Generates structured Markdown learning notes and tracks educational progress from AI-assisted coding sessions.
Study Summary is a specialized skill designed to bridge the gap between AI-driven learning and long-term knowledge retention. It analyzes coding conversations—specifically those following the 'Core Loop' learning pattern—to extract key concepts, mental models, and code examples. By offering both a concise 'Classic' mode for quick recaps and a 'Mastery' mode for detailed tracking of misconceptions and seed code history, it ensures that every insight gained during a session is documented and stored for future review within your repository.
Key Features
01Persistent progress tracking using MCP memory to record misconceptions
02Dual-mode note generation (Classic vs. Mastery) based on learning depth
03Standardized Markdown output with built-in review questions and diagrams
04Automated conversation scanning to extract rules and seed code history
05Bilingual support (Korean/English) with beginner-friendly terminology policies
0618 GitHub stars
Use Cases
01Tracking personal progress and specific misconceptions to prevent repeating architectural mistakes
02Creating a searchable library of 'seed code' examples and Apple documentation references
03Documenting Swift and iOS development concepts learned during an AI pair-programming session
