An advanced markdown engine
tegwick
c4ee5cc645
Created comprehensive changelog-schema-v1.0.md to validate CHANGELOG.md files following the Keep a Changelog format. This schema demonstrates the practical application of the schema evolution system. **Schema Features**: - Section validation: Enforces [Unreleased] section presence - Version format validation: [X.Y.Z] - YYYY-MM-DD pattern - Semantic versioning compliance - ISO 8601 date format checking - Change type subsections: Added, Changed, Deprecated, Removed, Fixed, Security - Content pattern matching via x-markitect-content-control extensions - Structural validation via JSON Schema properties **Validation Results**: ✅ Successfully validates project CHANGELOG.md ✅ All section requirements met (7 sections checked, 11 found) ✅ All content requirements met ✅ All semantic checks passing **Implementation Notes**: - H1 "Changelog" title validated via JSON Schema structural checks - H2 sections validated via x-markitect-sections classifications - SectionValidator limitation: Only checks H2+ headings, not H1 - Workaround: Structural validation covers H1 title requirement **Philosophy**: "The release that validates itself" - v0.10.0 uses its own schema system to validate its CHANGELOG - Perfect showcase of schema evolution practical value - Demonstrates x-markitect extensions in real-world use case **Stage 2 Complete** per release-management-optimization workplan. Files: - markitect/schemas/changelog-schema-v1.0.md (new) - CHANGELOG.md (documented new schema) |
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| agents | ||
| application | ||
| assets | ||
| capabilities | ||
| config | ||
| cost_notes | ||
| docs | ||
| domain | ||
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| guides | ||
| history | ||
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| markitect | ||
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| tools | ||
| wiki@8818df03d3 | ||
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| aliases.sh | ||
| asset_registry.json | ||
| CHANGELOG.md | ||
| demo_plugin_integration.py | ||
| GUARDRAILS.md | ||
| install | ||
| install.py | ||
| install.sh | ||
| Makefile | ||
| package-lock.json | ||
| package.json | ||
| pyproject.toml | ||
| pytest-timeout.ini | ||
| pytest.ini | ||
| test_asset_deployment.py | ||
| test_browser_ready.py | ||
| test_cli_integration.py | ||
| test_cli_plugin.md | ||
| test_cli_simple.py | ||
| test_cli_with_assets.py | ||
| test_complete_integration.py | ||
| test_integration.md | ||
| test_plugin_discovery.py | ||
| test_strict_mode.html | ||
| TODO.md | ||
MarkiTect Documentation
Welcome to the MarkiTect documentation. This directory contains comprehensive documentation for developers, users, and contributors.
Documentation Structure
📐 Architecture Documentation (architecture/)
Deep technical documentation about system design, performance, and implementation details.
- Capabilities Architecture - Critical: How capabilities work as independent git submodules and separation of concerns
- Caching System - Why and how MarkiTect's AST caching delivers 60-85% performance improvements
- Coming soon: Database Schema, CLI Architecture
👥 User Guides (user-guides/)
End-user documentation for working with MarkiTect CLI and features.
- Coming soon: Getting Started, Command Reference, Best Practices
🔧 Development Documentation (development/)
Documentation for contributors and developers extending MarkiTect.
- Coming soon: Contributing Guide, Testing Strategy, Release Process
Quick Links
For Users
- Installation & Setup
- Command Reference (coming soon)
- Performance Guide (coming soon)
For Developers
- Architecture Overview - System design and component relationships
- Development Setup - Local development environment
- API Documentation (coming soon)
Project Management
- Project Status - Current development status
- Roadmap - Strategic development plan
- Current Tasks - Task management using Keep a Todofile format
Key Concepts
Core Architecture Principles
- Parse Once, Use Many Times - AST caching for 60-85% performance improvement
- Convention Over Configuration - Sensible defaults with minimal setup
- Schema-Driven Processing - Structured markdown with validation
- Relational Metadata - Database-powered document relationships
Performance Philosophy
MarkiTect treats markdown documents as structured, queryable data rather than plain text. This approach enables:
- Lightning-fast document processing through intelligent caching
- Complex querying and relationship management
- Schema validation and consistency enforcement
- Scalable performance that grows with your content
Contributing to Documentation
Documentation follows the same quality standards as code:
- Clear Structure - Logical organization and navigation
- Practical Examples - Real-world usage patterns
- Performance Context - Why architectural decisions matter
- User-Focused - Written for the intended audience
Documentation Standards
- Use clear, concise language
- Include practical examples
- Explain the "why" behind design decisions
- Keep technical accuracy as the highest priority
- Update docs when changing functionality
This documentation is maintained alongside the codebase. For the most current information, always refer to the latest version in the repository.