\r \r

ClawHub Skill Growth Engine / ClawHub技能热度增长引擎\r

\r

English: AI-powered growth engine for ClawHub skills — analyze user reviews, track global trending topics, and rewrite your skill metadata (title, description, tags) to maximize downloads and GitHub-style stars.\r \r 中文: ClawHub技能热度增长引擎——分析用户评论、追踪全网热点、优化技能标题与描述，一站式提升下载量与Star数。\r \r

Trigger Keywords / 触发关键词\r

\r Immediately activate when user mentions:\r \r

• ClawHub / clawhub 优化 / 技能优化 / 热度提升\r
• 下载量提升 / stars / 下载量 / 曝光量\r
• 评论分析 / 用户反馈 / review 分析 / feedback\r
• 热点追踪 / 热搜 / trending / 热点挖掘\r
• 标题优化 / description 优化 / SEO / 关键词优化\r
• skill 改进 / 技能改进 / 提升关注度\r
• GitHub stars 策略 / stars 增长 / trending 技巧\r \r

Core Capabilities / 核心能力\r

\r

1. User Review & Feedback Analysis Engine\r

/ 用户评论与反馈分析引擎\r \r Analyze user reviews, feedback, and usage data to extract actionable improvement suggestions.\r \r Analysis Dimensions:\r \r | Dimension | What It Detects | Action |\r |-----------|----------------|--------|\r | Feature Requests | Users asking for capabilities the skill lacks | Add missing modules to SKILL.md |\r | Pain Points | Frustration or confusion signals in reviews | Simplify instructions, add examples |\r | Competitor Mentions | Users comparing to other tools | Add differentiation points |\r | Localization Gaps | Non-Chinese users struggling (language barriers) | Add English README + bilingual docs |\r | Pricing/Access Issues | Access friction, download barriers | Optimize onboarding flow |\r | Emotional Signals | Excitement/disappointment in wording | Prioritize highly-praised features |\r \r Review Analysis Code:\r \r

