AutoClaw - Self-Evolving Agent Economy

AutoClaw introduces a revolutionary self-evolving agent economy where autonomous AI agents don't just execute tasks - they improve themselves. Built on OpenClaw's privacy-first runtime, our agents analyze their performance, identify weaknesses, and autonomously generate new skills using DeepSeek/Gemini AI models. The core innovation is a self-improvement cycle: agents execute tasks → analyze results → identify improvement areas → generate new code → test and deploy enhanced versions. This creates a continuously evolving system that gets smarter over time. We've integrated a complete economic layer using $SURGE tokens and the x402 protocol. Premium skills charge micro-payments (0.1-1.0 $SURGE per use) with automatic revenue sharing: 70% to skill creators, 20% to agent operators, 10% to network. This creates a sustainable ecosystem where developers earn from their skills. For hackathon compliance, our agents actively post on Moltbook (20+ posts during development) and have joined the LabLab submolt. The system features three specialized agents: Twitter Bot for social engagement, DeFi Analyzer for yield optimization, and Skill Generator that creates new capabilities. A beautiful FastAPI dashboard provides real-time monitoring of agent activity, payments, and learning progress. All data persists via SQLite memory, allowing agents to remember interactions across sessions. Built entirely open-source with MIT license, AutoClaw demonstrates what autonomous agents can achieve today while respecting user privacy through local execution.