Memory Sync

About

Memory Sync provides a structured workflow for developers to maintain 'strategic redundancy' between concise AI-focused context (memories) and comprehensive documentation. It guides users through assessing codebase changes, updating token-efficient memory files, and flagging necessary documentation updates after significant milestones or architectural shifts. By ensuring both the AI agent and the human developer have accurate, up-to-date information, this skill prevents context drift and improves development efficiency during complex projects.

Key Features

• Structured workflow for updating token-efficient project memories
• Guided assessment of codebase changes via automated git analysis
• Impact analysis for architectural, convention, and workflow changes
• 0 GitHub stars
• Validation tools to ensure memory size remains within optimal token limits
• Standardized checklist templates for consistent synchronization after milestones

Use Cases

• Synchronizing documentation after completing a major project phase or milestone
• Updating AI context when new architectural patterns or naming conventions are introduced
• Maintaining high-quality human-readable docs that match the AI's internal project understanding