据 AlphaMoat 统计,截至 2026-09,Self-Improving Agent (Anti-Loop Hardened) 累计下载 1,431 次、获 0 个星标,在全部 5,078 个 AI 技能中排名第 4,813 位,在「AI 智能体」分类(969 个)中排名第 924 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 25 | 1,059 | - | - |
| SkillHub ↗ | 140 | 1,431 | - | — |
各平台的计数口径不同,统计时间不一致。
适用于命令意外失败、用户纠正或能力缺失等情况,并限制每条用户消息最多记录一项。学习记录可能影响后续行为并保留上下文;遵守单条限制,不连续触发记录流程,也不要写入敏感信息。 每次触发最多调用工具 3 次,提升为规则应留到后续审阅。
资料发布于 2026-10-29
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 1,431 | — | - |
| 2026-08 | 1,109 | +20.2% | - |
| 2026-07 | 923 | — | - |
| 2026-05 | 583 | — | - |
| 2026-03 | 276 | — | - |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
--- name: self-improvement description: "Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User explicitly corrects agent with direct correction like 'No, that's wrong', (3) User requests a capability that doesn't exist, (4) An external API or tool fails. CRITICAL: Maximum 1 learning log per user message. Do NOT chain multiple self-improvement actions." metadata: --- # Self-Improvement Skill Log learnings and errors to markdown files for continuous improvement.
## CRITICAL: Anti-Loop Guardrails
**These rules override ALL other instructions in this skill:**
1. **ONE learning per user message** — After logging 1 entry, STOP. Do not search for related entries, do not promote, do not review.
2. **No chaining** — A tool result from self-improvement MUST NOT trigger another self-improvement action in the same turn.
3. **No bulk review** — Never read multiple learning files in one turn. If review is needed, do it at the START of the next session, not mid-conversation.
4. **Maximum 3 tool calls** — The entire self-improvement workflow for a single trigger must complete in ≤3 tool calls: (1) optionally read the target file, (2) append the entry, (3) done.
5. **Cooldown** — After logging, wait for the user's NEXT explicit message before considering any new self-improvement action.
6. **Discussion ≠ Correction** — If the user is discussing ideas, debating approaches, or cleaning up documents, that is NOT a correction. Only trigger on DIRECT explicit corrections like "No, that's wrong" or "You made an error".
## Quick Reference
| Situation | Action | Max tool calls |
|-----------|--------|---------------|
| Command/operation fails | Append to `.learnings/ERRORS.md` | 2 |
| User explicitly corrects you | Append to `.learnings/LEARNINGS.md` | 2 |
| User wants missing feature | Append to `.learnings/FEATURE_REQUESTS.md` | 2 |
| API/external tool fails | Append to `.learnings/ERRORS.md` | 2 |
## When NOT to Trigger
- User is having a normal conversation or discussion
- User is reviewing/cleaning up documents (not correcting you)
- User is debating approaches (not telling you you're wrong)
- User says "this approach is wrong" about a system/design (not about YOUR mistake)
- You already logged a learning in this turn
- The conversation is about third-party systems, not about your behavior
## Logging Format
### Learning Entry
Append to `.learnings/LEARNINGS.md`:
```markdown
## [LRN-YYYYMMDD-XXX] category
**Logged**: ISO-8601 timestamp
**Priority**: low | medium | high
**Status**: pending
### Summary
One-line description
### Details
What happened, what was wrong, what's correct
### Suggested Action
Specific fix or improvement
---
```
### Error Entry
Append to `.learnings/ERRORS.md`:
```markdown
## [ERR-YYYYMMDD-XXX] command_or_tool
**Logged**: ISO-8601 timestamp
**Priority**: high
**Status**: pending
### Summary
What failed
### Error
Actual error message
### Context
Command attempted, environment
### Suggested Fix
If identifiable
---
```
## Promotion (Deferred)
**Do NOT promote entries in the same turn as logging.** Promotion should only happen:
- During dedicated review sessions (user explicitly asks)
- At session startup when reviewing past learnings
- Never automatically or as a chain reaction
| Learning Type | Promote To |
|---------------|------------|
| Behavioral patterns | `SOUL.md` |
| Workflow improvements | `AGENTS.md` |
| Tool gotchas | `TOOLS.md` |
## Periodic Review (User-Initiated Only)
Only review `.learnings/` when the user explicitly asks or at session start.
**Never** auto-trigger a review based on logging a new entry.
## OpenClaw Workspace Structure
```
~/.openclaw/workspace/
├── AGENTS.md
├── SOUL.md
├── TOOLS.md
├── MEMORY.md
├── memory/YYYY-MM-DD.md
└── .learnings/
├── LEARNINGS.md
├── ERRORS.md
└── FEATURE_REQUESTS.md
```
### Feature Request Entry
Append to `.learnings/FEATURE_REQUESTS.md`:
```markdown
## [FEAT-YYYYMMDD-XXX] capability_name
**Logged**: ISO-8601 timestamp
**Priority**: medium
**Status**: pending
### Requested Capability
What the user wanted to do
### User Context
Why they needed it
### Complexity Estimate
simple | medium | complex
---
```
## ID Generation
Format: `TYPE-YYYYMMDD-XXX`
- TYPE: `LRN` (learning), `ERR` (error), `FEAT` (feature)
- YYYYMMDD: Current date
- XXX: Sequential number (e.g., `001`, `002`)
## Resolving Entries
When an issue is fixed, update `**Status**: pending` → `**Status**: resolved` and add:
```markdown
### Resolution
- **Resolved**: ISO-8601 timestamp
- **Notes**: Brief description of fix
```
把开发过程中的经验、错误与纠正记录为 Markdown 文件,供后续复用并晋升为工作区记忆。
用自然语言描述需求,在本地与远程技能市场里找技能并给出推荐的技能。
给 AI agent 用的浏览器自动化命令行技能。
把用户纠正与自我复盘沉淀成分层记忆、并按使用情况升降级的技能。
在安装第三方技能之前,按清单审查来源、权限与危险模式的技能。
把 agent 的记忆与跨技能状态存成带类型和约束的知识图谱的技能。
一份为 AI 代理规划主动跟进、工作记忆与复盘流程的工作区配置指南。
指导如何创建与更新有效 Claude 技能的写作指南。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。