據 AlphaMoat 統計,截至 2026-09,Self-Improving Agent (Anti-Loop Hardened) 累計下載 1,431 次、獲 0 個星標,在全部 5,078 個 AI 技能中排名第 4,813 位,在「AI 智慧體」分類(969 個)中排名第 924 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 25 | 1059 | - | - |
| SkillHub ↗ | 140 | 1431 | - | — |
各平台的計數口徑不同,統計時間不一致。
適用於命令意外失敗、使用者糾正或能力缺失等情況,並限制每條使用者訊息最多記錄一項。學習記錄可能影響後續行為並保留上下文;遵守單條限制,不連續觸發記錄流程,也不要寫入敏感資訊。 每次觸發最多呼叫工具 3 次,提升為規則應留到後續審閱。
資料釋出於 2026-10-29
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 1431 | — | - |
| 2026-08 | 1109 | +20.2% | - |
| 2026-07 | 923 | — | - |
| 2026-05 | 583 | — | - |
| 2026-03 | 276 | — | - |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 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
```
將開發過程中的經驗、錯誤與修正記錄為 Markdown 檔案,供日後重用並提升為工作區記憶。
用自然語言描述需求,在本機與遠端技能市場尋找技能並取得推薦。
給 AI agent 用的瀏覽器自動化命令列技能。
將使用者明確糾正與自我檢視整理成分層記憶,並依使用情況升級或封存。
在安裝第三方技能之前,按清單審查來源、許可權與危險模式的技能。
將代理記憶與跨技能狀態整理成具型別與約束的知識圖譜。
規劃 AI 代理主動跟進、工作記憶與回顧流程的工作區設定指南。
指導如何建立與更新有效 Claude 技能的寫作指南。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。