LeoYeAI Skill Advisor
Pre-install assessment tool for OpenClaw skills. Generate comprehensive evaluation reports to help users decide whether to install a skill.
Features
- 🔒 Security Status: Check ClawHub official scan results
- 📊 Popularity Metrics: Downloads, stars, install count
- 🔄 Maintenance Status: Last update time, activity level
- 📦 Dependency Analysis: Required tools, libraries, complexity
- 💰 API Cost Assessment: Free/paid API requirements
- 🎯 Installation Recommendation: Clear go/no-go guidance
Trigger Conditions
- "Check this skill before installing" / "安装前检查这个skill"
- "Is {skill-name} safe?" / "{skill-name}安全吗"
- "Evaluate skill {skill-name}" / "评估skill {skill-name}"
- "What does {skill-name} need?" / "{skill-name}需要什么依赖"
- "Should I install {skill-name}?" / "要不要安装{skill-name}"
- "skill-advisor {skill-name}"
- "帮我看看这个skill怎么样"
Language Support
This skill supports multiple languages. Output language automatically matches the user's conversation language with OpenClaw.
Supported Languages:
- 中文 (Chinese)
- English
Detection:
- If user writes in Chinese → Output Chinese report
- If user writes in English → Output English report
- Default: Match the user's input language
Step 1: Get Skill Information
When user provides a skill name, fetch its metadata:
SKILL_NAME="user-provided-skill-name"
# Get skill metadata from ClawHub
echo "📡 Fetching skill information..."
clawhub inspect "$SKILL_NAME" 2>/dev/null
# Alternative: Use ClawHub API directly
curl -s "https://clawhub.ai/api/v1/skills/$SKILL_NAME" | python3 -m json.tool 2>/dev/null
Step 2: Fetch SKILL.md Content
Get the actual SKILL.md to analyze dependencies and functionality:
# Fetch SKILL.md content
SKILL_CONTENT=$(curl -s "https://clawhub.ai/api/v1/skills/$SKILL_NAME" | python3 -c "
import sys, json
try:
data = json.load(sys.stdin)
if 'skill' in data and 'content' in data['skill']:
print(data['skill']['content'])
elif 'content' in data:
print(data['content'])
else:
print('CONTENT_NOT_FOUND')
except:
print('PARSE_ERROR')
" 2>/dev/null)
echo "$SKILL_CONTENT"
Step 3: Analyze and Generate Report
Parse the skill data and generate the assessment report in the user's language:
python3 << 'PYEOF'
import json
import re
import sys
from datetime import datetime
# Detect user language from input (passed as argument)
USER_LANG = "en" # Default to English, will be overridden by agent
# Simulated skill data (replace with actual API response)
skill_data = {
"name": "SKILL_NAME_PLACEHOLDER",
"description": "DESCRIPTION_PLACEHOLDER",
"version": "1.0.0",
"owner": "AUTHOR_PLACEHOLDER",
"created_at": "2026-01-01T00:00:00Z",
"updated_at": "2026-03-20T00:00:00Z",
"downloads": 0,
"stars": 0,
"license": "MIT-0",
"security_status": "unknown"
}
skill_content = """
SKILL_MD_CONTENT_PLACEHOLDER
"""
# Labels for different languages
LABELS = {
"zh": {
"conclusion_header": "🎯 结论",
"recommend_install": "✅ 推荐安装",
"caution_install": "⚠️ 可以安装，请注意事项",
"not_recommend": "❌ 不建议安装",
"score": "综合评分",
"security_pass": "通过",
"security_review": "需审查",
"deps_light": "轻量",
"deps_heavy": "较重",
"report_title": "📋 Skill 评估报告",
"metrics": "综合指标",
"official_security": "🔒 官方安全",
"benign": "✅ Benign（ClawHub扫描通过）",
"suspicious": "⚠️ Suspicious（需要审查）",
"security_unknown": "❓ 未知（未扫描）",
"popularity": "📈 流行度",
"downloads": "downloads",
"stars": "stars",
"maintenance": "🔄 维护状态",
"active_maintain": "天前更新（活跃维护）",
"normal_maintain": "天前更新（正常维护）",
"less_maintain": "天前更新（维护较少）",
"stop_maintain": "天前更新（可能停止维护）",
"maintenance_unknown": "❓ 未知",
"dep_burden": "📦 依赖负担",
"no_dep": "无需额外依赖",
"light_dep": "轻量",
"heavy_dep": "较重",
"deps_count": "个依赖",
"api_cost": "💰 API成本",
"no_api": "无需外部API",
"api_required": "需要",
"description": "📝 功能说明",
"env_req": "⚙️ 环境要求",
"cli_tools": "命令行工具",
