每日备份 2026-06-10 12:57:13
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# Errors
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Error logs and failure patterns for **skill-self-evolution-enhancer**.
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**Categories**: timeout | context_overhead | missing_data | workflow_error
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**Statuses**: pending | in_progress | resolved | wont_fix | promoted
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## Status Definitions
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| Status | Meaning |
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|--------|---------|
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| `pending` | Not yet addressed |
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| `in_progress` | Actively being worked on |
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| `resolved` | Issue fixed or workaround found |
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| `wont_fix` | Decided not to address |
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| `promoted` | Elevated to evolution rules |
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## Error Entry Format
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```markdown
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## [ERR-YYYYMMDD-XXX] category
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**Logged**: ISO-8601 timestamp
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**Priority**: low | medium | high | critical
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**Status**: pending
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**Area**: 领域
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### Summary
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One-line description
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### Details
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Full context
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### Root Cause
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Likely cause if known
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### Workaround
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What was tried or could be tried
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### Metadata
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- Source: error_log | user_report | test
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- Tags: tag1, tag2
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- Recurrence-Count: 1
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---
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```
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## [ERR-20260326-001] cron_timeout_context_overhead
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**Logged**: 2026-03-26T04:14:00Z
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**Priority**: high
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**Status**: resolved
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**Area**: cron任务调度
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### Summary
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cron agentTurn timeout设置120s但实际超时，原因是session上下文大(205k)导致agent处理慢
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### Details
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- 脚本 `evolution-report.sh` 本身执行仅需 4秒
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- 但 cron agentTurn 报告超时 120028ms（连续3次）
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- session 状态显示: `unknown/205k (?%)` 说明上下文很大
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- 日志分析显示脚本实际在 4s 内完成
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### Root Cause
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timeoutSeconds 设置的是 cron job 的硬性超时，但 OpenClaw agent 处理大上下文时初始化+推理本身就耗时很长，与实际脚本执行时间无关
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### Workaround
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将 `timeoutSeconds` 从 120 降到 60（脚本只需4s，60s足够让agent初始化完成）
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已对 `dbd84977`（GitHub进化猎手）和 `b0afa4db`（日志清理）应用修复
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### Metadata
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- Source: heartbeat_analysis
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- Tags: cron, timeout, context-size, self-healing
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- Recurrence-Count: 3
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- See Also: HEARTBEAT.md
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---
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## [ERR-20260326-002] resource_guard_cpu_parsing_bug
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**Logged**: 2026-03-26T09:25:00Z
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**Priority**: high
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**Status**: resolved
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**Area**: 资源监控
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### Summary
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资源守卫脚本CPU解析bug：int($2)对"4.5"返回0，显示95%而非5%
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### Details
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- `top -bn1 | grep "Cpu(s)"` 输出: `4.5 us, 0.0 sy, 0.0 ni, 95.5 id`
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- 脚本用 `awk '{print int($2)}'` 取字段2，得到 `4.5`，但 `int("4.5")` 在awk中返回 0
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- 导致 CPU 显示为 idle 字段值（95%），实际是空闲95%，使用仅5%
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### Root Cause
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awk int()函数对含小数点的字符串处理有误，且脚本逻辑不对：应该用 idle 计算使用率，而非直接取us字段
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### Workaround
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修改为 `cpu_usage=$(top -bn1 | grep "Cpu(s)" | awk '{print int($8)}')` 然后 `cpu_usage=$((100 - cpu_usage))`
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### Metadata
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- Source: heartbeat_false_alarm
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- Tags: monitoring, awk, parsing
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- Recurrence-Count: 1
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- File: /home/yh6788/.openclaw/scripts/resource-guard.sh
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---
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## [ERR-20260326-002] camoufox_browse_headless_crash
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**Logged**: 2026-03-26T14:01:00Z
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**Priority**: high
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**Status**: resolved
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**Area**: 浏览器自动化
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### Summary
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camoufox browse.py 硬编码 headless=False，在服务器上会卡住等待用户输入
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### Details
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- 原脚本最后有 input("Press Enter to close...")，headless模式下无法交互
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- 原脚本没有 headless 参数选项
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- camoufox 安装在 ~/.local/lib/python3.13/site-packages/，不在 venv 里
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### Root Cause
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脚本设计假设在有GUI环境运行，未考虑服务器无头模式
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### Workaround
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修复后的 browse.py:
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1. 添加 --headless 参数
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2. 无DISPLAY时自动启用headless
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3. headless模式下跳过等待用户输入
