📦 ClawHub Skill Growth Engine — ClawHub 技能 Growth Engine

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

English: AI-powered growth engine for ClawHub 技能s — analyze user reviews, 追踪 global trending topics, and rewrite your 技能 metadata (title, description, tags) to maximize 下载s 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 技能 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

• User Review & Feedback Analysis Engine

/ 用户评论与反馈分析引擎

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

Analysis Dimensions:

Dimension What It 检测s Action Feature 请求s Users asking for capabilities the 技能 lacks 添加 missing 模块s to 技能.md PAIn Points Frustration or confusion 签名als in reviews Simplify instructions, 添加 examples Competitor Mentions Users comparing to other 工具s 添加 differentiation points Localization Gaps Non-Chinese users struggling (language barriers) 添加 English README + bilingual docs Pricing/访问 Issues 访问 friction, 下载 barriers 优化 onboarding flow Emotional 签名als Excitement/dis应用ointment in wording Prioritize highly-prAIsed features

Review Analysis Code:

导入 re from collections 导入 Counter

def analyze_reviews(reviews: 列出[str]) -> dict: """ Analyze user reviews and 提取 actionable insights. reviews: 列出 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_请求_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" ]

结果s = { "positive_签名als": [], "negative_签名als": [], "feature_请求s": [], "keywords": Counter() }

for review in reviews: text_lower = review.lower() # 检测 sentiment 签名als for kw in positive_keywords: if kw in text_lower: 结果s["positive_签名als"].应用end(review) break for kw in negative_keywords: if kw in text_lower: 结果s["negative_签名als"].应用end(review) break # 检测 feature 请求s for pattern in feature_请求_patterns: if re.搜索(pattern, text_lower): 结果s["feature_请求s"].应用end(review) break # Word frequency (simple 令牌izer) words = re.findall(r'\b\w{3,}\b', text_lower) 结果s["keywords"].更新(w for w in words if len(w) > 3)

return 结果s

输出 格式化:

Review Analysis 报告

🔥 Top 5 PrAIsed Features

• [Feature] — mentioned X times
• ...

💡 Top 5 Feature 请求s

• [请求] — mentioned X times → Priority: HIGH/MEDIUM/LOW
• ...

⚠️ Top 5 PAIn Points

• [PAIn point] — urgency: CRITICAL/HIGH/MEDIUM
• ...

📊 Keyword Frequency (Top 20)

🎯 Recommended Actions

• [HIGH] 添加 [missing feature] to 添加ress [请求]
• [MEDIUM] Simplify [confusing part] based on [pAIn point]
• [LOW] 添加 [example/tutorial] to reduce confusion

• Trending Topic 追踪er

/ 全网热点追踪引擎

监控 trending topics across 40+ 平台s to identify hot keywords that can boost 技能 visibility.

Supported Data Sources:

Source API/端点 Data Use Case Weibo Hot 搜索 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 工具s WeChat 索引 Tencent API 微信指数 China eco系统 BAIdu 索引 索引.bAIdu.com 百度指数 搜索 trends Google Trends trends.google.com Global trends International Product Hunt producthunt.com PH热榜 Global 启动up 工具s

Trending Data Fetching Code:

导入 请求s 导入 json

def fetch_weibo_trending(limit: int = 20) -> 列出[dict]: """Fetch real-time Weibo hot 搜索 topics.""" url = "https://uAPIs.cn/API/hotboard" params = {"type": "weibo", "limit": limit} try: resp = 请求s.获取(url, params=params, timeout=10) data = resp.json() return [ {"rank": i+1, "title": item.获取("title", ""), "hot": item.获取("hot", ""), "url": item.获取("url", "")} for i, item in enumerate(data.获取("data", [])[:limit]) ] except 异常 as e: return [{"error": str(e)}]

def fetch_github_trending(lang: str = "python", limit: int = 10)