import re\r
from collections import Counter\r
\r
def analyze_reviews(reviews: list[str]) -> dict:\r
    """\r
    Analyze user reviews and extract actionable insights.\r
    reviews: list of review texts\r
    Returns: dict with categorized insights\r
    """\r
    positive_keywords = [\r
        "great", "amazing", "love", "perfect", "useful", "helpful",\r
        "强大", "好用", "实用", "完美", "赞", "棒", "优秀"\r
    ]\r
    negative_keywords = [\r
        "confusing", "broken", "bug", "missing", "wrong",\r
        "复杂", "难用", "没用", "问题", "错误", "缺东西"\r
    ]\r
    feature_request_patterns = [\r
        r"wish.*could", r"would be nice", r"should have",\r
        r"建议", r"希望有", r"能否加入", r"期待"\r
    ]\r
\r
    results = {\r
        "positive_signals": [],\r
        "negative_signals": [],\r
        "feature_requests": [],\r
        "keywords": Counter()\r
    }\r
\r
    for review in reviews:\r
        text_lower = review.lower()\r
        # Detect sentiment signals\r
        for kw in positive_keywords:\r
            if kw in text_lower:\r
                results["positive_signals"].append(review)\r
                break\r
        for kw in negative_keywords:\r
            if kw in text_lower:\r
                results["negative_signals"].append(review)\r
                break\r
        # Detect feature requests\r
        for pattern in feature_request_patterns:\r
            if re.search(pattern, text_lower):\r
                results["feature_requests"].append(review)\r
                break\r
        # Word frequency (simple tokenizer)\r
        words = re.findall(r'\b\w{3,}\b', text_lower)\r
        results["keywords"].update(w for w in words if len(w) > 3)\r
\r
    return results\r
```\r
\r
**Output Format:**\r
\r
```markdown\r
## Review Analysis Report\r
\r
### 🔥 Top 5 Praised Features\r
1. [Feature] — mentioned X times\r
2. ...\r
\r
### 💡 Top 5 Feature Requests\r
1. [Request] — mentioned X times → Priority: HIGH/MEDIUM/LOW\r
2. ...\r
\r
### ⚠️ Top 5 Pain Points\r
1. [Pain point] — urgency: CRITICAL/HIGH/MEDIUM\r
2. ...\r
\r
### 📊 Keyword Frequency (Top 20)\r
| Keyword | Count | Sentiment |\r
|---------|-------|-----------|\r
| XXX     | 123   | Positive  |\r
| ...     | ...   | ...       |\r
\r
### 🎯 Recommended Actions\r
1. **[HIGH]** Add [missing feature] to address [request]\r
2. **[MEDIUM]** Simplify [confusing part] based on [pain point]\r
3. **[LOW]** Add [example/tutorial] to reduce confusion\r
```\r
\r
---\r
\r
### 2. Trending Topic Tracker\r
/ 全网热点追踪引擎\r
\r
Monitor trending topics across 40+ platforms to identify hot keywords that can boost skill visibility.\r
\r
**Supported Data Sources:**\r
\r
| Source | API/Endpoint | Data | Use Case |\r
|--------|-------------|------|----------|\r
| Weibo Hot Search | `uapis.cn` | Real-time热搜 | China trending |\r
| Zhihu Hot | `uapis.cn` | 知乎热榜 | Tech discussions |\r
| Bilibili Trending | `uapis.cn` | B站热搜 | Youth/tech audience |\r
| GitHub Trending | `github.com/trending` | GitHub热门 | Developer tools |\r
| WeChat Index | Tencent API | 微信指数 | China ecosystem |\r
| Baidu Index | `index.baidu.com` | 百度指数 | Search trends |\r
| Google Trends | `trends.google.com` | Global trends | International |\r
| Product Hunt | `producthunt.com` | PH热榜 | Global startup tools |\r
\r
**Trending Data Fetching Code:**\r
\r
```python\r
import requests\r
import json\r
\r
def fetch_weibo_trending(limit: int = 20) -> list[dict]:\r
    """Fetch real-time Weibo hot search topics."""\r
    url = "https://uapis.cn/api/hotboard"\r
    params = {"type": "weibo", "limit": limit}\r
    try:\r
        resp = requests.get(url, params=params, timeout=10)\r
        data = resp.json()\r
        return [\r
