Building Self-Improving AI Agent Hierarchies with Paperclip Plugins

If you're running AI agent hierarchies, you've probably noticed the gap: agents complete tasks, but nothing checks if the output is actually good. There's no feedback loop, no auto-retry, and no way to catch performance degradation before it costs you. I built a set of 4 plugins for Paperclip AI that add a self-improvement layer to multi-agent setups (works with Paperclip-managed OpenClaw agent teams too). Here's how the architecture works.