據 AlphaMoat 統計,截至 2026-10,Skill From Memory 累計下載 5,487 次、獲 2 個星標,按累計下載量在本次參與排名的 5,109 個 AI 技能中排名第 2,536 位,在「AI 智慧體」分類(987 個)中排名第 491 位。
列表預設按累計下載量排序,也可按星標排序;詳情頁排名按累計下載量計算。
| 平台 | 累計下載 | 星標 | 評論 |
|---|---|---|---|
| ClawHub ↗ | 3940 | 2 | - |
| SkillHub ↗ | 5487 | 2 | — |
各平台的計數口徑不同,統計時間不一致。
Convert memory, conversation history, or completed tasks into publishable OpenClaw skills. Use when (1) A task or workflow should be reusable, (2) Extracting...
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 |
|---|---|---|---|
| 2026-10 | 5487 | — | 2 |
| 2026-09 | 4080 | — | 2 |
| 2026-08 | 3743 | +2.1% | 2 |
| 2026-07 | 3667 | +5.7% | 2 |
| 2026-06 | 3469 | +4.8% | 2 |
| 2026-05 | 3309 | — | 2 |
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: skill-from-memory description: Convert memory, conversation history, or completed tasks into publishable OpenClaw skills. Use when (1) A task or workflow should be reusable, (2) Extracting lessons from memory to create tools, (3) Packaging solved problems as skills for future use, (4) Publishing skills to GitHub and ClawHub registry. --- # Skill from Memory Transform your work into reusable skills. Extract workflows, solutions, and patterns from conversation history or memory files, package them as skills, and publish to GitHub and ClawHub. ## Overview
This skill automates the complete workflow:
1. **Extract** - Parse conversation history or memory for reusable patterns
2. **Design** - Structure as a proper skill with SKILL.md and resources
3. **Create** - Generate skill files and scripts
4. **Publish** - Push to GitHub and publish to ClawHub
## Quick Start
### Create Skill from Recent Conversation
```bash
# Analyze last conversation and create skill draft
./scripts/extract-from-history.sh /path/to/session.jsonl ./my-new-skill
# Or specify a time range
./scripts/extract-from-history.sh /path/to/session.jsonl ./my-new-skill --since "2026-02-03" --pattern "backup"
```
### Create Skill from Memory File
```bash
# Extract from memory markdown
./scripts/extract-from-memory.sh /path/to/memory/2026-02-04.md ./my-new-skill
```
### Full Auto-Create and Publish
```bash
# One command: extract, create, and publish
./scripts/create-and-publish.sh \
--source /path/to/session.jsonl \
--skill-name "my-automation" \
--github-repo "user/my-skills" \
--clawhub-slug "my-automation"
```
## Workflow Steps
### Step 1: Extract Requirements
Identify from conversation/memory:
- **Task Pattern**: What workflow was solved?
- **Inputs/Outputs**: What goes in, what comes out?
- **Scripts/Tools**: What code was written?
- **Key Decisions**: What choices were made?
### Step 2: Design Skill Structure
Decide resource types:
- `scripts/` - For reusable code
- `references/` - For documentation
- `assets/` - For templates/files
### Step 3: Create Skill Files
Generate:
- `SKILL.md` with frontmatter and instructions
- Scripts in `scripts/`
- Any reference files
### Step 4: Publish
Push to GitHub and publish to ClawHub:
```bash
./scripts/publish.sh ./my-skill \
--github "user/repo" \
--clawhub-slug "my-skill" \
--version "1.0.0"
```
## Scripts Reference
### extract-from-history.sh
Parse conversation JSONL for skill content.
```bash
./scripts/extract-from-history.sh <session.jsonl> <output-dir> [options]
Options:
--since DATE Only extract from DATE onwards
--pattern REGEX Filter messages matching pattern
--tools-only Only extract tool usage patterns
```
### extract-from-memory.sh
Parse memory markdown files.
```bash
./scripts/extract-from-memory.sh <memory.md> <output-dir>
```
### create-skill.sh
Generate skill structure from extracted content.
```bash
./scripts/create-skill.sh <extracted-content-dir> <skill-name>
Options:
--description "..." Skill description
--type workflow Skill type (workflow|tool|reference)
```
### publish.sh
Complete publish workflow.
```bash
./scripts/publish.sh <skill-path> [options]
Options:
--github REPO GitHub repo (owner/repo)
--clawhub-slug ClawHub slug
--version VER Version tag
--skip-github Skip GitHub push
--skip-clawhub Skip ClawHub publish
```
## Example: Converting a Task to Skill
### Original Task (from conversation)
User: "帮我设置每天自动备份OpenClaw配置"
→ Agent creates backup scripts + cron setup
### Skill Creation Process
1. **Extract**:
```bash
./scripts/extract-from-history.sh \
~/.openclaw/agents/main/sessions/latest.jsonl \
./extracted-backup
```
2. **Design**:
- Type: Workflow skill
- Scripts: backup.sh, setup-cron.sh, cleanup.sh
- No assets needed
3. **Create**:
```bash
./scripts/create-skill.sh ./extracted-backup cron-backup \
--description "Automated backup scheduling with cron" \
--type workflow
```
4. **Publish**:
```bash
./scripts/publish.sh ./cron-backup \
--github "zfanmy/openclaw-skills" \
--clawhub-slug "cron-backup" \
--version "1.0.0"
```
## Best Practices
### What Makes a Good Skill
✅ **Do**:
- Single, well-defined purpose
- Reusable across contexts
- Includes working scripts
- Clear usage examples
- Progressive disclosure design
❌ **Don't**:
- Too broad or vague
- Hardcoded personal paths
- Missing error handling
- Undocumented assumptions
### Extracting from Memory
Look for these patterns:
- "帮我写一个脚本..."
- "设置定时任务..."
- "以后每次都要..."
- "这个流程可以复用..."
### GitHub Integration
Required setup:
```bash
# Configure git
git config --global user.name "Your Name"
git config --global user.email "[email protected]"
# Setup SSH key for GitHub
ssh-keygen -t ed25519 -C "[email protected]"
# Add ~/.ssh/id_ed25519.pub to GitHub Settings → SSH Keys
# Login to ClawHub
clawhub login
```
### Versioning
Follow semantic versioning:
- `1.0.0` - Initial release
- `1.0.1` - Bug fix
- `1.1.0` - New feature
- `2.0.0` - Breaking change
## Troubleshooting
### Extraction finds nothing
- Check session file path
- Verify date range with `--since`
- Try broader pattern matching
### GitHub push fails
- Verify SSH key is added to GitHub
- Check repo exists and you have access
- Ensure git config user.name/email set
### ClawHub publish fails
- Run `clawhub login` first
- Check skill validation passes
- Verify slug is unique
### Skill doesn't work when used
- Test scripts manually first
- Check for hardcoded paths
- Verify all dependencies listed
- Run with `--examples` flag when creating
## Related Skills
- **skill-creator** - Low-level skill creation utilities
- **cron-backup** - Example output skill (backup automation)
- **clawhub** - ClawHub CLI operations
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。
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。
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。
資料月份:2026-10 · 下載/星標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。