"python_pkg": "Python包",
"node_pkg": "Node包",
"api_key": "API密钥",
"no_special_req": "无特殊要求",
"usage_note": "⚠️ 使用注意",
"data_upload": "📤 文档/数据会上传到",
"external_service": "📤 会访问外部服务",
"sensitive_data": "🔐 敏感数据请谨慎处理",
"install_advice": "💡 安装建议",
"safe_install": "可安全安装。",
"caution_install_text": "可以安装，但请注意上述事项。",
"not_install_text": "不建议安装，请寻找替代方案。",
"need_config": "需要配置API Key",
"meta_info": "ℹ️ 元信息",
"author": "作者",
"version": "版本",
"license": "许可证",
"score_time": "评分时间",
},
"en": {
"conclusion_header": "🎯 Conclusion",
"recommend_install": "✅ Recommended",
"caution_install": "⚠️ Install with Caution",
"not_recommend": "❌ Not Recommended",
"score": "Overall Score",
"security_pass": "Passed",
"security_review": "Review Needed",
"deps_light": "Light",
"deps_heavy": "Heavy",
"report_title": "📋 Skill Assessment Report",
"metrics": "Metrics",
"official_security": "🔒 Official Security",
"benign": "✅ Benign (ClawHub scan passed)",
"suspicious": "⚠️ Suspicious (needs review)",
"security_unknown": "❓ Unknown (not scanned)",
"popularity": "📈 Popularity",
"downloads": "downloads",
"stars": "stars",
"maintenance": "🔄 Maintenance",
"active_maintain": "days ago (actively maintained)",
"normal_maintain": "days ago (normal maintenance)",
"less_maintain": "days ago (less maintained)",
"stop_maintain": "days ago (possibly abandoned)",
"maintenance_unknown": "❓ Unknown",
"dep_burden": "📦 Dependencies",
"no_dep": "No dependencies required",
"light_dep": "Light",
"heavy_dep": "Heavy",
"deps_count": "dependencies",
"api_cost": "💰 API Cost",
"no_api": "No external API required",
"api_required": "Requires",
"description": "📝 Description",
"env_req": "⚙️ Requirements",
"cli_tools": "CLI Tools",
"python_pkg": "Python Packages",
"node_pkg": "Node Packages",
"api_key": "API Keys",
"no_special_req": "No special requirements",
"usage_note": "⚠️ Usage Notes",
"data_upload": "📤 Data uploads to",
"external_service": "📤 Accesses external services",
"sensitive_data": "🔐 Handle sensitive data with care",
"install_advice": "💡 Installation Advice",
"safe_install": "Safe to install.",
"caution_install_text": "Can be installed, but please note the above.",
"not_install_text": "Not recommended. Consider alternatives.",
"need_config": "API Key configuration required",
"meta_info": "ℹ️ Metadata",
"author": "Author",
"version": "Version",
"license": "License",
"score_time": "Scored at",
}
}
def get_label(key, lang="en"):
"""Get localized label"""
return LABELS.get(lang, LABELS["en"]).get(key, key)
def calculate_security_score(content, security_status):
score = 100
if security_status == "benign":
return 100
elif security_status == "suspicious":
return 50
dangerous_patterns = [
(r'curl\s+-fsSL.*\|.*bash', 30),
(r'sudo\s+(apt|yum|dnf)\s+install', 15),
(r'eval\s*\(', 20),
(r'exec\s*\(', 15),
]
for pattern, penalty in dangerous_patterns:
if re.search(pattern, content, re.IGNORECASE):
score -= penalty
return max(0, score)
def calculate_popularity_score(downloads, stars):
score = 0
if downloads >= 10000: score += 60
elif downloads >= 1000: score += 50
elif downloads >= 100: score += 40
elif downloads >= 10: score += 30
else: score += 20
if stars >= 50: score += 40
elif stars >= 10: score += 30
elif stars >= 1: score += 20
else: score += 10
return score
def calculate_maintenance_score(updated_at):
try:
last_update = datetime.fromisoformat(updated_at.replace('Z', '+00:00'))
now = datetime.now(last_update.tzinfo)
days = (now - last_update).days
if days <= 7: return 100
elif days <= 30: return 80
elif days <= 90: return 60
else: return 40
except:
return 50
def extract_dependencies(content):
deps = {"bins": [], "env_vars": [], "pip_packages": [], "npm_packages": [], "complexity": "unknown"}
bins_match = re.search(r'"bins"\s*:\s*\[(.*?)\]', content)
