docs: complete project research (STACK, FEATURES, ARCHITECTURE, PITFALLS, SUMMARY)

Synthesized research findings from 4 parallel researcher agents:

Key Findings:
- Stack: discord.py 2.6.4 + PostgreSQL/SQLite with webhook-driven PluralKit integration
- Architecture: 7-component system with clear separation of concerns, async-native
- Features: Rule-based learning system starting simple, avoiding context inference and ML
- Pitfalls: 8 critical risks identified with phase assignments and prevention strategies

Recommended Approach:
- 5-phase build order (detection → translation → teaching → config → polish)
- Focus on dysgraphia accessibility for teaching interface
- Start with message detection reliability (Phase 1, load-bearing)
- Shared emoji dictionary (Phase 1-3); per-server overrides deferred to Phase 4+

Confidence Levels:
- Tech Stack: VERY HIGH (all production-proven, no experimental choices)
- Architecture: VERY HIGH (mirrors successful production bots)
- Features: HIGH (tight scope, transparent approach)
- Roadmap: HIGH (logical phase progression with value delivery)

Gaps to Address in Requirements:
- Vivi's teaching UX preferences (dysgraphia-specific patterns)
- Exact emoji coverage and naming conventions
- Moderation/teaching permissions model
- Multi-system scope and per-system customization needs

Ready for requirements definition and roadmap creation.

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>

.planning/research/README.md

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+# Research Documents
+
+This directory contains research and analysis for the Vivi Speech Translator project.
+
+## Documents
+
+### PITFALLS.md
+Comprehensive analysis of common mistakes in Discord bot development, with specific focus on:
+- **PluralKit Integration Pitfalls** - Message detection, webhook reliability
+- **Discord API Pitfalls** - Message content intent, rate limiting, permissions
+- **Learning System Pitfalls** - Dictionary quality, teaching interface UX, scope creep
+- **Multi-Server Issues** - Dictionary conflicts across servers
+- **Emoji Handling** - Unicode edge cases, combining characters
+- **Security** - Authorization, privilege escalation, data privacy
+- **Translation Quality** - Making translations feel natural
+- **Accessibility** - Text-heavy interfaces for users with Dysgraphia
+- **Infrastructure** - Hosting and reliability
+
+Each pitfall includes:
+- What goes wrong (the problem)
+- Warning signs (how to detect it)
+- Prevention strategies (how to avoid it)
+- Which phase should address it
+
+**Top 8 Critical Pitfalls to Watch For:**
+1. Message Detection Reliability (Phase 1)
+2. Message Content Intent Architecture (Phase 1)
+3. Dictionary Quality Degradation (Phase 3)
+4. Teaching Interface Complexity (Phase 3)
+5. Rate Limiting and Scaling (Phase 2+)
+6. Emoji Edge Cases (Phase 2)
+7. Authorization and Security (Phase 3)
+8. Webhook Race Conditions (Phase 2+)