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Simplified marker extraction architecture: - AI normalization (agents.py) handles natural conversation - Simple line-start matching for explicit markers as fallback - Removed complex regex patterns (DECISION_PATTERN, QUESTION_PATTERN, ACTION_PATTERN) - Participants can now write naturally without strict formatting rules This implements the original design intent: fast AI model normalizes conversational text into structured format, then simple parsing logic extracts it. Benefits: - More flexible for participants (no strict formatting required) - Simpler code (startswith() instead of regex) - Clear separation: AI for understanding, code for mechanical parsing - Cost-effective (fast models for simple extraction task) Updated workflow-marker-extraction.puml to show patterns in notes instead of inline text (fixes PlantUML syntax error). 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> |
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| .. | ||
| AUTOMATION.md | ||
| DESIGN.md | ||
| INSTALL.md | ||
| PROGRESS.md | ||
| ai-provider-fallback.puml | ||
| architecture-overview.puml | ||
| cascading-rules.puml | ||
| commit-workflow.puml | ||
| diagrams-README.md | ||
| directory-structure.puml | ||
| discussion-stages.puml | ||
| file-lifecycle.puml | ||
| patcher-pipeline.puml | ||
| voting-system.puml | ||
| workflow-marker-extraction.puml | ||