tegwick 87e970bbee feat: implement intelligent auto-sizing textarea for optimal editing UX
Enhanced the editing experience with smart textarea sizing that adapts
to content dimensions:

Smart Auto-Sizing Logic:
- Dynamically calculates height based on content lines
- Minimum height: 3 lines (63px) for comfortable editing
- Maximum height: 20 lines (444px) to prevent excessive expansion
- Precise calculation using line-height and padding measurements

Responsive Behavior:
- Auto-resizes on input events as you type
- Handles paste operations with proper sizing
- Smooth transitions with 0.15s ease animation
- Temporarily disables transition during measurement for accuracy

Technical Implementation:
- Line-height aware calculation (14px font × 1.5 = 21px per line)
- Proper padding compensation (24px total)
- Scroll-height based measurement for precise content fitting
- Debounced initial sizing to handle DOM rendering

User Experience Benefits:
- Textarea perfectly fits content size on open
- No unnecessary white space for short content
- Sufficient space for longer content without overwhelming
- Natural, document-like editing experience
- Visual harmony with surrounding content boxes

CSS Enhancements:
- Reduced min-height from 100px to 60px for better proportions
- Added smooth height transitions for polished feel
- Maintained vertical resize capability for user control
- Proper box-sizing for consistent measurements

This creates a much more natural editing experience where the textarea
intelligently adapts to match the content being edited.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-25 21:53:49 +02:00
2025-10-03 03:39:43 +02:00
2025-10-03 03:39:43 +02:00
2025-10-06 22:51:38 +02:00

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.

  • Caching System - Why and how MarkiTect's AST caching delivers 60-85% performance improvements
  • Coming soon: Database Schema, CLI Architecture, Plugin System

👥 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

For Users

For Developers

Project Management

Key Concepts

Core Architecture Principles

  1. Parse Once, Use Many Times - AST caching for 60-85% performance improvement
  2. Convention Over Configuration - Sensible defaults with minimal setup
  3. Schema-Driven Processing - Structured markdown with validation
  4. 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:

  1. Clear Structure - Logical organization and navigation
  2. Practical Examples - Real-world usage patterns
  3. Performance Context - Why architectural decisions matter
  4. 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.

Description
An advanced markdown engine
https://coulomb.social/open/MarkiTect
Readme 34 MiB
2025-11-08 20:34:42 +00:00
Languages
Python 84.7%
JavaScript 8%
HTML 5.6%
Makefile 1.3%
Shell 0.2%
Other 0.1%