Claude MarketplacesSubmit

Wx Favorites Report

aradotso/trending-skills

If you've ever wanted to browse your WeChat favorites outside the Mac client, this skill walks you through the entire reverse-engineering stack. It uses Frida to hook the PBKDF2 key derivation while WeChat is running, matches the salt to the encrypted SQLCipher database, decrypts it page by page with AES-256-CBC, then parses the XML-encoded favorites into a single-file HTML report with charts and a word cloud. The setup is surprisingly involved: you have to strip the hardened runtime, run the Frida hook while opening the favorites tab, and manually script the decryption. It's a great reference if you're dealing with SQLCipher or need to extract data from a stubborn native app, but expect to spend an hour getting it working the first time.

skills.sh installs: 299
GitHub stars: 26
last updated: Jun 3, 2026

Install

$ npx -y skills add aradotso/trending-skills --skill wx-favorites-report --agent claude-code

Installs into .claude/skills of the current project.

Files

wx-favorites-report

Skill by ara.so — Daily 2026 Skills collection.

End-to-end pipeline that hooks into the WeChat Mac client via Frida, extracts PBKDF2-derived encryption keys, decrypts the favorite.db SQLCipher database, parses XML-encoded favorites, and renders a single-file interactive HTML report with charts, word cloud, and filterable card browser.

Prerequisites

macOS (Apple Silicon or Intel)
WeChat Mac 4.x installed and logged in
Python 3.9+
Frida 17.x

pip3 install frida frida-tools pycryptodome

Project Layout

~/.claude/skills/wechat-favorites-viz/
├── SKILL.md
└── scripts/
    ├── parse_favorites.py      # SQLite/CSV/JSON → unified JSON
    ├── generate_report.py      # JSON → single-file HTML
    └── demo_data.py            # synthetic data for testing

Full Pipeline (Step-by-Step)

Step 1 — Strip Hardened Runtime from WeChat

The App Store build blocks Frida injection. Copy and re-sign without entitlements:

killall WeChat 2>/dev/null; sleep 2
cp -R /Applications/WeChat.app ~/Desktop/WeChat.app
codesign --force --deep --sign - ~/Desktop/WeChat.app

SKILL.md on GitHub

Sponsors

Promote your product hereReach 125k+ visitors monthly Promote your product hereReach 125k+ visitors monthly

Agent CaffeineSponsoredClose your lid, come back to finished work

SnugSponsoredThe clipboard manager for the AI era Promote your product hereReach 125k+ visitors monthly

WaxSponsoredBlock anything with supervision, without erasing your iPhone Promote your product hereReach 125k+ visitors monthly

knobsSponsoredSee your site on any phone, any day, in any language

Details

Repository: github.com/aradotso/trending-skills
First seen: Jun 3, 2026

Recommended

1

cavemanjuliusbrussee/cavemanUltra-compressed communication mode. Cuts output tokens 65% (measured) by speaking like caveman while keeping full technical accuracy. Supports intensity levels618.3Kskills.sh installs

2

grill-memattpocock/skillsA relentless interview to sharpen a plan or design.1.5Mskills.sh installs

3

improveshadcn/improveSurvey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute. Strictly read-only on s40Kskills.sh installs

4

systematic-debuggingobra/superpowersUse when encountering any bug, test failure, or unexpected behavior, before proposing fixes326.7Kskills.sh installs

5

karpathy-guidelinesforrestchang/andrej-karpathy-skillsBehavioral guidelines to reduce common LLM coding mistakes through explicit assumptions, simplicity, and verifiable success criteria.17.9Kskills.sh installs

6

find-skillsvercel-labs/skillsHelps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express int4.3Mskills.sh installs