1. Module Cycles: properly format cycle paths as A → B → C → A
2. Repository layout: group by top-level directory with file counts
3. Integration detection: match patterns against import names (substring),
add Storage and AI/ML categories to all templates and summary
4. Usage examples: extract __init__ required params for class constructors
Also fix golden test to use ends_with for module-prefixed symbol IDs.
- renderer: render_architecture_md accepts Config, uses project name and current date
- renderer: generate real Python usage examples from analyzed symbols
- writer: skip writing files when content unchanged (optimization)
- cli: add --dry-run flag to generate command (lists files without writing)
- cli: add verbose logging for file/module/symbol generation progress
- Test config loading and validation on test-project
- Test scanning Python files from test-project
- Test cycle detection with known cyclic and acyclic graphs
- Test renderer output generation
- Test duration and file size parsing
- Introduced `archdoc.toml` configuration file for project settings, including scanning and analysis options.
- Created initial `ARCHITECTURE.md` file with project summary and structure.
- Generated documentation files for source files and modules, including placeholders for future content.
- Updated the documentation generation logic to handle new project structure and file paths.
- Created `.gitignore` files for various directories to exclude unnecessary files.
- Added `PLAN.md` to outline the project goals and architecture documentation generation.
- Implemented the `archdoc-cli` with a command-line interface for initializing and generating documentation.
- Developed the `archdoc-core` library for analyzing Python projects and generating architecture documentation.
- Included caching mechanisms to optimize repeated analysis.
- Established a comprehensive test suite to ensure functionality and error handling.
- Updated `README.md` to provide an overview and installation instructions for ArchDoc.
