Doppel Feature Implementation Guide
CommunityEnd-to-end Doppel feature blueprint
AuthorZeddy-88
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Doppel teams face the challenge of coordinating complex AI-powered features across frontend, backend, and data layers. This guide provides a unified blueprint for implementing Doppel's face-matching, liveness, translation, chat, and notification capabilities end-to-end.
Core Features & Use Cases
- Face matching using 128-dim embeddings and pgvector index (IVFFlat)
- Liveness verification with AWS Rekognition and random missions
- Real-time chat with translation and emotion-preserving translation
- End-to-end user lifecycle: signup, liveness, profile, matching, chat, and notifications
- Data privacy and security baked-in (encryption, rate limits, audits)
Quick Start
Implement the end-to-end Doppel feature stack by following the SKILL.md and architecture.md guidelines.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: Doppel Feature Implementation Guide Download link: https://github.com/Zeddy-88/Dople/archive/main.zip#doppel-feature-implementation-guide Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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