            {"rank": i+1, "title": item.get("title", ""),\r
             "hot": item.get("hot", ""), "url": item.get("url", "")}\r
            for i, item in enumerate(data.get("data", [])[:limit])\r
        ]\r
    except Exception as e:\r
        return [{"error": str(e)}]\r
\r
def fetch_github_trending(lang: str = "python", limit: int = 10) -> list[dict]:\r
    """Fetch GitHub trending repositories."""\r
    url = f"https://api.github.com/search/repositories"\r
    params = {\r
        "q": f"language:{lang}+created:>2025-01-01",\r
        "sort": "stars", "order": "desc", "per_page": limit\r
    }\r
    headers = {"Accept": "application/vnd.github.v3+json"}\r
    try:\r
        resp = requests.get(url, params=params, headers=headers, timeout=10)\r
        data = resp.json()\r
        return [\r
            {"name": item["name"], "stars": item["stargazers_count"],\r
             "description": item["description"], "url": item["html_url"]}\r
            for item in data.get("items", [])[:limit]\r
        ]\r
    except Exception as e:\r
        return [{"error": str(e)}]\r
\r
def google_trends_suggestions(keyword: str) -> list[str]:\r
    """Get related queries from Google Trends."""\r
    # Using pytrends library\r
    from pytrends.request import TrendReq\r
    pytrends = TrendReq(hl='en-US', tz=360)\r
    pytrends.build_payload([keyword], cat=0, timeframe='today 3-m', geo='')\r
    related = pytrends.related_queries()\r
    suggestions = []\r
    for kw_list in related.values():\r
        for item in kw_list.get('top', []) if kw_list else []:\r
            suggestions.append(item['query'])\r
    return suggestions[:10]\r
```\r
\r
**Trending Keyword Mapping for Skills:**\r
\r
```python\r
TRENDING_MAPPING = {\r
    # AI/LLM trends → skill keyword suggestions\r
    "DeepSeek": ["DeepSeek", "LLM", "AI agent", "Chinese AI"],\r
    "AI Agent": ["AI Agent", "workflow automation", "autonomous AI"],\r
    "Claude": ["Claude", "Anthropic", "context window", "reasoning"],\r
    "Stock Market": ["A-share", "quantitative trading", "technical analysis"],\r
    "Insurance": ["insurance tech", "insurtech", "risk management"],\r
    "Content Creation": ["AI video", "short video", "social media AI"],\r
    "Productivity": ["workflow automation", "efficiency", "productivity tools"],\r
}\r
\r
def map_trending_to_skill(trending_topics: list[str], skill_tags: list[str]) -> list[dict]:\r
    """Map trending topics to skill tags for SEO boost."""\r
    suggestions = []\r
    for topic in trending_topics:\r
        for trend, keywords in TRENDING_MAPPING.items():\r
            if trend.lower() in topic.lower():\r
                for kw in keywords:\r
                    if kw not in skill_tags:\r
                        suggestions.append({\r
                            "trend": topic,\r
                            "suggested_tag": kw,\r
                            "priority": "HIGH" if len(suggestions) \x3C 5 else "MEDIUM"\r
                        })\r
    return suggestions[:10]\r
```\r
\r
---\r
\r
### 3. SEO Title & Description Optimizer\r
/ SEO标题与描述优化器\r
\r
Rewrite skill titles and descriptions using proven SEO frameworks to maximize search visibility and click-through rate.\r
\r
**Title Optimization Framework:**\r
\r
| Principle | English Example | Chinese Example |\r
|-----------|----------------|----------------|\r
| **Front-load value** | "AI Insurance Claims Analyzer" | "保险理赔AI专家" |\r
| **Include keyword** | "Stock Technical Analysis" | "A股技术分析" |\r
| **Show outcome** | "Increase Downloads 10x" | "提升下载量" |\r
| **Use numbers** | "5-Step Process" | "7大核心能力" |\r
| **Be specific** | "China Insurance C-ROSS Actuarial" | "偿二代精算定价" |\r
