clawhub-skill-optimizer

by gechengling

Install this Skill

curl -fsSL -o clawhub-skill-optimizer.zip https://skill.seembox.com/api/v1/skills/clawhub-skill-optimizer/download && unzip clawhub-skill-optimizer.zip

Download clawhub-skill-optimizer.zip

SKILL.md About

---
name: ClawHub Skill Growth Engine
description: AI-powered ClawHub skill growth optimizer — analyzes reviews, tracks trending topics, and rewrites titles/descriptions for maximum downloads and stars. Triggers: clawhub optimization, skill growth, SEO, stars, downloads, review analysis, trending keywords, skill improvement, GitHub stars strategy.
version: 1.0.0
---

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

> **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.
>
> **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。

## Trigger Keywords / 触发关键词

Immediately activate when user mentions:

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

## Core Capabilities / 核心能力

### 1. User Review & Feedback Analysis Engine
/ 用户评论与反馈分析引擎

Analyze user reviews, feedback, and usage data to extract actionable improvement suggestions.

**Analysis Dimensions:**

| Dimension | What It Detects | Action |
|-----------|----------------|--------|
| **Feature Requests** | Users asking for capabilities the skill lacks | Add missing modules to SKILL.md |
| **Pain Points** | Frustration or confusion signals in reviews | Simplify instructions, add examples |
| **Competitor Mentions** | Users comparing to other tools | Add differentiation points |
| **Localization Gaps** | Non-Chinese users struggling (language barriers) | Add English README + bilingual docs |
| **Pricing/Access Issues** | Access friction, download barriers | Optimize onboarding flow |
| **Emotional Signals** | Excitement/disappointment in wording | Prioritize highly-praised features |

**Review Analysis Code:**

```python
import re
from collections import Counter

def analyze_reviews(reviews: list[str]) -> dict:
    """
    Analyze user reviews and extract actionable insights.
    reviews: list of review texts
    Returns: dict with categorized insights
    """
    positive_keywords = [
        "great", "amazing", "love", "perfect", "useful", "helpful",
        "强大", "好用", "实用", "完美", "赞", "棒", "优秀"
    ]
    negative_keywords = [
        "confusing", "broken", "bug", "missing", "wrong",
        "复杂", "难用", "没用", "问题", "错误", "缺东西"
    ]
    feature_request_patterns = [
        r"wish.*could", r"would be nice", r"should have",
        r"建议", r"希望有", r"能否加入", r"期待"
    ]

results = {
        "positive_signals": [],
        "negative_signals": [],
        "feature_requests": [],
        "keywords": Counter()
    }

for review in reviews:
        text_lower = review.lower()
        # Detect sentiment signals
        for kw in positive_keywords:
            if kw in text_lower:
                results["positive_signals"].append(review)
                break
        for kw in negative_keywords:
            if kw in text_lower:
                results["negative_signals"].append(review)
                break
        # Detect feature requests
        for pattern in feature_request_patterns:
            if re.search(pattern, text_lower):
                results["feature_requests"].append(review)
                break
        # Word frequency (simple tokenizer)
        words = re.findall(r'\b\w{3,}\b', text_lower)
        results["keywords"].update(w for w in words if len(w) > 3)

return results
```

**Output Format:**

```markdown
## Review Analysis Report

### 🔥 Top 5 Praised Features
1. [Feature] — mentioned X times
2. ...

### 💡 Top 5 Feature Requests
1. [Request] — mentioned X times → Priority: HIGH/MEDIUM/LOW
2. ...

### ⚠️ Top 5 Pain Points
1. [Pain point] — urgency: CRITICAL/HIGH/MEDIUM
2. ...

### 📊 Keyword Frequency (Top 20)
| Keyword | Count | Sentiment |
|---------|-------|-----------|
| XXX     | 123   | Positive  |
| ...     | ...   | ...       |

### 🎯 Recommended Actions
1. **[HIGH]** Add [missing feature] to address [request]
2. **[MEDIUM]** Simplify [confusing part] based on [pain point]
3. **[LOW]** Add [example/tutorial] to reduce confusion
```

---

### 2. Trending Topic Tracker
/ 全网热点追踪引擎

Monitor trending topics across 40+ platforms to identify hot keywords that can boost skill visibility.