if bins_match:
deps["bins"] = [b.strip().strip('"') for b in bins_match.group(1).split(',') if b.strip()]
env_match = re.search(r'"env"\s*:\s*\[(.*?)\]', content)
if env_match:
deps["env_vars"] = [e.strip().strip('"') for e in env_match.group(1).split(',') if e.strip()]
pip_patterns = re.findall(r'pip\s+install\s+([\w-]+)', content)
deps["pip_packages"] = list(set(pip_patterns))
npm_patterns = re.findall(r'npm\s+(?:install|i)\s+(?:-g\s+)?([\w-]+)', content)
deps["npm_packages"] = list(set(npm_patterns))
lines = len(content.split('\n'))
if lines < 100: deps["complexity"] = "simple"
elif lines < 250: deps["complexity"] = "medium"
else: deps["complexity"] = "complex"
return deps
def calculate_dependency_score(deps):
score = 100
bin_count = len(deps["bins"])
if bin_count <= 2: score -= 10
elif bin_count <= 4: score -= 20
elif bin_count > 4: score -= 30
pkg_count = len(deps["pip_packages"]) + len(deps["npm_packages"])
if pkg_count > 5: score -= 20
elif pkg_count > 0: score -= 10
return max(0, score)
def calculate_api_cost_score(deps, content):
if not deps["env_vars"]:
return 100
free_indicators = ["免费", "free", "免费额度", "new user", "free tier"]
has_free = any(indicator in content.lower() for indicator in free_indicators)
return 80 if has_free else 60
def generate_report(skill_data, skill_content, lang="en"):
L = lambda k: get_label(k, lang)
name = skill_data.get("name", "unknown")
description = skill_data.get("description", "No description")
version = skill_data.get("version", "?.?.?")
owner = skill_data.get("owner", "unknown")
downloads = skill_data.get("downloads", 0)
stars = skill_data.get("stars", 0)
updated_at = skill_data.get("updated_at", "")
security_status = skill_data.get("security_status", "unknown")
license_type = skill_data.get("license", "unknown")
security_score = calculate_security_score(skill_content, security_status)
popularity_score = calculate_popularity_score(downloads, stars)
maintenance_score = calculate_maintenance_score(updated_at)
deps = extract_dependencies(skill_content)
dependency_score = calculate_dependency_score(deps)
api_cost_score = calculate_api_cost_score(deps, skill_content)
total_score = (
security_score * 0.30 +
popularity_score * 0.25 +
maintenance_score * 0.20 +
dependency_score * 0.15 +
api_cost_score * 0.10
)
if total_score >= 80:
grade = "A"
recommendation = L("recommend_install")
rec_icon = "✅"
elif total_score >= 60:
grade = "B"
recommendation = L("caution_install")
rec_icon = "⚠️"
else:
grade = "C"
recommendation = L("not_recommend")
rec_icon = "❌"
if security_status == "benign":
security_text = L("benign")
elif security_status == "suspicious":
security_text = L("suspicious")
else:
security_text = L("security_unknown")
try:
last_update = datetime.fromisoformat(updated_at.replace('Z', '+00:00'))
now = datetime.now(last_update.tzinfo)
days = (now - last_update).days
if days <= 7:
maintenance_text = f"✅ {days}{L('active_maintain')}"
elif days <= 30:
maintenance_text = f"✅ {days}{L('normal_maintain')}"
elif days <= 90:
maintenance_text = f"⚠️ {days}{L('less_maintain')}"
else:
maintenance_text = f"⚠️ {days}{L('stop_maintain')}"
except:
maintenance_text = L("maintenance_unknown")
all_deps = deps["bins"] + deps["pip_packages"] + deps["npm_packages"]
if not all_deps:
deps_text = L("no_dep")
elif len(all_deps) <= 3:
deps_text = f"{L('light_dep')}（{', '.join(all_deps)}）"
else:
deps_text = f"{L('heavy_dep')}（{len(all_deps)}{L('deps_count')}）"
if not deps["env_vars"]:
api_text = L("no_api")
else:
api_text = f"{L('api_required')} {', '.join(deps['env_vars'])}"
data_warnings = []
if "api.siliconflow.cn" in skill_content or "siliconflow" in skill_content.lower():
data_warnings.append(f"{L('data_upload')} api.siliconflow.cn")
