CatSyphon: Analyze your AI coding assistant conversations (github.com)

CatSyphon has launched a tool for analyzing interactions with AI coding assistants, allowing users to track conversations, uncover usage patterns, and optimize their workflows. This open-source project enables developers to import and analyze their coding logs from AI models like Claude Code and OpenAI Codex. Key features include the ability to view session histories, identify effective coding strategies, and evaluate the impact of AI assistance on coding tasks through detailed analytics and sentiment tracking. This tool is significant for the AI/ML community as it empowers developers to refine their interactions with AI coding assistants, enhancing productivity and collaboration. By providing insights into task success rates, agent effectiveness, and collaboration clarity, CatSyphon can help users adopt best practices and recognize areas for improvement in their coding processes. With a backend built on Python 3.11 and FastAPI and a frontend utilizing React and TypeScript, CatSyphon is designed for flexibility, allowing for both local analysis and potential enterprise-level deployment.