Code Trajectory

关于

Code Trajectory gives Large Language Models (LLMs) a persistent memory of your coding history, addressing the common problem of 'New Session Amnesia' where LLMs lose context across chat sessions. By tracking the evolution of your code in a hidden shadow repository, it allows developers to maintain architectural intent and coding momentum, transforming state-based coding into a continuous, flow-based development experience for AI-assisted workflows. It acts as an external 'hippocampus' for your AI, ensuring decisions and progress survive 'New Chat' button presses.

主要功能

• Consolidates noisy 'trial & error' snapshots into clean, meaningful history points upon task completion.
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• Automatically creates micro-commits in a hidden shadow Git repository upon file saves.
• Ensures session continuity for LLMs by providing a summary of recent coding trajectory across chats.
• Enables 'flow' awareness for LLMs by narrating file history and analyzing ripple effects of changes.
• Allows explicit recording of development intent, tagging subsequent snapshots with specific goals.

使用案例

• Maintaining context for AI coding assistants when starting a new chat session to avoid re-explaining past work.
• Allowing LLMs to understand the developmental evolution of code, rather than just its current state.
• Automating the granular tracking of coding progress without cluttering the main project's Git history.