if "curl" in skill_content and "https://" in skill_content:
urls = re.findall(r'https?://[^\s"'\)]+', skill_content)
external_domains = set()
for url in urls:
if "clawhub" not in url and "github" not in url and "openclaw" not in url:
domain = url.split("//")[1].split("/")[0]
external_domains.add(domain)
if external_domains:
data_warnings.append(f"{L('external_service')}：{', '.join(list(external_domains)[:3])}")
report = f"""
┌─────────────────────────────────────────────────────────┐
│ {L('conclusion_header')}：{rec_icon} {recommendation.ljust(30)}│
│ {L('score')}：{total_score:.0f}/100 ({grade}级) | {L('official_security').replace('🔒 ', '')}：{L('security_pass') if security_score >= 80 else L('security_review')} | {L('dep_burden').replace('📦 ', '')}：{L('deps_light') if dependency_score >= 80 else L('deps_heavy')} │
└─────────────────────────────────────────────────────────┘
━━━ {L('report_title')}：{name} ━━━━━━━━━━━━━━━━━━━━━━━━━
📊 {L('metrics')}
├─ {L('official_security')}：{security_text}
├─ {L('popularity')}：⭐ {downloads} {L('downloads')} | ⭐ {stars} {L('stars')}
├─ {L('maintenance')}：{maintenance_text}
├─ {L('dep_burden')}：{deps_text}
└─ {L('api_cost')}：{api_text}
{L('description')}
{description[:150]}{'...' if len(description) > 150 else ''}
{L('env_req')}"""
if deps["bins"]:
report += f"\n├─ {L('cli_tools')}：{', '.join(deps['bins'])}"
if deps["pip_packages"]:
report += f"\n├─ {L('python_pkg')}：{', '.join(deps['pip_packages'])}"
if deps["npm_packages"]:
report += f"\n├─ {L('node_pkg')}：{', '.join(deps['npm_packages'])}"
if deps["env_vars"]:
report += f"\n└─ {L('api_key')}：{', '.join(deps['env_vars'])}"
elif not deps["bins"] and not deps["pip_packages"] and not deps["npm_packages"]:
report += f"\n└─ {L('no_special_req')}"
if data_warnings:
report += f"\n\n{L('usage_note')}"
for warning in data_warnings:
report += f"\n├─ {warning}"
report += f"\n└─ {L('sensitive_data')}"
report += f"\n\n{L('install_advice')}"
if total_score >= 80:
report += f"\n{L('safe_install')}"
elif total_score >= 60:
report += f"\n{L('caution_install_text')}"
else:
report += f"\n{L('not_install_text')}"
if deps["env_vars"]:
report += f"\n{L('need_config')}：{', '.join(deps['env_vars'])}"
report += f"""
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
{L('meta_info')}
├─ {L('author')}：{owner}
├─ {L('version')}：{version}
├─ {L('license')}：{license_type}
└─ {L('score_time')}：{datetime.now().strftime('%Y-%m-%d %H:%M')}
"""
return report
# Example usage - English
print("=== English Report ===")
print(generate_report(skill_data, skill_content, "en"))
print("\n\n=== 中文报告 ===")
print(generate_report(skill_data, skill_content, "zh"))
PYEOF
Step 4: Output Report
The report is displayed directly to the user. No files are created.
🎯 结论：✅ 推荐安装
综合评分：85/100 (A级) | 安全：通过 | 依赖：轻量
━━━ 📋 Skill 评估报告：{skill-name} ━━━━━━━━━━━━━━━━━
...
Usage Flow
User (Chinese): "帮我看看 china-doc-ocr 这个skill怎么样"
Agent:
1. Detect user language → Chinese
2. Run: clawhub inspect china-doc-ocr
3. Fetch SKILL.md content from ClawHub API
4. Parse and analyze
5. Generate report in Chinese
6. Display report to user
---
User (English): "Is skill-xyz safe to install?"
Agent:
1. Detect user language → English
2. Run: clawhub inspect skill-xyz
3. Fetch SKILL.md content from ClawHub API
4. Parse and analyze
5. Generate report in English
6. Display report to user
Error Handling
Skill not found → "❌ 未找到该skill，请检查名称"
ClawHub API error → "❌ 无法连接ClawHub，请稍后重试"
Parse error → "⚠️ 部分信息解析失败，报告可能不完整"
Notes
- No files are generated (pure text output)
- Report shows conclusion first, then details
- Security status uses ClawHub's official scan results
- Scores are calculated dynamically based on multiple factors
- All data fetched in real-time from ClawHub