微云字节

self-improving-agent

AI Agentv2.0.1
By 微云字节Updated 2026-05-112 versions · latest released 2026-03-08self-improving-agent-next@clawhub_weiyunbyte/self-improving-agent-next
Context ManagementMemory#Self Improving

According to AlphaMoat, as of 2026-09, self-improving-agent has 3,124 downloads and 2 stars — ranked #3,646 of 5,078 AI skills overall, and #736 of 969 in AI Agent.

Installs
145
Downloads
3.1K
Stars
2
Overall Rank
#3,646
Top 72% overall · Top 76% in AI Agent
PlatformInstallsDownloadsStarsComments
ClawHub ↗662.6K--
SkillHub ↗1453.1K2—

Platforms count differently and update at different times.

What this skill does

Stores errors, lessons and feature requests separately under .learnings/, with context, suggested actions, related entries and status. Review notes around tasks. Repeated, broadly applicable or easily repeated mistakes can become long-term project rules with their origin recorded. Improvement relies on recording and later practice.

Profile published 2026-10-26

What you can do with it

  • Record recurring failures and derive workflow rules

When to use it

  • When users correct behavior, tools fail or better methods emerge

Example prompts

Generated from the skill’s documentation as examples; not results of actual runs.

Record this correction, link related entries and suggest the next action

Monthly Trend

Downloads3.1K
5511.9K3.3K2026-03 · Downloads 7422026-05 · Downloads 1.2K2026-06 · Downloads 1.6K2026-07 · Downloads 2.3K2026-08 · Downloads 2.6K2026-09 · Downloads 3.1K26-0326-09
Stars2
0122026-03 · Stars -2026-05 · Stars 22026-06 · Stars 22026-07 · Stars 22026-08 · Stars 22026-09 · Stars 226-0326-09

The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.

MonthDownloadsMoMStars
2026-093.1K—2
2026-082.6K+10.5%2
2026-072.3K+42.2%2
2026-061.6K+32.1%2
2026-051.2K—2
2026-03742—-

SKILL.md (original)

The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.

5.3 KB · ClawHub v2.0.1
---
name: self-improving-agent
description: "记录错误、纠正、能力缺口与最佳实践,形成可复用的持续改进闭环。适用于:命令失败、用户纠正、外部 API/工具异常、发现更优做法、提出新能力需求,以及任务前复盘历史经验。"
---

# Self-Improving Agent(自我改进)

把“踩坑”变成“资产”。
每次失败、纠正或新发现,都写入结构化记录,后续可检索、可复盘、可沉淀到长期规则。
Show all (240 lines)
---

## 1. 什么时候必须记录

出现以下任一情况时,立即记录:

1. **命令/操作失败**(非 0 退出、超时、异常输出)
2. **用户纠正你**(“不对”“应该是…”)
3. **用户提出你当前不具备的能力**
4. **外部服务失败**(API 报错、限流、鉴权失败)
5. **你意识到知识已过时或理解错误**
6. **你发现了可复用的更优流程**

---

## 2. 记录到哪里

在工作区使用 `.learnings/`:

- `.learnings/LEARNINGS.md`:纠正、认知缺口、最佳实践
- `.learnings/ERRORS.md`:失败与异常
- `.learnings/FEATURE_REQUESTS.md`:能力请求

若目录不存在,先创建:

```bash
mkdir -p .learnings
```

---

## 3. 快速分流规则

- **失败/报错** → `ERRORS.md`
- **被纠正/学到新规则** → `LEARNINGS.md`
- **想要但暂不支持的能力** → `FEATURE_REQUESTS.md`

---

## 4. ID 规范

格式:`TYPE-YYYYMMDD-XXX`

- TYPE: `LRN` / `ERR` / `FEAT`
- 日期:当天日期
- XXX:三位序号(如 `001`)