**Supported Data Sources:**

| Source | API/Endpoint | Data | Use Case |
|--------|-------------|------|----------|
| Weibo Hot Search | `uapis.cn` | Real-time热搜 | China trending |
| Zhihu Hot | `uapis.cn` | 知乎热榜 | Tech discussions |
| Bilibili Trending | `uapis.cn` | B站热搜 | Youth/tech audience |
| GitHub Trending | `github.com/trending` | GitHub热门 | Developer tools |
| WeChat Index | Tencent API | 微信指数 | China ecosystem |
| Baidu Index | `index.baidu.com` | 百度指数 | Search trends |
| Google Trends | `trends.google.com` | Global trends | International |
| Product Hunt | `producthunt.com` | PH热榜 | Global startup tools |

**Trending Data Fetching Code:**

```python
import requests
import json

def fetch_weibo_trending(limit: int = 20) -> list[dict]:
    """Fetch real-time Weibo hot search topics."""
    url = "https://uapis.cn/api/hotboard"
    params = {"type": "weibo", "limit": limit}
    try:
        resp = requests.get(url, params=params, timeout=10)
        data = resp.json()
        return [
            {"rank": i+1, "title": item.get("title", ""),
             "hot": item.get("hot", ""), "url": item.get("url", "")}
            for i, item in enumerate(data.get("data", [])[:limit])
        ]
    except Exception as e:
        return [{"error": str(e)}]

def fetch_github_trending(lang: str = "python", limit: int = 10) -> list[dict]:
    """Fetch GitHub trending repositories."""
    url = f"https://api.github.com/search/repositories"
    params = {
        "q": f"language:{lang}+created:>2025-01-01",
        "sort": "stars", "order": "desc", "per_page": limit
    }
    headers = {"Accept": "application/vnd.github.v3+json"}
    try:
        resp = requests.get(url, params=params, headers=headers, timeout=10)
        data = resp.json()
        return [
            {"name": item["name"], "stars": item["stargazers_count"],
             "description": item["description"], "url": item["html_url"]}
            for item in data.get("items", [])[:limit]
        ]
    except Exception as e:
        return [{"error": str(e)}]

def google_trends_suggestions(keyword: str) -> list[str]:
    """Get related queries from Google Trends."""
    # Using pytrends library
    from pytrends.request import TrendReq
    pytrends = TrendReq(hl='en-US', tz=360)
    pytrends.build_payload([keyword], cat=0, timeframe='today 3-m', geo='')
    related = pytrends.related_queries()
    suggestions = []
    for kw_list in related.values():
        for item in kw_list.get('top', []) if kw_list else []:
            suggestions.append(item['query'])
    return suggestions[:10]
```

**Trending Keyword Mapping for Skills:**

```python
TRENDING_MAPPING = {
    # AI/LLM trends → skill keyword suggestions
    "DeepSeek": ["DeepSeek", "LLM", "AI agent", "Chinese AI"],
    "AI Agent": ["AI Agent", "workflow automation", "autonomous AI"],
    "Claude": ["Claude", "Anthropic", "context window", "reasoning"],
    "Stock Market": ["A-share", "quantitative trading", "technical analysis"],
    "Insurance": ["insurance tech", "insurtech", "risk management"],
    "Content Creation": ["AI video", "short video", "social media AI"],
    "Productivity": ["workflow automation", "efficiency", "productivity tools"],
}

def map_trending_to_skill(trending_topics: list[str], skill_tags: list[str]) -> list[dict]:
    """Map trending topics to skill tags for SEO boost."""
    suggestions = []
    for topic in trending_topics:
        for trend, keywords in TRENDING_MAPPING.items():
            if trend.lower() in topic.lower():
                for kw in keywords:
                    if kw not in skill_tags:
                        suggestions.append({
                            "trend": topic,
                            "suggested_tag": kw,
                            "priority": "HIGH" if len(suggestions) < 5 else "MEDIUM"
                        })
    return suggestions[:10]
```

---

### 3. SEO Title & Description Optimizer
/ SEO标题与描述优化器

Rewrite skill titles and descriptions using proven SEO frameworks to maximize search visibility and click-through rate.

