An advanced markdown engine
tegwick
246decbcac
Implemented comprehensive content command family for MarkdownMatters CLI following TDD8 methodology and MarkdownMatters specification. ## TDD8 Cycle 1 - Content Commands ### Core Implementation - Content parser for extracting main content without matter zones - Content statistics calculator (words, lines, paragraphs, characters) - CLI commands: `content-get` and `content-stats` - Full integration with existing markitect CLI ### MarkdownMatters Compliance - Correctly removes YAML/TOML/JSON frontmatter - Correctly removes tailmatter blocks (`yaml tailmatter`, `json tailmatter`) - Preserves contentmatter (MultiMarkdown key-value pairs within content) - Follows three-zone specification from wiki/MarkdownMatters.md ### Module Structure ``` markitect/content/ ├── __init__.py # Module exports ├── parser.py # ContentParser with matter zone removal ├── stats.py # ContentStats data class └── commands.py # CLI commands implementation ``` ### CLI Commands Added - `markitect content-get --file [path]` - Extract pure content - `markitect content-stats --file [path]` - Calculate content statistics ### Test Coverage - 16 comprehensive tests covering all scenarios - Test fixtures for different document types - CLI integration tests with Click testing - Edge case handling (file not found, empty content, etc.) ### Validation Results - All tests pass (16/16) - Manual CLI testing confirmed - Proper matter zone separation validated - Statistics calculation accuracy verified ## Technical Architecture ### ContentParser Class - `extract_content()` - Remove frontmatter and tailmatter - `calculate_stats()` - Generate comprehensive statistics - `_remove_frontmatter()` - YAML frontmatter removal - `_remove_tailmatter()` - Tailmatter block removal ### ContentStats Data Class - word_count, line_count, paragraph_count, character_count - JSON serialization support via `to_dict()` ## GAMEPLAN Progress - ✅ TDD8 Cycle 1: Content Commands (COMPLETE) - 🔄 Next: Cycle 2 - Frontmatter Commands - Remaining: Contentmatter, Tailmatter command families This implements the foundation for Issue #38 with 6 remaining cycles planned for complete MarkdownMatters CLI functionality. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> |
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| .claude/agents | ||
| .github/workflows | ||
| .issues | ||
| .venv_old | ||
| application | ||
| cli | ||
| config | ||
| docs | ||
| domain | ||
| examples | ||
| gitea | ||
| history | ||
| infrastructure | ||
| markitect | ||
| services | ||
| tddai | ||
| tests | ||
| tools | ||
| wiki@648d8247c4 | ||
| .env.tddai | ||
| .gitignore | ||
| .gitmodules | ||
| AGENT_TOOLING_OPTIMIZATION_REPORT.md | ||
| ARCHITECTURAL_CHAOS_TESTING_ISSUE.md | ||
| ARCHITECTURE.md | ||
| AUTONOMOUS_WORK_REMINDER.md | ||
| CAPABILITIES.md | ||
| CONFIG.md | ||
| DOMAIN_LOGIC_SEPARATION_DEMO.md | ||
| ERROR_HANDLING_GUIDE.md | ||
| FEATURES.md | ||
| gitea_issue_body.txt | ||
| install-claude.sh | ||
| install-cursor.sh | ||
| install-depends.sh | ||
| install-nvm.sh | ||
| install-pip.sh | ||
| ISSUE_46_COMPLETION.md | ||
| ISSUE_WORKFLOW_REMINDER.md | ||
| LEGACY_AGENT_GUIDE.md | ||
| LEGACY_COMPATIBILITY_SYSTEM.md | ||
| Makefile | ||
| NEXT_SESSION_BRIEFING.md | ||
| ProjectStatusDigest.md | ||
| pyproject.toml | ||
| pytest-timeout.ini | ||
| pytest.ini | ||
| README.md | ||
| RelevantClaudeIssues.md | ||
| retrieved_roundtrip.md | ||
| ROADMAP.md | ||
| run_architectural_tests.py | ||
| run_randomized_tests.py | ||
| schema_summary.py | ||
| tddai-setup.sh | ||
| tddai_cli.py | ||
| tddai_issue_body.txt | ||
| TEST_ARCHITECTURE.md | ||
| test_frontmatter.md | ||
| test_roundtrip.md | ||
| test_status_report.md | ||
| visualize_schema.py | ||
MarkiTect - Advanced Markdown Engine
Your Markdown, Redefined.
MarkiTect transforms markdown from plain text into intelligent, structured data with performance optimization, schema validation, and relational querying capabilities. Stop treating documentation as text files—start managing it as a database.
Key Features:
- Lightning Performance: 60-85% faster document processing through intelligent AST caching
- Schema Validation: Enforce document structure and consistency
- Database Integration: Query markdown content with SQL-like operations
- CLI Tools: Complete command-line interface for automation and workflows
📚 Documentation
Quick Start: Getting Started · Command Reference
Architecture: Caching System · Performance Philosophy
Development: TDD Workflow · Contributing
Project Status: Current Status · Roadmap · Next Actions