SkillFoxx

WeChat Favorites Report skill

A skill processes your WeChat favorites on a Mac and builds an HTML report with search, filters and activity charts.

  • 645 ★ on the repository
  • Last commit
  • MIT
Skill

Broad access

Why this level

  • Keys and decrypted databases expose personal saved items and account contents.
  • Frida and application-copy preparation affect a sensitive environment; thumbnails and libraries can load over the network.
All reasons and checks

zhuyansen/wx-favorites-reportAuthor:Jason Zhu

Install

In your terminal, with SkillFoxx CLI

npx skillfoxx add skills/wechat-favorites-report

Detects the agents on your machine, shows the access level and pins the version.

Other ways to install

Access and checks

How we review

Broad accessThe tool can change data, run commands or handle secrets.

  • Keys and decrypted databases expose personal saved items and account contents.
  • Frida and application-copy preparation affect a sensitive environment; thumbnails and libraries can load over the network.

This is third-party code. Review the repository files before installing.

What it does

WeChat Favorites Report builds an interactive HTML report from WeChat saved items. One script parses records into a common JSON format. Another creates charts and a list you can search and filter by content type or tag. For an owned collection, the workflow extracts a key from WeChat and decrypts its local database. This requires account access and creates copies of personal data. Start with a demo report to inspect the result without accessing your own database.

Who it is for. For owners of a WeChat collection who want to find and inspect saved items locally.

Good fit when

  • Find items of a particular type in a large collection.
  • Inspect when items were saved.
  • Compare frequent sources and tags.
  • Test the report with demo data before processing personal material.

Not a fit when

  • You need unauthorized access to another account or device.
  • Decrypted personal-database copies cannot be created.
  • You need embedded playback of original videos and encrypted attachments.

Example request

Build the demo WeChat favorites report first and show its filters; do not access my database without separate approval.

Limitations

Extraction targets macOS with signed-in WeChat Mac 4.x and Python 3.9 or later; this method is not established for other systems. Frida works with a prepared application copy, so a WeChat update can break key extraction. Keys, decrypted databases and HTML contain personal information; keep them out of public repositories. Original images, videos and files from the encrypted CDN do not appear in the report, so the HTML does not replace a complete copy of the collection.

How to disable. Stop local report viewing and disable the skill. Inspect temporary keys, decrypted copies and HTML reports separately, retaining only needed data.

FAQ

Which charts are included?

Monthly trends, content types, sources, time-based activity and word or tag clouds.

Can I search saved items?

Yes. The collection view supports text search, sorting and pagination.

What does the parser accept?

SQLite, CSV or JSON can be normalized; prepare the source separately.

How is HTML generated from prepared JSON?

Use `python3 generate_report.py --input data.json --output report.html` in the corresponding script directory.

Can report screenshots be published safely?

Only after separate review and removal of personal information. The report exposes saved items and their contents.

Does the report work entirely offline?

Not always. Thumbnails and chart libraries can load from the network even when the database and HTML are stored locally.

Discussion

No questions or reviews yet.

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README in short

Separate scripts parse data and generate HTML. The details view shows the selected item’s title, description, original link and tags.

README badge

Original SKILL.md

---
name: wx-favorites-report
description: |
  微信收藏可视化：从加密的微信本地数据库端到端解密、解析，生成交互式 HTML 可视化报告。
  触发词：/wx-favorites-report、微信收藏可视化、收藏报告、收藏分析
  支持输入：加密/解密后的 Favorite.db（SQLite）或 CSV/JSON 导出文件
---

# 微信收藏可视化 Skill

将微信收藏数据（加密 Favorite.db）端到端解密、解析、生成交互式 HTML 可视化报告。

## 执行流程

### Step 1: 确认数据源

询问用户是否已有解密后的 Favorite.db。

- **已有解密 DB** → 跳到 Step 3
- **未解密** → 进入 Step 2 密钥提取 + 解密

### Step 2: 密钥提取与数据库解密（macOS）

#### 2a. 准备签名副本
```bash
# 复制微信到桌面并去掉 Hardened Runtime
cp -R /Applications/WeChat.app ~/Desktop/WeChat.app
codesign --force --deep --sign - ~/Desktop/WeChat.app
```

#### 2b. 安装 frida
```bash
pip3 install frida frida-tools
```

#### 2c. 提取密钥
```bash
# 关闭原版微信，从桌面副本启动
killall WeChat 2>/dev/null; sleep 2

# 用 frida spawn 模式启动微信并 hook PBKDF2
PYTHONPATH=$(python3 -c "import site; print(site.getusersitepackages())") python3 << 'PYEOF'
import frida, time

JS_CODE = """

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