**Title Optimization Framework:**

| Principle | English Example | Chinese Example |
|-----------|----------------|----------------|
| **Front-load value** | "AI Insurance Claims Analyzer" | "保险理赔AI专家" |
| **Include keyword** | "Stock Technical Analysis" | "A股技术分析" |
| **Show outcome** | "Increase Downloads 10x" | "提升下载量" |
| **Use numbers** | "5-Step Process" | "7大核心能力" |
| **Be specific** | "China Insurance C-ROSS Actuarial" | "偿二代精算定价" |
| **Evoke emotion** | "Stop Losing Money" | "告别选号盲目" |

**Description Structure (AIDA Framework):**

```
A - Attention:    [Bold hook: "The ONLY ClawHub skill that..."]
I - Interest:     [Specific problem + your unique solution]
D - Desire:       [Concrete results: "Used by 500+ analysts"]
A - Action:       [Clear CTA: "Install now and..."]
```

**Title Rewrite Examples:**

| Original (Chinese) | Optimized (English) | Optimized (Chinese) | Stars Impact |
|--------------------|--------------------|--------------------|--------------|
| 招投标文书助手 | Enterprise Bid Document AI | 企业招投标文书AI助手 | ⭐⭐⭐ |
| 保险反欺诈 | Insurance Anti-Fraud Pro | 保险反欺诈分析专家 | ⭐⭐⭐⭐ |
| 缠论技术分析 | Chanlun Technical Analysis Engine | 缠论技术分析引擎 | ⭐⭐⭐⭐ |
| 彩票预测 | Lottery Data Analysis & Number Generator | 彩票数据分析选号助手 | ⭐⭐ |

**Tag Optimization:**

```python
def optimize_tags(current_tags: list[str], trending_keywords: list[str],
                  competitors: list[str]) -> dict:
    """
    Optimize skill tags for maximum discoverability.
    """
    must_have = ["clawhub", "skill", "ai-agent"]  # Always include
    high_value = ["python", "api", "automation", "analysis", "tool"]
    trending = [kw for kw in trending_keywords if kw not in current_tags][:5]
    competitor_tags = [t for t in competitors if t not in current_tags][:3]

optimized = must_have + high_value + trending + competitor_tags
    optimized = list(dict.fromkeys(optimized))[:20]  # Dedupe, max 20

return {
        "current_tags": current_tags,
        "recommended_tags": optimized,
        "new_tags_added": [t for t in optimized if t not in current_tags],
        "tags_removed": [t for t in current_tags if t not in optimized],
        "seo_score_improvement": f"+{len([t for t in optimized if t not in current_tags]) * 5}%",
    }
```

---

### 4. GitHub-Style Stars Growth Strategy
/ GitHub式Star增长策略

Apply proven open-source project growth tactics to ClawHub skills.

**Strategy Framework:**

| Strategy | Implementation | Expected Impact |
|----------|---------------|----------------|
| **README Quality** | First 5 lines = summary. Clear "What/Why/How". Screenshots. | ⭐⭐⭐⭐ |
| **Keyword SEO** | Title + first 2 lines contain main keywords. README H1-H3 structure. | ⭐⭐⭐⭐⭐ |
| **Demo/Preview** | Short video or GIF showing the skill in action | ⭐⭐⭐⭐ |
| **Cross-posting** | Share on Zhihu, Weibo, Bilibili with skill link | ⭐⭐⭐ |
| **Community Building** | Create WeChat group / QQ group for skill users | ⭐⭐⭐ |
| **Regular Updates** | Version updates with changelog. "Updated 2 days ago" signal. | ⭐⭐⭐⭐ |
| **Comparison Content** | "vs [competitor]" articles to attract their users | ⭐⭐⭐ |
| **Trending Integration** | Tie skill to current hot topics (AI agents, DeepSeek, etc.) | ⭐⭐⭐⭐⭐ |
| **Multi-language** | English README = global audience 10x | ⭐⭐⭐⭐⭐ |

**README Bilingual Template:**

```markdown
# [English Title] / [中文标题]

> **English Description**: One powerful sentence describing the skill's core value.
> Built for [target user]. Solves [specific problem].

## ✨ Features / Features / 核心功能

- ✅ Feature 1 with specific metric or result
- ✅ Feature 2 — [why it matters]
- ✅ Feature 3

## 🚀 Quick Start

