據 AlphaMoat 統計,截至 2026-09,Skill Vetter 累計下載 4,871 次、獲 1 個星標,在全部 5,078 個 AI 技能中排名第 1,924 位,在「AI 智慧體」分類(969 個)中排名第 362 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 130 | 4129 | 1 | - |
| SkillHub ↗ | 123 | 4871 | 1 | — |
各平台的計數口徑不同,統計時間不一致。
該技能提供安全審查清單,要求檢視全部檔案,檢查網路訪問、憑據、系統檔案修改、依賴安裝和許可權範圍,並形成風險分類報告。審查結論可能錯誤或誤導;採取行動前應複核實際檔案和掃描證據。執行示例命令前確認倉庫地址,不要把私有 token 或憑據貼上進審查流程。
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 | 4871 | — | 1 |
| 2026-08 | 4148 | +8.5% | 1 |
| 2026-07 | 3822 | +9.1% | 1 |
| 2026-06 | 3502 | +15.2% | 1 |
| 2026-05 | 3040 | — | 1 |
| 2026-03 | 2253 | — | 1 |
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-vetter version: 1.0.0 description: Security-first skill vetting for AI agents. Use before installing any skill from ClawdHub, GitHub, or other sources. Checks for red flags, permission scope, and suspicious patterns. --- # Skill Vetter 🔒 Security-first vetting protocol for AI agent skills. **Never install a skill without vetting it first.**
## When to Use
- Before installing any skill from ClawdHub
- Before running skills from GitHub repos
- When evaluating skills shared by other agents
- Anytime you're asked to install unknown code
## Vetting Protocol
### Step 1: Source Check
```
Questions to answer:
- [ ] Where did this skill come from?
- [ ] Is the author known/reputable?
- [ ] How many downloads/stars does it have?
- [ ] When was it last updated?
- [ ] Are there reviews from other agents?
```
### Step 2: Code Review (MANDATORY)
Read ALL files in the skill. Check for these **RED FLAGS**:
```
🚨 REJECT IMMEDIATELY IF YOU SEE:
─────────────────────────────────────────
• curl/wget to unknown URLs
• Sends data to external servers
• Requests credentials/tokens/API keys
• Reads ~/.ssh, ~/.aws, ~/.config without clear reason
• Accesses MEMORY.md, USER.md, SOUL.md, IDENTITY.md
• Uses base64 decode on anything
• Uses eval() or exec() with external input
• Modifies system files outside workspace
• Installs packages without listing them
• Network calls to IPs instead of domains
• Obfuscated code (compressed, encoded, minified)
• Requests elevated/sudo permissions
• Accesses browser cookies/sessions
• Touches credential files
─────────────────────────────────────────
```
### Step 3: Permission Scope
```
Evaluate:
- [ ] What files does it need to read?
- [ ] What files does it need to write?
- [ ] What commands does it run?
- [ ] Does it need network access? To where?
- [ ] Is the scope minimal for its stated purpose?
```
### Step 4: Risk Classification
| Risk Level | Examples | Action |
|------------|----------|--------|
| 🟢 LOW | Notes, weather, formatting | Basic review, install OK |
| 🟡 MEDIUM | File ops, browser, APIs | Full code review required |
| 🔴 HIGH | Credentials, trading, system | Human approval required |
| ⛔ EXTREME | Security configs, root access | Do NOT install |
## Output Format
After vetting, produce this report:
```
SKILL VETTING REPORT
═══════════════════════════════════════
Skill: [name]
Source: [ClawdHub / GitHub / other]
Author: [username]
Version: [version]
───────────────────────────────────────
METRICS:
• Downloads/Stars: [count]
• Last Updated: [date]
• Files Reviewed: [count]
───────────────────────────────────────
RED FLAGS: [None / List them]
PERMISSIONS NEEDED:
• Files: [list or "None"]
• Network: [list or "None"]
• Commands: [list or "None"]
───────────────────────────────────────
RISK LEVEL: [🟢 LOW / 🟡 MEDIUM / 🔴 HIGH / ⛔ EXTREME]
VERDICT: [✅ SAFE TO INSTALL / ⚠️ INSTALL WITH CAUTION / ❌ DO NOT INSTALL]
NOTES: [Any observations]
═══════════════════════════════════════
```
## Quick Vet Commands
For GitHub-hosted skills:
```bash
# Check repo stats
curl -s "https://api.github.com/repos/OWNER/REPO" | jq '{stars: .stargazers_count, forks: .forks_count, updated: .updated_at}'
# List skill files
curl -s "https://api.github.com/repos/OWNER/REPO/contents/skills/SKILL_NAME" | jq '.[].name'
# Fetch and review SKILL.md
curl -s "https://raw.githubusercontent.com/OWNER/REPO/main/skills/SKILL_NAME/SKILL.md"
```
## Trust Hierarchy
1. **Official OpenClaw skills** → Lower scrutiny (still review)
2. **High-star repos (1000+)** → Moderate scrutiny
3. **Known authors** → Moderate scrutiny
4. **New/unknown sources** → Maximum scrutiny
5. **Skills requesting credentials** → Human approval always
## Remember
- No skill is worth compromising security
- When in doubt, don't install
- Ask your human for high-risk decisions
- Document what you vet for future reference
---
*Paranoia is a feature.* 🔒🦀
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。