| **Evoke emotion** | "Stop Losing Money" | "告别选号盲目" |\r
\r
**Description Structure (AIDA Framework):**\r
\r
```\r
A - Attention:    [Bold hook: "The ONLY ClawHub skill that..."]\r
I - Interest:     [Specific problem + your unique solution]\r
D - Desire:       [Concrete results: "Used by 500+ analysts"]\r
A - Action:       [Clear CTA: "Install now and..."]\r
```\r
\r
**Title Rewrite Examples:**\r
\r
| Original (Chinese) | Optimized (English) | Optimized (Chinese) | Stars Impact |\r
|--------------------|--------------------|--------------------|--------------|\r
| 招投标文书助手 | Enterprise Bid Document AI | 企业招投标文书AI助手 | ⭐⭐⭐ |\r
| 保险反欺诈 | Insurance Anti-Fraud Pro | 保险反欺诈分析专家 | ⭐⭐⭐⭐ |\r
| 缠论技术分析 | Chanlun Technical Analysis Engine | 缠论技术分析引擎 | ⭐⭐⭐⭐ |\r
| 彩票预测 | Lottery Data Analysis & Number Generator | 彩票数据分析选号助手 | ⭐⭐ |\r
\r
**Tag Optimization:**\r
\r
```python\r
def optimize_tags(current_tags: list[str], trending_keywords: list[str],\r
                  competitors: list[str]) -> dict:\r
    """\r
    Optimize skill tags for maximum discoverability.\r
    """\r
    must_have = ["clawhub", "skill", "ai-agent"]  # Always include\r
    high_value = ["python", "api", "automation", "analysis", "tool"]\r
    trending = [kw for kw in trending_keywords if kw not in current_tags][:5]\r
    competitor_tags = [t for t in competitors if t not in current_tags][:3]\r
\r
    optimized = must_have + high_value + trending + competitor_tags\r
    optimized = list(dict.fromkeys(optimized))[:20]  # Dedupe, max 20\r
\r
    return {\r
        "current_tags": current_tags,\r
        "recommended_tags": optimized,\r
        "new_tags_added": [t for t in optimized if t not in current_tags],\r
        "tags_removed": [t for t in current_tags if t not in optimized],\r
        "seo_score_improvement": f"+{len([t for t in optimized if t not in current_tags]) * 5}%",\r
    }\r
```\r
\r
---\r
\r
### 4. GitHub-Style Stars Growth Strategy\r
/ GitHub式Star增长策略\r
\r
Apply proven open-source project growth tactics to ClawHub skills.\r
\r
**Strategy Framework:**\r
\r
| Strategy | Implementation | Expected Impact |\r
|----------|---------------|----------------|\r
| **README Quality** | First 5 lines = summary. Clear "What/Why/How". Screenshots. | ⭐⭐⭐⭐ |\r
| **Keyword SEO** | Title + first 2 lines contain main keywords. README H1-H3 structure. | ⭐⭐⭐⭐⭐ |\r
| **Demo/Preview** | Short video or GIF showing the skill in action | ⭐⭐⭐⭐ |\r
| **Cross-posting** | Share on Zhihu, Weibo, Bilibili with skill link | ⭐⭐⭐ |\r
| **Community Building** | Create WeChat group / QQ group for skill users | ⭐⭐⭐ |\r
| **Regular Updates** | Version updates with changelog. "Updated 2 days ago" signal. | ⭐⭐⭐⭐ |\r
| **Comparison Content** | "vs [competitor]" articles to attract their users | ⭐⭐⭐ |\r
| **Trending Integration** | Tie skill to current hot topics (AI agents, DeepSeek, etc.) | ⭐⭐⭐⭐⭐ |\r
| **Multi-language** | English README = global audience 10x | ⭐⭐⭐⭐⭐ |\r
\r
**README Bilingual Template:**\r
\r
```markdown\r
# [English Title] / [中文标题]\r
\r
\x3C!-- English (for international users - put FIRST) -->\r
> **English Description**: One powerful sentence describing the skill's core value.\r
> Built for [target user]. Solves [specific problem].\r
\r
## ✨ Features / Features / 核心功能\r
\r
- ✅ Feature 1 with specific metric or result\r
- ✅ Feature 2 — [why it matters]\r
- ✅ Feature 3\r
\r
## 🚀 Quick Start\r
\r
```bash\r
# Install\r
npx clawhub install @yourname/your-skill\r
\r
# Use\r
/your-skill [command]\r
```\r
\r
## 📖 Documentation\r
\r
Full docs at [link] or continue reading below.\r
\r
---\r
\r
\x3C!-- 中文部分（放在英文后面，供国内用户阅读） -->\r
> **中文介绍**：一句话描述技能核心价值。针对[目标用户]，解决[具体问题]。\r
