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Cascading Development Framework
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rob 33b550ad5b docs: complete update for AI normalization architecture 
Updated all documentation to reflect the new two-tier extraction system:

**workflow-marker-extraction.puml:**
- Completely rewritten to show AI normalization flow
- Documents agents.normalize_discussion() as primary method
- Shows simple line-start fallback for explicit markers
- Includes natural conversation examples vs. explicit markers
- Demonstrates resilience and cost-effectiveness

**AUTOMATION.md:**
- Restructured "Conversation Guidelines" section
- Emphasizes natural conversation as recommended approach
- Clarifies AI normalization extracts from conversational text
- Documents explicit markers as fallback when AI unavailable
- Explains two-tier architecture benefits

**diagrams-README.md:**
- Already updated in previous commit

All documentation now accurately reflects:
✅ AI-powered extraction (agents.py) for natural conversation
✅ Simple fallback parsing (workflow.py) for explicit markers
✅ Multi-provider resilience (claude → codex → gemini)
✅ No strict formatting requirements for participants

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

Co-Authored-By: Claude <noreply@anthropic.com>
 		2025-11-02 20:04:09 -04:00
assets feat: allow ramble codex and gemini providers 2025-11-02 00:46:36 -03:00
automation refactor: simplify workflow.py to use AI normalization with minimal fallback 2025-11-02 18:48:12 -04:00
config feat: add multi-provider AI system with model hint optimization 2025-11-01 21:43:13 -03:00
docs docs: complete update for AI normalization architecture 2025-11-02 20:04:09 -04:00
src fix: sync installer ramble provider options 2025-11-02 01:13:27 -03:00
tests feat: share ai fallback with agents and add provider status 2025-11-02 00:21:10 -03:00
tools feat: add multi-provider AI system with model hint optimization 2025-11-01 21:43:13 -03:00
.gitignore 1st commit 2025-10-27 20:17:35 -03:00
AGENTS.md fix: Add YAML syntax fix and mock AI script for testing 2025-10-31 09:18:59 -03:00
CLAUDE.md docs: comprehensive AI configuration documentation update 2025-11-01 21:48:25 -03:00
GEMINI.md uptodate agents 2025-10-30 13:17:58 -03:00
README.md docs: comprehensive AI configuration documentation update 2025-11-01 21:48:25 -03:00
VERSION 1st commit 2025-10-27 16:24:50 -03:00
pyproject.toml fix: Add YAML syntax fix and mock AI script for testing 2025-10-31 09:18:59 -03:00

README.md

CascadingDev (CDev)

CDev — short for Cascading Development — is a Git-native AI–human collaboration framework that automates documentation, discussion summaries, and code review directly within your repository.
It lets you build self-documenting projects where AI assists in generating and maintaining feature discussions, design docs, and implementation plans — all version-controlled alongside your code.

✨ Key Features

  • Git-Integrated Workflow — every discussion, decision, and artifact lives in Git.
  • Multi-Provider AI System — automatic fallback chains (Claude → Codex → Gemini) with intelligent model selection (fast/quality).
  • Cascading Rules System — nearest .ai-rules.yml defines how automation behaves.
  • Stage-Per-Discussion Model — separate files for feature, design, implementation, testing, and review.
  • Pre-commit Hook — automatically maintains summaries, diagrams, and vote tallies.
  • Ramble GUI — friendly PySide6/PyQt5 dialog for capturing structured feature requests.
  • Deterministic Builds — a reproducible installer bundle you can unzip and run anywhere.

🚀 Quick Start (Developers)

# 1. Create and activate a virtual environment
python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip wheel PySide6

# 2. Build the installer bundle
python tools/build_installer.py

# 3. Test-install into a temporary folder
python install/cascadingdev-*/setup_cascadingdev.py --target /tmp/myproject --no-ramble