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4. 添加 USER_SITE 路径到 sys.path
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### Metadata
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- Source: self_discovery
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- Tags: camoufox, headless, server
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- Recurrence-Count: 1
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- See Also: camoufox/scripts/browse.py
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---
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## [ERR-20260327-001] log_cleaner_timeout
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**Logged**: 2026-03-27T18:35:00Z
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**Priority**: high
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**Status**: resolved
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**Area**: cron任务调度
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### Summary
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日志清理脚本本身只需1.3秒，但cron timeout 60秒仍超时
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### Root Cause
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同GitHub进化猎手问题：agent初始化（含session加载、context初始化）耗时远超脚本执行时间
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### Workaround
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将timeout从60s降到30s，脚本仅需1.3s，30s足够agent初始化完成
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### Metadata
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- Source: heartbeat_check
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- Tags: cron, timeout, agent-initialization
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- Recurrence-Count: 2
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- See Also: ERR-20260326-001
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---
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## [ERR-20260327-001] cron_timeout_agent_context_overhead_v2
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**Logged**: 2026-03-27T03:05:00Z
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**Priority**: high
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**Status**: resolved
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**Area**: cron任务调度
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### Summary
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降低cron timeout反而导致更多超时：agent加载205k上下文需要60-120s
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### Details
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- 脚本本身执行只需 1.2 秒
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- 但 agent 加载 205k 上下文需要 60-120s
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- 60s timeout: 持续超时
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- 180s timeout: 足够agent初始化完成
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### Root Cause
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OpenClaw agentTurn timeout 指的是 agent 整个执行周期，不是脚本执行时间。agent 需要时间初始化大上下文 session。
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### Workaround
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对于简单脚本任务，timeout 应设置为 120-300s，保证 agent 有足够时间初始化后再执行脚本
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### Metadata
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- Source: heartbeat_analysis
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- Tags: cron, timeout, context-size, agent-overhead
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- Recurrence-Count: 2
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- See Also: ERR-20260326-001
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---
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## 2026-03-27 日志清理超时问题
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**问题**: log-cleaner.sh 连续2次 timeout（cron 设置 60s）
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**根因**: 逐文件循环 `stat` + 条件判断，大目录极慢
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**解决方案**: 改用 `find -mtime +N -print -delete` 批量操作，timeout 提升至 120s
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**进化**: 脚本已优化，cron 已更新
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## 日志清理脚本超时问题 (2026-03-27)
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**问题**: 日志清理cron任务连续2次超时（timeout）
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**根因**: 脚本扫描目录包含node_modules等大目录，导致1.5GB数据遍历超时
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**解决方案**:
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- 排除目录：node_modules、.cache、.npm、.pnpm-store、.git
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- 聚焦日志目录：workspace/sleep-learning、logs、token-monitor/logs
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- 不再扫描整个workspace和openclaw根目录
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**验证**: 修复后执行耗时0秒，正常完成
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@@ -0,0 +1,163 @@
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# Learnings
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Corrections, insights, and best practices for **skill-self-evolution-enhancer**.
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**Categories**: correction | insight | knowledge_gap | best_practice
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**Statuses**: pending | in_progress | resolved | wont_fix | promoted
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## [LRN-20260326-001] insight
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**Logged**: 2026-03-26T04:14:00Z
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**Priority**: high
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**Status**: resolved
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**Area**: 自进化冷启动
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### Summary
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learnings文件初始为空时，需要从heartbeat/cron日志/执行输出中主动提取进化素材
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### Details
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skill自进化需要真实错误数据驱动，但冷启动时.learnings/是空白模板
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解决方案：从系统日志(cron状态、资源使用)、执行输出(stderr/stdout)、用户反馈中主动提取
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### Suggested Action
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在HEARTBEAT.md中增加"每次心跳检查时提取一条可进化的错误/改进项"规则
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### Metadata
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- Source: heartbeat_automation_session
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- Tags: cold-start, self-evolution, data-driven
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- Recurrence-Count: 1
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---
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## [LRN-20260327-001] insight
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**Logged**: 2026-03-27T08:04:00Z
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**Priority**: medium
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**Status**: resolved
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**Area**: GitHub进化猎手-克隆超时
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### Summary
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GitHub进化猎手在心跳/cron环境中克隆大型仓库容易超时，需要优化分析策略
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### Details
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心跳/cron环境网络受限，克隆⭐49306的deer-flow和⭐20811的agentscope均超时失败
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解决方案：改用web_fetch读取README+API分析结构，不依赖git clone
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### Suggested Action
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修改github-intel.sh，增加"克隆前先web_fetch README预览"逻辑，对⭐>20000项目改用API+README分析
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### Metadata
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- Source: github-intel-cron-20260327