示例:
- `LRN-20260308-001`
- `ERR-20260308-002`
- `FEAT-20260308-001`

---

## 5. 模板(请严格使用)

### 5.1 Learning 模板(LEARNINGS.md)

```markdown
## [LRN-YYYYMMDD-XXX] correction | knowledge_gap | best_practice

**Logged**: ISO-8601 时间
**Priority**: low | medium | high | critical
**Status**: pending
**Area**: frontend | backend | infra | tests | docs | config

### Summary
一句话总结

### Details
发生了什么、哪里错了、正确做法是什么

### Suggested Action
下一次应执行的具体动作

### Metadata
- Source: conversation | error | user_feedback | simplify-and-harden
- Related Files: path/to/file
- Tags: tag1, tag2
- See Also: LRN-...(可选)
- Pattern-Key: ...(可选)
- Recurrence-Count: 1(可选)
- First-Seen: YYYY-MM-DD(可选)
- Last-Seen: YYYY-MM-DD(可选)

---
```

### 5.2 Error 模板(ERRORS.md)

```markdown
## [ERR-YYYYMMDD-XXX] command_or_integration

**Logged**: ISO-8601 时间
**Priority**: medium | high | critical
**Status**: pending
**Area**: frontend | backend | infra | tests | docs | config

### Summary
一句话说明失败点

### Error
```
完整报错文本
```

### Context
- 执行了什么命令/操作
- 使用了哪些参数
- 关键环境信息

### Suggested Fix
可执行的修复建议

### Metadata
- Reproducible: yes | no | unknown
- Related Files: path/to/file
- See Also: ERR-...(可选)

---
```

### 5.3 Feature Request 模板(FEATURE_REQUESTS.md)

```markdown
## [FEAT-YYYYMMDD-XXX] capability_name

**Logged**: ISO-8601 时间
**Priority**: low | medium | high
**Status**: pending
**Area**: frontend | backend | infra | tests | docs | config

### Requested Capability
用户希望实现什么

### User Context
用户为什么需要它

### Complexity Estimate
simple | medium | complex

### Suggested Implementation
实现方向(脚本、工具、流程)

### Metadata
- Frequency: first_time | recurring
- Related Features: ...(可选)

---
```

---

## 6. 状态流转

允许状态:

- `pending`:待处理
- `in_progress`:处理中
- `resolved`:已解决
- `promoted`:已提升到长期规则文件
- `wont_fix`:不处理(需写原因)

当问题已解决时,补充:

```markdown
### Resolution
- **Resolved**: ISO-8601 时间
- **Commit/PR**: commit hash 或 PR 链接
- **Notes**: 做了什么
```

---

## 7. 何时“晋升”到长期记忆文件

满足以下任一条件,建议晋升:

- 同类问题重复出现
- 对多人/多任务都适用
- 不写下来就会反复踩坑

晋升目标:

- 工作流规则 → `AGENTS.md`
- 行为/表达规则 → `SOUL.md`
- 工具使用细节 → `TOOLS.md`
- 长期偏好/事实 → `MEMORY.md`

晋升后把原条目状态改为 `promoted`,并注明目标文件。

---

## 8. 复盘频率

建议在以下时机快速复盘 `.learnings/`:

- 开始新任务前
- 完成复杂任务后
- 每周至少一次

可用命令:

```bash
# 统计 pending
grep -h "Status\*\*: pending" .learnings/*.md | wc -l

# 查看高优先级
grep -B5 "Priority\*\*: high" .learnings/*.md | grep "^## \["
```

---

## 9. 执行原则(简版)

1. **立即记录**:别等会儿,信息会丢。
2. **写可执行建议**:不是“再看看”,而是“下次先做 X”。
3. **优先去重与关联**:能关联就加 `See Also`。
4. **重复三次就系统化**:提升到 `AGENTS.md/SOUL.md/TOOLS.md`。
5. **短而准**:结论可复用,描述可追溯。

---

## 10. OpenClaw 场景建议

- 在主会话中把高价值学习同步到 `MEMORY.md`。
- 在需要跨会话协作时,使用 `sessions_send` 分享关键学习。
- 对高频重复问题,优先将规则写入工作区文档,减少未来上下文成本。

> 目标不是“记日志”,而是持续降低错误率、提高可复用性。

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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.