```bash
# Install
npx clawhub install @yourname/your-skill

# Use
/your-skill [command]
```

## 📖 Documentation

Full docs at [link] or continue reading below.

---

> **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]。

## 🎯 核心功能

- ✅ 功能1 — [具体效果/数据]
- ✅ 功能2 — [为什么有用]
- ✅ 功能3

## ⚡ 快速上手

1. 安装：`npx clawhub install @yourname/your-skill`
2. 使用：`/your-skill [命令]`
3. 查看文档见下方

## 📚 详细文档

[详细内容...]
```

---

### 5. Full Skill Optimization Report
/ 全流程技能优化报告

Generate a complete optimization report combining all analysis:

```markdown
# 🎯 ClawHub Skill Optimization Report
**Skill**: [skill-name]
**Generated**: [timestamp]
**Analyzer**: ClawHub Skill Growth Engine v1.0.0

---

## 📊 Current Status

| Metric | Current | Target | Gap |
|--------|---------|--------|-----|
| Downloads | XXX | 1,000+ | +XXX |
| Stars | XX | 100+ | +XX |
| Description Length | XXX chars | 200-300 | OK |
| Tags Count | X | 10-15 | Add X |
| Has English README | No | Yes | MISSING |
| Last Updated | YYYY-MM-DD | < 30 days | STALE |

---

## 🔥 Trending Keywords to Integrate

| # | Trending Topic | Relevant Tag | Priority | Integration |
|---|---------------|-------------|---------|-------------|
| 1 | [topic] | [tag] | HIGH | Add to description |
| 2 | [topic] | [tag] | MEDIUM | Add to tags |
| ... | ... | ... | ... | ... |

---

## 📝 Title & Description Rewrite

### Current
**Title**: [old title]
**Description**: [old description]

### Optimized
**Title (EN)**: [optimized English title]
**Title (CN)**: [optimized Chinese title]
**Description (EN)**:
> [SEO-optimized English description - AIDA framework]

**Description (CN)**:
> [优化后的中文描述]

### Tags Optimization
**Current**: [tag1, tag2, ...]
**Add**: [new tags]
**Remove**: [obsolete tags]

---

## 💬 Review Analysis Findings

### Top Requests from Users
1. [Request 1] → Add to SKILL.md priority section
2. [Request 2] → Add FAQ section
3. [Request 3] → Create tutorial

### Pain Points to Fix
1. [Pain point 1] → Rewrite confusing section
2. [Pain point 2] → Add troubleshooting guide

---

## 📋 Action Plan (Priority Order)

| # | Action | Type | Impact | Effort |
|---|--------|------|--------|--------|
| 1 | Add English README | Content | ⭐⭐⭐⭐⭐ | Low |
| 2 | Rewrite title with trending keyword | SEO | ⭐⭐⭐⭐⭐ | Low |
| 3 | Add missing feature from reviews | Feature | ⭐⭐⭐⭐ | Medium |
| 4 | Cross-post on [platform] | Promotion | ⭐⭐⭐⭐ | High |
| ... | ... | ... | ... | ... |

---

## ✅ Checklist for Publishing

- [ ] Title contains main keyword
- [ ] Description is 200-300 characters (English)
- [ ] Tags include trending + evergreen keywords
- [ ] English README added (English FIRST, Chinese SECOND)
- [ ] Changelog updated
- [ ] Version bumped to X.X.X
- [ ] All reference files checked for broken links
- [ ] Bilingual trigger keywords in SKILL.md
```

---

## Workflow / 工作流程

```
User Input: Current skill details / user reviews / trending goal
    ↓
[Step 1] Analyze Reviews → Extract pain points + requests
[Step 2] Fetch Trending Data → Map to skill keywords
[Step 3] SEO Rewrite → Title + description + tags
[Step 4] GitHub Stars Strategy → README + promotion plan
[Step 5] Generate Full Report → Actionable checklist
    ↓
User confirms changes
    ↓
Apply: Update SKILL.md + README.md + tags + changelog
```

---

## Reference Files

| File | Content |
|------|---------|
| `references/seo_optimization_guide.md` | Full SEO framework + keyword research methods |
| `references/trending_topic_tracker.md` | Trending APIs + code + keyword mapping |
| `references/review_analysis_templates.md` | Review analysis templates + sentiment scoring |

_meta.json Metadata

{
  "ownerId": "kn74e704j3ygjcygnpf02rdvd185js13",
  "publishedAt": 1777906978393,
  "slug": "clawhub-skill-optimizer",
  "version": "1.0.0"
}