ginger_wechat_portrait

Name: ginger_wechat_portrait
Rating: 61 (1 reviews)
Author: Jiang59991

Jiang59991/ginger_wechat_portrait

An automated Claude Code skill that decrypts local WeChat databases on macOS, extracts chat histories, and generates comprehensive visual and AI-driven personality analysis reports.

497 102No licenseUpdated 2026-03-28

Good

View on GitHub Open source file

Overview

This skill acts as an intelligent local pipeline for analyzing WeChat chat logs on macOS. It manages Python virtual environments, automatically clones decryption tools, guides users through necessary macOS security permissions (SIP and LLDB key extraction), processes message CSVs via natural language tool execution, and leverages Claude to perform Big Five and MBTI personality profiling. The final output is an interactive HTML report featuring behavioral heatmaps, word clouds, and comparative linguistic analytics.

Capabilities

▸Automated python dependency management in isolated virtual environments
▸WeChat database state checking and decryption pipeline management
▸Guided LLDB memory key extraction for macOS WeChat clients
▸Contact message export, fuzzy search, and avatar extraction
▸Statistical charting of message frequency, hourly distribution, and word counts
▸Claude-driven linguistic personality profiling (Big Five and MBTI)
▸HTML report generation with embedded CSS and visualization charts

Best for

Analyzing chat behaviors and activity trends with specific WeChat contacts, Generating AI-powered Big Five and MBTI personality comparisons between users and contacts, Creating shareable visual HTML reports of messaging habits, peak hours, and linguistic styles

Works with

Claude Code

Evoa Score breakdown= Σ (score × weight)

Task usefulness20%100 → +20.0

実タスクにどれだけ役立つか（機能の豊富さ・用途の明確さ）。 — AIによるcapabilities/use-cases解析

Code quality15%88 → +13.2

実装・指示の品質。 — AIによるSKILL.md/README解析

Maintenance15%70 → +10.5

リポジトリがどれだけ活発に保守されているか。 — GitHub 最終push日時の新しさ

Documentation12%39 → +4.7

ドキュメントの充実度・分かりやすさ。 — README/独自要約の情報量

Security15%50 → +7.5

危険・不審な挙動が無いか。 — AIによるセキュリティレビュー

Originality10%85 → +8.5

ありふれたラッパーではない独自性。 — AIによる独自性判定

Popularity8%71 → +5.7

コミュニティの採用度。 — GitHub Stars/Forks（対数スケール）

Compatibility5%25 → +1.3

対応AIエージェントの広さ。 — AIによる対応エージェント判定

Weighted total71.3 / 100

ライセンス不明/制限あり（Red）のSkillは総合スコアに0.85倍の補正を適用します。ランキングはこのScoreのみで決まり、広告で変わりません。算出方法の詳細 →

Security considerations

The skill interacts directly with the local macOS WeChat process memory using LLDB to extract database encryption keys, requiring temporary disabling of System Integrity Protection (SIP). All data processing and AI analysis occur locally on the user's machine with no telemetry or external transmission.