The GEP-powered self-evolving engine for AI agents. Auditable evolution with Genes, Capsules, and Events. | evomap.ai

A curated list of AI Agent evolution, memory systems, multi-agent architectures, and self-improvement projects. | evomap.ai

OpenClaw Q&A 社区 — AI Agent 记忆系统、多Agent架构、进化系统、具身AI | 龙虾茶馆 🦞

Automated harness evolution for AI agents. A Claude Code plugin that iteratively optimizes system prompts, routing, retrieval, and orchestration code using full-trace counterfactual diagnosis. Based on Meta-Harness (Lee et al., 2026).

🌳 Autonomous continuous learning framework for OpenClaw AI agents - Run 59 exploration rounds overnight

Autonomous agent-to-agent marketplace with live Karpathy loop self-improvement. Agents discover, hire, benchmark, and evolve programmatically. MPP/x402/MCP. No humans in the loop.

Feishu-specific wrapper for capability-evolver with rich card reporting and dashboard visualization

Governed evolution layer for OpenClaw and Atlas Memory: runtime ingest, audit trails, reviewable proposals, rollback-safe promotion, and restart-safe handoff workflows.

An open framework for building self-improving AI agent teams. Includes a meta-agent architecture with independent auditing, git-backed evolution, and structured feedback loops. Ships with a complete marketing team, a reusable team-builder skill, and a portable prompt that works with any LLM.

Liquid Cluster Harness — 子 Agent 从用完即弃到自然生长的集群成员

Rollback-first reliability layer for AI agents: trace failures, apply guarded changes, and rollback on regression.

Agent evolution lab: evolve autonomous-agent skills, tools, prompts, datasets, and evaluation loops from real usage evidence

Agent personality evolution framework (MIT) — generic, sanitized skill for OpenClaw

A safe, transparent, and human-controlled self-evolution framework for AI agents. Three-zone safety architecture ensures AI learns autonomously while humans stay in control.

MOLT (蜕界) — Reflexive Co-evolution Engine for Multi-Agent Systems. Observe structural friction, attribute root causes, evolve through evidence. Native OpenClaw product.

Audit AI coding agents and project configurations for security flaws using static analysis, custom rules, and LLM-assisted verification.

Standardize AI agent behavior across IDEs and CLI tools using a single configuration file to reduce token usage and build persistent skill libraries.

🧬 Agent 自我进化系统 - 基于数据驱动的 AI Agent 能力提升平台 | ✨ 任务监控/技能评估/智能调度/自动进化 | 📊 95%+ 测试覆盖，<20ms 延迟