Captures AI agent corrections, extracts reusable behaviors, and activates them contextually to improve agent performance.
Sponsored
Floop provides persistent memory for AI coding agents, learning from your corrections to extract reusable behaviors and activate them context-awarely. Inspired by cognitive science, it uses spreading activation to build an associative 'blast radius' around your current work, pulling in not just direct matches but also related behaviors that offer useful context and bolster the AI's understanding. This ensures agents learn from mistakes and maintain consistency across sessions.
Key Features
01Learns from agent corrections to create durable behaviors
025 GitHub stars
03Context-aware behavior activation based on file type, task, and semantic relevance
04Spreading activation memory inspired by cognitive science for associative context retrieval
05Token-optimized assembly for budget-aware context injection
06MCP server integration for seamless use with AI tools like Claude Code
Use Cases
01Training AI coding agents with persistent memory and learned behaviors
02Integrating context-aware behavioral learning into AI development workflows
03Maintaining consistent AI agent performance across various coding sessions and projects
