rob
/
CascadingDev
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

docs: update diagrams-README to reflect AI normalization architecture 

Updated workflow-marker-extraction diagram description to emphasize:
- AI-powered normalization for natural conversation (agents.py)
- Simple line-start fallback for explicit markers (workflow.py)
- Two-tier extraction system design

Benefits of this approach:
- Participants write naturally without strict formatting rules
- Fast AI model handles conversation → structured data conversion
- Simple fallback code when AI unavailable
- Clear separation of concerns

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
rob 2025-11-02 18:52:00 -04:00
parent da726cb5bf
commit 380c7b5d12
1 changed files with 11 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

20
docs/diagrams-README.md
View File

@ -157,17 +157,17 @@ plantuml -tsvg docs/*.puml
--- ---
### 10. **workflow-marker-extraction.puml** 🆕 ### 10. **workflow-marker-extraction.puml** 🆕
**Detailed flowchart** of regex-based marker extraction from discussion files. **Detailed flowchart** of AI-powered marker extraction with simple fallback parsing.
**Shows:** **Shows:**
- Comment parsing from discussion files - Comment parsing from discussion files
- Regex pattern matching for **DECISION**, **QUESTION**, **ACTION** - AI normalization (agents.py) for natural conversation
- Support for both plain (DECISION:) and markdown bold (**DECISION**:) formats - Simple line-start fallback for explicit markers (DECISION:, QUESTION:, ACTION:)
- Structured data extraction - Structured data extraction from AI-generated JSON
- Summary section generation - Summary section generation
- Marker block updates in .sum.md files - Marker block updates in .sum.md files
**Best for:** Understanding how structured markers are extracted and why regex was chosen over line-start matching. **Best for:** Understanding the two-tier extraction system - AI for natural conversation, simple parsing for strict format fallback.
--- ---
@ -236,9 +236,11 @@ Patch fails → Save debug artifacts → Log error → Continue
4. Check .git/ai-rules-debug/ for provider outputs 4. Check .git/ai-rules-debug/ for provider outputs
### Understanding Marker Extraction ### Understanding Marker Extraction
1. See **workflow-marker-extraction.puml** for regex patterns 1. See **workflow-marker-extraction.puml** for AI normalization flow
2. Review automation/workflow.py for implementation 2. Review automation/agents.py for AI-powered extraction
3. Test with **DECISION**, **QUESTION**, **ACTION** markers in discussions 3. Review automation/workflow.py for simple fallback implementation
4. Test with natural conversation - AI extracts markers automatically
5. Fallback: Use explicit line-start markers (DECISION:, QUESTION:, ACTION:)
--- ---
@ -252,7 +254,7 @@ Patch fails → Save debug artifacts → Log error → Continue
| Model Hints (fast/quality) | ✅ Complete | ai-provider-fallback.puml | | Model Hints (fast/quality) | ✅ Complete | ai-provider-fallback.puml |
| Vote Tracking | ✅ Complete | voting-system.puml | | Vote Tracking | ✅ Complete | voting-system.puml |
| Multi-Stage Promotion | ✅ Complete | discussion-stages.puml | | Multi-Stage Promotion | ✅ Complete | discussion-stages.puml |
| Regex Marker Extraction | ✅ Complete | workflow-marker-extraction.puml | | AI Marker Normalization | ✅ Complete | workflow-marker-extraction.puml |
| Structured Summaries | ✅ Complete | workflow-marker-extraction.puml | | Structured Summaries | ✅ Complete | workflow-marker-extraction.puml |
| Implementation Gate | ✅ Complete | file-lifecycle.puml | | Implementation Gate | ✅ Complete | file-lifecycle.puml |
| Error Handling | ✅ Complete | commit-workflow.puml | | Error Handling | ✅ Complete | commit-workflow.puml |