wechat_backlog.py --limit 30
```

## 周报/主题报告候选清单(给 LLM 写总结用)

```bash
python3 /home/ubuntu/.openclaw/skills/knowledge-base-collector/scripts/weekly_digest.py --days 7 --limit 30
```

## 重要注意事项(安全/隐私)
- 截图/网页可能包含 token/验证码/密钥:入库前应做脱敏(替换为 `REDACTED`)。
- 公众号抓取受风控影响:建议允许“占位入库”,后续再补全。

Files in this skill

  • SKILL.md3.8 KB
  • scripts/ingest_image.py4.8 KB
  • scripts/ingest_url.py8.3 KB
  • scripts/search_kb.py4.5 KB
  • scripts/tagger.py4 KB
  • scripts/wechat_backlog.py2.2 KB
  • scripts/weekly_digest.py3.2 KB

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