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- Tags: network-timeout, github-analysis, optimization
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- Recurrence-Count: 1
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---
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## [LRN-20260327-002] insight
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**Logged**: 2026-03-27T08:04:00Z
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**Priority**: high
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**Status**: in_progress
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**Area**: 重大突破性项目发现
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### Summary
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本期发现2个⭐>20000的突破性项目，需要深度研究
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### Details
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发现两个突破性项目：
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1. **bytedance/deer-flow** (⭐49306) - SuperAgent框架，集成sandbox/memories/tools/skill/subagents/message gateway
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2. **agentscope-ai/agentscope** (⭐20811) - "Build and run agents you can see, understand and trust"
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这两个项目代表了当前Agent架构的最新方向，值得深入研究代码结构
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### Suggested Action
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下次有充足时间时，手动克隆这两个项目分析代码结构
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### Metadata
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- Source: github-intel-cron-20260327
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- Tags: breakthrough-project, deer-flow, agentscope, agent-framework
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- Recurrence-Count: 1
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---
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## [LRN-20260327-004] best_practice
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**Logged**: 2026-03-27T12:04:00Z
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**Priority**: high
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**Status**: resolved
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**Area**: GitHub进化猎手-本期深度分析
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### Summary
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本期分析3个高价值项目：last30days-skill、superpowers、dexter
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### Details
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从 **mvanhorn/last30days-skill** (⭐11702) 学到：
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1. **Open Claw原生适配**: 明确说明"Designed for Open Claw and similar always-on AI environments"，提供open variant
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2. **Watchlist + briefings模式**: SQLite持久化研究数据，支持自然语言查询历史，支持定时cron触发
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3. **多信号并行 + 质量排序**: 10个平台并行搜索，双向文本相似度 + 参与度速度归一化
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4. **Comparative Mode**: "X vs Y"模式并行3次研究 + 并排对比
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从 **obra/superpowers** (⭐117412) 学到：
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1. **Subagent驱动开发**: dispatching-parallel-agents + 两阶段review (spec compliance → code quality)
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2. **Skills自动触发**: agent在执行任务前自动检查相关skills，无需手动调用
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3. **brainstorming skill**: Socratic设计澄清，在写代码前先确认真正需求
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4. **git-worktrees隔离**: 每个任务在独立branch的worktree执行，避免污染主分支
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5. **skills库生态**: 测试/调试/协作/元技能分类，writing-skills指导创建新skill
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从 **virattt/dexter** (⭐19354) 学到：
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1. **自验证循环**: 执行任务后检查结果，迭代直到confidence足够
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2. **Scratchpad调试日志**: 每个query生成JSONL文件，记录tool调用和LLM推理过程
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3. **Task Planning自动分解**: 复杂query自动拆解为结构化研究步骤
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4. **Loop Detection**: 内置循环检测和step limits防止无限执行
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5. **WhatsApp Gateway**: 通过WhatsApp与agent交互
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### Suggested Action
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1. 考虑为OpenClaw skills增加watchlist/briefings持久化模式
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2. 引入superpowers的"执行前先brainstorm"流程
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3. 学习dexter的scratchpad日志机制用于调试
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4. last30days-skill的"对比模式"可作为GitHub进化的分析模板
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### Metadata
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- Source: github-intel-cron-20260327-deep-analysis-2
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- Tags: last30days-skill, superpowers, dexter, agent-framework
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- Recurrence-Count: 1
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---
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## [LRN-20260327-003] best_practice
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**Logged**: 2026-03-27T08:29:00Z
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**Priority**: high
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**Status**: resolved
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**Area**: GitHub进化猎手-多源情报融合设计模式
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### Summary
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oh-my-claudecode的团队协作模式揭示了multi-agent编排的最佳实践
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### Details
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从oh-my-claudecode (⭐13148)学到：
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1. **Team Pipeline架构**: team-plan → team-prd → team-exec → team-verify → team-fix 循环
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2. **Deep Interview技能**: Socratic追问 + 数学模糊度门控 (ambiguity ≤ 20%才允许执行)
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3. **tmux CLI Workers**: 真实终端窗口作为worker，支持多agent并行
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4. **AGENTS.md规范**: 用guidance_schema_contract定义角色契约，operating_principles + delegation_rules
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从last30days-skill (⭐11242)学到：
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1. **多信号质量排序**: 8个平台并行搜索，双向文本相似度 + 参与度速度归一化 + 跨平台收敛检测
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2. **Polymarket预测市场集成**: 用真钱 bets 作为信号源，比Reddit更可靠
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3. **Per-project .env配置**: 项目级环境变量隔离
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4. **自动归档**: 每次运行保存到 ~/Documents/ 构建个人研究库
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从agentscope (⭐20827)学到：
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1. **"可观测的Agent"理念**: Build and run agents you can see, understand and trust
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2. **A2A协议支持**: Agent间标准通信协议
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3. **VNC-powered GUI沙箱**: 运行时可视化调试
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4. **OTel生产部署**: K8s + Docker内置支持
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### Suggested Action
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将team pipeline分阶段架构引入OpenClaw skill编排；考虑增加"模糊度门控"机制在执行危险操作前要求用户确认
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### Metadata
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- Source: github-intel-cron-20260327-deep-analysis
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- Tags: multi-agent, orchestration, team-pipeline, skill-design
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- Recurrence-Count: 1
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