\r
## 🎯 核心功能\r
\r
- ✅ 功能1 — [具体效果/数据]\r
- ✅ 功能2 — [为什么有用]\r
- ✅ 功能3\r
\r
## ⚡ 快速上手\r
\r
1. 安装：`npx clawhub install @yourname/your-skill`\r
2. 使用：`/your-skill [命令]`\r
3. 查看文档见下方\r
\r
## 📚 详细文档\r
\r
[详细内容...]\r
```\r
\r
---\r
\r
### 5. Full Skill Optimization Report\r
/ 全流程技能优化报告\r
\r
Generate a complete optimization report combining all analysis:\r
\r
```markdown\r
# 🎯 ClawHub Skill Optimization Report\r
**Skill**: [skill-name]\r
**Generated**: [timestamp]\r
**Analyzer**: ClawHub Skill Growth Engine v1.0.0\r
\r
---\r
\r
## 📊 Current Status\r
\r
| Metric | Current | Target | Gap |\r
|--------|---------|--------|-----|\r
| Downloads | XXX | 1,000+ | +XXX |\r
| Stars | XX | 100+ | +XX |\r
| Description Length | XXX chars | 200-300 | OK |\r
| Tags Count | X | 10-15 | Add X |\r
| Has English README | No | Yes | MISSING |\r
| Last Updated | YYYY-MM-DD | \x3C 30 days | STALE |\r
\r
---\r
\r
## 🔥 Trending Keywords to Integrate\r
\r
| # | Trending Topic | Relevant Tag | Priority | Integration |\r
|---|---------------|-------------|---------|-------------|\r
| 1 | [topic] | [tag] | HIGH | Add to description |\r
| 2 | [topic] | [tag] | MEDIUM | Add to tags |\r
| ... | ... | ... | ... | ... |\r
\r
---\r
\r
## 📝 Title & Description Rewrite\r
\r
### Current\r
**Title**: [old title]\r
**Description**: [old description]\r
\r
### Optimized\r
**Title (EN)**: [optimized English title]\r
**Title (CN)**: [optimized Chinese title]\r
**Description (EN)**:\r
> [SEO-optimized English description - AIDA framework]\r
\r
**Description (CN)**:\r
> [优化后的中文描述]\r
\r
### Tags Optimization\r
**Current**: [tag1, tag2, ...]\r
**Add**: [new tags]\r
**Remove**: [obsolete tags]\r
\r
---\r
\r
## 💬 Review Analysis Findings\r
\r
### Top Requests from Users\r
1. [Request 1] → Add to SKILL.md priority section\r
2. [Request 2] → Add FAQ section\r
3. [Request 3] → Create tutorial\r
\r
### Pain Points to Fix\r
1. [Pain point 1] → Rewrite confusing section\r
2. [Pain point 2] → Add troubleshooting guide\r
\r
---\r
\r
## 📋 Action Plan (Priority Order)\r
\r
| # | Action | Type | Impact | Effort |\r
|---|--------|------|--------|--------|\r
| 1 | Add English README | Content | ⭐⭐⭐⭐⭐ | Low |\r
| 2 | Rewrite title with trending keyword | SEO | ⭐⭐⭐⭐⭐ | Low |\r
| 3 | Add missing feature from reviews | Feature | ⭐⭐⭐⭐ | Medium |\r
| 4 | Cross-post on [platform] | Promotion | ⭐⭐⭐⭐ | High |\r
| ... | ... | ... | ... | ... |\r
\r
---\r
\r
## ✅ Checklist for Publishing\r
\r
- [ ] Title contains main keyword\r
- [ ] Description is 200-300 characters (English)\r
- [ ] Tags include trending + evergreen keywords\r
- [ ] English README added (English FIRST, Chinese SECOND)\r
- [ ] Changelog updated\r
- [ ] Version bumped to X.X.X\r
- [ ] All reference files checked for broken links\r
- [ ] Bilingual trigger keywords in SKILL.md\r
```\r
\r
---\r
\r
## Workflow / 工作流程\r
\r
```\r
User Input: Current skill details / user reviews / trending goal\r
    ↓\r
[Step 1] Analyze Reviews → Extract pain points + requests\r
[Step 2] Fetch Trending Data → Map to skill keywords\r
[Step 3] SEO Rewrite → Title + description + tags\r
[Step 4] GitHub Stars Strategy → README + promotion plan\r
[Step 5] Generate Full Report → Actionable checklist\r
    ↓\r
User confirms changes\r
    ↓\r
Apply: Update SKILL.md + README.md + tags + changelog\r
```\r
\r
---\r
\r
## Reference Files\r
\r
| File | Content |\r
|------|---------|\r
| `references/seo_optimization_guide.md` | Full SEO framework + keyword research methods |\r
| `references/trending_topic_tracker.md` | Trending APIs + code + keyword mapping |\r
| `references/review_analysis_templates.md` | Review analysis templates + sentiment scoring |\r