recursive-self-improvement递归自我改进系统，能够自动检测错误并修复，或持续优化和重构。包含修复模式和优化模式，支持并发执行、自动化测试、性能监控、智能调度、自适应学习、错误预测和异常恢复。用于需要持续自我优化的系统。
Install via ClawdBot CLI:
clawdbot install Erichy777/recursive-self-improvement系统有两种基本工作模式，根据系统状态自动切换：
触发条件： 检测到错误或异常
工作流程：
系统状态： REPAIRING → REPAIRED → STABLE
触发条件： 系统稳定运行，无错误超过 N 轮
工作流程：
系统状态： OPTIMIZING → OPTIMIZED → STABLE
INITIAL: 初始状态REPAIRING: 修复模式中OPTIMIZING: 优化模式中STABLE: 稳定运行ERROR: 检测到错误OPTIMIZED: 已优化完成系统支持多任务并发执行：
任务池 → 智能调度 → 并发执行 → 结果收集调度策略：
默认配置：
系统内置测试框架：
测试类型：
测试覆盖率：
实时监控以下指标：
系统状态：
性能指标：
基于历史数据和预测的智能调度：
优先级计算：
调度策略：
从执行中学习，持续优化：
学习内容：
预测能力：
提前识别潜在错误：
预测维度：
预测阈值：
智能错误处理和恢复：
内置策略：
TIMEOUT: 重试 + 指数退避MEMORY_ERROR: 并行化处理CONCURRENCY_LIMIT: 动态调整并发数恢复流程：
每次运行记录使用标准格式：
{
"timestamp": "2026-02-05T21:55:00Z",
"mode": "REPAIRING | OPTIMIZING | STABLE",
"action": "fix | refactor | validate | monitor",
"previous_state": "状态名称",
"current_state": "状态名称",
"details": "详细描述",
"results": {
"key1": true/false,
"key2": "value"
}
}系统自动管理版本：
版本格式： vN.M
升级规则：
升级条件：
何时使用：
最佳实践：
可在配置文件中调整：
{
"optimization": {
"min_stable_rounds": 3,
"max_concurrent_tasks": 8,
"timeout_seconds": 5
},
"testing": {
"target_coverage": 80,
"critical_coverage": 100
},
"monitoring": {
"metrics_interval": 60,
"alert_thresholds": {
"cpu": 80,
"memory": 90
}
}
}Generated Mar 1, 2026
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