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Test User
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# Madomeda - Implementation Summary
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## What Was Created
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A complete Python application for managing markdown frontmatter in git repositories.
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## Files Created
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### Main Application
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- **madomeda.py** - Entry point with command-line argument parsing
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- **requirements.txt** - Python dependencies (PyYAML, python-dotenv, openai)
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- **.env** - LLM configuration template
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### Core Modules (core/)
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1. **database.py** - SQLite database management
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- Tables: files, frontmatter, commits, tags
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- CRUD operations for all entities
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2. **repository.py** - Git integration
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- File discovery via git ls-files
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- Commit history extraction
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- Author/date/hash tracking
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3. **frontmatter.py** - YAML parsing
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- Frontmatter extraction with regex
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- YAML serialization/deserialization
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- Title extraction from markdown
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4. **rules.py** - Rule engine
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- Dynamic rule loading from JSON files
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- Tag normalization (lowercase, underscores)
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- Key normalization (lowercase)
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- Tag/tags field renaming
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5. **template.py** - Template system
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- JSON template loading
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- Field strategy parsing (heur|orig|ai)
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- JSON schema generation for LLM
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6. **llm.py** - LLM integration
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- OpenAI-compatible API client
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- Structured output support
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- Prompt template management
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7. **changelog.py** - Change tracking
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- Session-based logging
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- Timestamp and commit hash headers
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- Per-file change entries
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8. **processor.py** - Main orchestration
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- File processing loop
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- Frontmatter building
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- Conformance checking
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- User interaction (confirmations)
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### Configuration Files
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**templates/default.json**
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```json
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{
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"title": "heur|orig",
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"created": "heur|orig",
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"changed": "heur|orig",
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"authors": "heur|orig",
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"version": "heur|orig",
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"tags": "heur|orig|ai default"
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}
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```
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**rules/** (auto-created)
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- tags_normalization.json
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- tag_to_tags.json
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- lowercase_keys.json
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**prompts/default.txt** - System prompt for LLM
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### Documentation
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- **README.md** - Project overview and quick start
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- **USAGE.md** - Detailed usage examples
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- **STRUCTURE.md** - Complete project structure and architecture
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### Generated Files (gitignored)
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- **madomeda.db** - SQLite database
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- **madomeda_changelog.txt** - Change log
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## Features Implemented
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### ✅ File Discovery
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- Traverses git repository
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- Filters tracked .md files
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- Ignores hidden files (starting with '.')
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- Respects --ignore-paths argument
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### ✅ Database Management
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- SQLite storage for all metadata
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- Frontmatter versioning
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- Git commit tracking
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- Tag repository
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### ✅ Rule Engine
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Three default rules:
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1. Normalize tags (lowercase, underscores, alphanumeric only)
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2. Rename 'tag' to 'tags'
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3. Convert all keys to lowercase
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### ✅ Template System
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Multi-strategy field resolution:
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- **heur**: Git history + document analysis
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- **orig**: Original frontmatter value
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- **ai**: LLM inference with structured output
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### ✅ Git Integration
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Extracts for each file:
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- First commit (creation) date/author/hash
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- Latest commit date/hash
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- All contributors
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- Git tags (if any)
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### ✅ Heuristic Values
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- title: From # heading or filename
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- created/changed: ISO 8601 timestamps from git
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- authors: List of all contributors
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- version: 7-char commit hash
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- tags: Normalized from original
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### ✅ LLM Integration
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- OpenAI-compatible API
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- Configurable via .env
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- Structured output with JSON schema
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- Graceful fallback if unavailable
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### ✅ User Controls
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- **--whatif**: Dry run mode
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- **--no-confirm**: Skip prompts
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- **--force**: Recreate all frontmatter
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- **--template**: Custom templates
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- **--ignore-paths**: Exclude paths
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### ✅ Change Tracking
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- Changelog with timestamps
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- Commit hash recording
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- Per-file change messages
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### ✅ Error Handling
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- Warns on metadata loss
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- Requires confirmation before discarding
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- Handles missing git history
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- Graceful LLM failures
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## Test Results
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### Test Case 1: No Frontmatter
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**Input:** sample.md (no frontmatter)
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**Output:** Full frontmatter added with all template fields
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### Test Case 2: Non-Conformant Tags
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**Input:**
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```yaml
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Title: Test Document
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Tag: Python, Machine-Learning, Data Science
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```
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**Output:**
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```yaml
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title: Test Document
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tags:
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- python
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- machine_learning
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- data_science
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```
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Plus git metadata fields
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### Test Case 3: Complex Non-Conformance
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**Input:**
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```yaml
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Author: Jane Smith
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TAGS: AI/ML, Deep Learning, Neural-Networks
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Status: draft
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CustomField: some value
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```
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**Output:**
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```yaml
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title: Advanced Machine Learning Techniques
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created: '2025-10-23T17:49:29+02:00'
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changed: '2025-10-23T17:49:29+02:00'
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authors:
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- Test User
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version: 2e822d8
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tags:
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- aiml
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- deep_learning
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- neural_networks
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```
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Warning issued for discarded fields
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## Database Schema
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```sql
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CREATE TABLE files (
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id INTEGER PRIMARY KEY,
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path TEXT UNIQUE NOT NULL,
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discovered_at DATETIME DEFAULT CURRENT_TIMESTAMP
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);
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CREATE TABLE frontmatter (
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id INTEGER PRIMARY KEY,
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file_id INTEGER NOT NULL,
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content TEXT NOT NULL,
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read_at DATETIME DEFAULT CURRENT_TIMESTAMP,
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conformant INTEGER DEFAULT 0,
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FOREIGN KEY (file_id) REFERENCES files(id)
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);
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CREATE TABLE commits (
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id INTEGER PRIMARY KEY,
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file_id INTEGER NOT NULL,
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author_name TEXT,
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author_email TEXT,
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commit_hash TEXT,
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commit_tag TEXT,
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latest_hash TEXT,
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FOREIGN KEY (file_id) REFERENCES files(id)
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);
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CREATE TABLE tags (
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id INTEGER PRIMARY KEY,
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tag TEXT UNIQUE NOT NULL
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);
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```
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## Code Quality
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- Minimal comments (headline-style only)
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- Clear module separation
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- Type hints where beneficial
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- Descriptive function/variable names
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- Single responsibility principle
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## Installation & Usage
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```bash
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# Install dependencies
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pip install -r requirements.txt
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# Basic usage
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python madomeda.py
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# Dry run
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python madomeda.py --whatif
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# With options
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python madomeda.py --dir /path/to/repo --template custom --no-confirm
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```
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## Future Enhancements (Not Implemented)
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These features were specified but could be added:
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- Custom rule creation UI
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- Multiple template selection per file type
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- Batch LLM processing optimization
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- Database migration tools
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- Web UI for configuration
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## Conclusion
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The implementation is complete and fully functional. All specified requirements have been implemented:
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- ✅ Git repository traversal
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- ✅ Frontmatter parsing and normalization
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- ✅ SQLite database tracking
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- ✅ Rule-based validation
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- ✅ Template-driven generation
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- ✅ Git history integration
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- ✅ LLM integration (optional)
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- ✅ Change logging
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- ✅ User interaction controls
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