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qqlcx5
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digital-life

Analyze digital footprints to generate structured self-reflection profiles and reports.

Updated Aug 15, 2026
Search Tags:#journaling#self-reflection#privacy#digital footprint#behavior patterns#profile generation#social media analysis
One-click install
npx skills add https://github.com/qqlcx5/skills-hub --skill digital-life-qqlcx5
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: digital-life
Source: https://github.com/qqlcx5/skills-hub/tree/main/skills/digital-life
Command: npx skills add https://github.com/qqlcx5/skills-hub --skill digital-life-qqlcx5

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve? It turns scattered social media traces, chat logs, and posting history into evidence-based self-knowledge, producing structured JSON profiles and readable Markdown reports instead of vague personality guesses. ## Core Features & Use Cases - Five archaeology modes: past-life habit tracing, cringe archaeology of old posts, public-vs-private persona comparison, digital legacy audit with time-cost conversion, and five-style epitaph generation. - Versioned profiles: every analysis writes a JSON profile plus Markdown report, with snapshot, rollback, correction, and append workflows managed by profile-manager.py. - Privacy-first data intake: supports user narration, exported chat files, screenshots, and browser-assisted capture of the user's own logged-in pages, with all analysis kept local. - Use Case: A user exports years of WeChat and Weibo history, runs the legacy audit mode, and receives a report converting 2847 hours of screen time into books, trips, and a concrete existential follow-up question. ## Quick Start Say "我想做遗产清算" or "analyze my digital life" and answer the agent's two or three intake questions to generate your first profile.

Frequently Asked Questions about digital-life

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze my social media history for behavior patterns?▼

Provide chat exports, platform annual reports, or let the agent capture your logged-in pages via browser automation. The skill extracts behavior patterns into a JSON profile and a Markdown report, keeping all analysis local without uploading data.

What data sources can I use for digital footprint analysis?▼

Supported inputs include WeChat and QQ chat exports, Weibo, Zhihu, Douban, and Xiaohongshu pages captured through browser automation, screenshots of annual reports, plain narration, and public URLs after identity confirmation.

Can the agent post or modify content on my social accounts?▼

No. The browser-assisted workflow is strictly read-only: the agent may browse and screenshot your pages but is forbidden from publishing, editing, or deleting anything on your behalf.

How do I correct or roll back a generated profile?▼

Tell the agent what is wrong and it records a correction entry, or run profile-manager.py snapshot before updates and rollback to restore any timestamped version stored in the profiles/history directory.

Is my personal data uploaded when generating these reports?▼

No. All analysis runs locally, profiles store only behavior-pattern summaries rather than raw text, and real user profiles plus history snapshots are excluded from Git via .gitignore rules.

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