# MarkiTect Project - Status Digest **Version:** 0.1.0 **Last Updated:** 2025-09-22 **Tagline:** "Your Markdown, Redefined" ## Core Vision Transform Markdown from plain text into intelligent, structured, reusable data with schema validation and automation capabilities. ## Architecture Overview ### MarkiTect Library (Python Core) - **Reusable Python package** designed for CLI, service offerings, and third-party integration - **TDD approach** with comprehensive test coverage and pytest framework - **Modern packaging** using `pyproject.toml` and semantic versioning - **Minimal dependencies** with `markdown-it-py` as primary parser ### TDD Infrastructure (tddai Library) - **Complete TDD workspace management** with Python library architecture - **Issue-driven development** with Gitea API integration - **AI-assisted test generation** framework for automated TDD workflows - **Workspace lifecycle management** from issue creation to test integration - **CLI interface** (`tddai_cli.py`) for seamless command-line operations ### MarkiTect CLI (Command-Line Interface) - **SQLite database** for temporary, in-memory operations - **GraphQL API** using `graphene` library for read/write operations - **SQLAlchemy ORM** for data modeling (MarkdownFile, SchemaFile, AST content) - **JSON Schema validation** using `jsonschema` library ## Key Features & Components ### Core Functionality - **AbstractSyntaxTree** processing and manipulation - **MarkdownParser** using `markdown-it-py` for detailed AST generation - **JsonSchemaValidator** for enforcing document structure - **ChunkInclusion** system for modular content composition - **StaticSiteGenerator** integration capabilities ### Schema Operations - **Generate schemas** from existing Markdown at specified nesting depths - **Validate Markdown** against defined schemas - **Generate stub files** from schemas with placeholder content - **InclusionStub** handling for modular document architecture ### GraphQL Interface - **Query operations** for retrieving Markdown files, schemas, and AST data - **Mutation operations** for adding/updating content in database - **Real-time validation** and schema checking ## Development Approach ### Test-Driven Development - **Complete TDD infrastructure** with `tddai` Python library - **Issue-driven workflow** with workspace management (`tdd-start`, `tdd-add-test`, `tdd-status`, `tdd-finish`) - **20+ passing tests** using pytest with proper behavior-based testing - **AI-assisted test generation** integrated into development cycle - **Green-state validation** before all commits ### Markdown Feature Support (MF-1 through MF-10) Complete specification coverage including: - Headings and sections structure - Text formatting (bold, italic, strikethrough) - Lists (ordered, unordered, task lists) - Links, images, and media handling - Code blocks and syntax highlighting - Tables and complex formatting - Footnotes and reference systems ## Project Status ### Current State - **TDD infrastructure complete** with robust Python library architecture - **Issue-driven development workflow** fully operational - **Comprehensive test suite** with 20 passing tests and pytest integration - **Build system** with sophisticated Makefile and virtual environment integration - **AI-assisted development** cycle with workspace management ### Social Integration - **CoulombSocial participation** since September 2025 - **Gitea issues integration** with API-driven workflow management - **Open-source development** model with collaborative wiki - **Issue-to-test automation** for structured development cycles ## Technical Foundation ### Development Tools - **Python 3.8+** with modern tooling (Black, Ruff, mypy, pytest) - **Make-based workflow** with intelligent environment detection and TDD integration - **Git submodules** for wiki documentation management - **tddai library** for complete TDD workspace automation - **Issue management** with Gitea API integration and CLI tools ### Brand Identity - **Professional visual identity** with 3D "M" logo incorporating Markdown symbols - **Color palette**: Deep teal/navy (primary), vibrant orange, lime green - **Core pillars**: Structural Integrity, Consistency, Reusability, Automation ## Repository Structure ``` markitect_project/ ├── markitect/ # Main Python package │ ├── __init__.py │ └── parser.py # Core parsing functionality ├── tddai/ # TDD infrastructure library │ ├── __init__.py # Package exports │ ├── workspace.py # Workspace lifecycle management │ ├── issue_fetcher.py # Gitea API integration │ ├── test_generator.py # AI-assisted test generation │ ├── config.py # Configuration management │ └── exceptions.py # Custom exception hierarchy ├── tests/ # Comprehensive test suite (20+ tests) │ ├── test_parser.py # Parser tests │ ├── test_issue_11_*.py # TDD infrastructure tests │ └── test_*.py # Additional test modules ├── tddai_cli.py # TDD CLI interface ├── wiki/ # Git submodule with comprehensive documentation ├── Makefile # Development workflow automation with TDD targets ├── pyproject.toml # Python package configuration ├── ProjectStatusDigest.md # This document ├── ProjectDiary.md # Development milestone tracking └── README.md # Project overview ``` ## Getting Started 1. **Environment Setup:** ```bash make setup # Create venv and install dependencies make venv-status # Check environment activation state ``` 2. **Development Workflow:** ```bash make test # Run comprehensive test suite (20+ tests) make update # Pull latest changes from upstream make status # Check git status ``` 3. **TDD Workflow:** ```bash make tdd-start NUM=X # Start working on issue X make tdd-add-test # Generate tests for current issue make tdd-status # Check workspace status make tdd-finish # Complete issue and integrate tests ``` 4. **Issue Management:** ```bash make list-issues # Show all Gitea issues make list-open-issues # Show active backlog make show-issue NUM=X # Detailed issue view ``` 5. **Building:** ```bash make build # Build the package make clean # Clean build artifacts ``` --- MarkiTect represents a significant evolution toward treating documentation as **structured, validatable, and reusable data** rather than simple text files, with robust tooling for large-scale content management and automation. > **Note:** This digest is maintained using Claude Code. 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