Weibo Trends Analyzer – 微博热搜创意产品分析

Overview

This skill helps you identify creative product opportunities from Weibo trending topics. It fetches real-time hot search data, researches comprehensive background information, evaluates product development potential, and presents findings in an interactive dashboard.

Keywords: Weibo, 微博, trending topics, hot search, 热搜, product ideas, creative products, market analysis, social media trends, Chinese market

Workflow

1. Fetch Weibo Trending Topics

Default API: https://apis.tianapi.com/weibohot/index?key=4dfdf794141101d7bb8ece0294dbbc02

When the user requests Weibo trending analysis, fetch the current hot search list:

curl -s "https://apis.tianapi.com/weibohot/index?key=4dfdf794141101d7bb8ece0294dbbc02"

API Response Processing:

The API returns data in this format:

{
  "code": 200,
  "msg": "success",
  "result": {
    "list": [
      {
        "hotword": "trending keyword",
        "hotwordnum": "1234567",
        "hottag": "新/热/荐"
      }
    ]
  }
}

Field Mapping:

• hotword → Trending keyword (热搜关键词)
• hotwordnum → Heat value (热度值), may contain category prefix like “综艺 587870”
• hottag → Tag (标签): “新”(new), “热”(hot), “荐”(recommended), or empty
• Ranking position → Inferred from array index (1-based)

Parsing Instructions:

1. Check if code == 200 to confirm success
2. Extract the result.list array
3. For each item in the list:
   • Rank = array index + 1
   • Keyword = hotword
   • Heat value = extract numeric value from hotwordnum (remove category prefix if present)
   • Tag = hottag
   • Category = extract from hotwordnum prefix if exists (e.g., “综艺”, “剧集”, “盛典”, “演出”)
4. Limit analysis to top 10-15 items to manage processing time

Error Handling:

If API fetch fails, follow this fallback strategy:

1. API Returns Error Code (code ≠ 200):

   • Log the error message from API response
   • Inform user: “API returned error: {msg}. Would you like to use mock data instead?”
   • Suggest checking API key or quota limits
   • If user agrees, use .claude/skills/weibo-trends-analyzer/weibo-mock-data.json

2. Network/Connection Failure:

   • Inform user: “Unable to connect to API. Possible network issue.”
   • Offer to use mock data: .claude/skills/weibo-trends-analyzer/weibo-mock-data.json
   • Suggest verifying internet connection

3. Invalid JSON Response:

   • Log the response received
   • Inform user: “API returned invalid data format”
   • Recommend checking if API endpoint has changed
   • Fall back to mock data if available

4. Empty or Malformed Data:

   • If result.list is empty or missing
   • Inform user: “No trending topics found in API response”
   • Use mock data as fallback

2. Deep Research Each Trending Topic

For EACH trending topic, perform 2 focused web searches to gather essential background:

Search Strategy (2 searches per topic):

Search 1: Context & Background Combine social media discussions and news background in one search:

• Search query examples:
  • “{keyword} 微博 新闻背景”
  • “{keyword} 热搜原因 讨论”
  • “{keyword} latest news 用户看法”

Goal: Understand WHAT the trend is about and WHY it’s trending

Search 2: User Insights & Market Potential Focus on consumer perspective and product opportunities:

• Search query examples:
  • “{keyword} 用户需求 产品”
  • “{keyword} 消费者痛点”
  • “{keyword} 产品创意 市场”

Goal: Identify user needs, pain points, and product development opportunities

Information to Extract: From the 2 searches, gather:

• ✅ Social media sentiment and discussion volume (社交媒体讨论)
• ✅ News background and event context (新闻背景)
• ✅ Target demographics and audience size (目标人群)
• ✅ User pain points and unmet needs (用户痛点)
• ✅ Existing products or market gaps (市场机会)
• ✅ Cultural/social significance (文化意义)

Error Handling for Web Searches:

1. Search Returns No Results:

   • Log: “No search results for: {keyword}”
   • Mark research as “Limited data available”
   • Proceed with analysis using keyword itself and general market knowledge
   • Note in dashboard: “⚠️ 背景研究受限”

2. Search Timeout or Failure:

   • Retry once with simplified query (just keyword without additional terms)
   • If retry fails, mark as “Search unavailable”
   • Continue analysis with available data
   • Note limitation in product analysis

3. Irrelevant Search Results:

   • If results don’t match trending topic context:
   • Try alternative search query with different keywords
   • Use general industry knowledge for analysis
   • Document: “Based on general market analysis”

4. Partial Search Success (1 of 2 succeeds):

   • Proceed with available search data
   • Note which aspect is missing (context vs. user insights)
   • Make conservative estimates for missing information
   • Mark in dashboard with: “⚠️ 部分数据”

3. AI-Powered Product Ideation & Scoring

For each trending topic, analyze and generate creative product ideas using this scoring framework:

Scoring System (Total: 100 Points)

1. Product Development Potential (可发展度): 40 points

   • Market size and scalability (15 points)
   • Technical feasibility (10 points)
   • Trend longevity vs. fleeting fad (10 points)
   • Competitive landscape (5 points)

2. Interest Level (有趣度): 20 points

   • Creative uniqueness (10 points)
   • Emotional appeal (5 points)
   • Share-ability/viral potential (5 points)

3. Practical Life Utility (生活有用度): 20 points

   • Daily life integration (10 points)
   • Problem-solving capability (5 points)
   • Target audience size (5 points)

4. Small-Scale Production Ease (小规模生产容易程度): 20 points

   • Manufacturing complexity (10 points)
   • Material accessibility (5 points)
   • Cost efficiency for small batches (5 points)

Product Concept Requirements:

For each trend, generate 1-3 creative product concepts including:

• Market Category (市场赛道): Which product category (e.g., home decor, fashion accessories, stationery, tech gadgets, lifestyle products, toys, etc.)
• Product Name (产品名称): Catchy, memorable name
• Target Audience (销售对象人群): Specific demographic (age, interests, income level, lifestyle)
• Manufacturing Characteristics (工厂批量生产特点):
  • Production method (e.g., 3D printing, injection molding, screen printing, laser cutting)
  • Material requirements
  • Minimum order quantity (MOQ) feasibility
  • Lead time estimates
  • Cost structure (per unit at different volumes)
• Detailed Description (详细描述): How the product relates to the trending topic
• Total Score (总分): Sum of all four scoring dimensions
• Score Breakdown (评分分析): Brief justification for each score component

Scoring Guidelines:

• Be objective and realistic
• Consider Chinese market context
• Factor in current manufacturing capabilities
• Account for trend cycle timing

4. Generate Interactive HTML Dashboard

Create a comprehensive, visually appealing HTML dashboard with the following structure:

Dashboard Components:

A. Header Section

- Title: "微博热搜创意产品分析报告 - Weibo Trends Product Analysis"
- Generation timestamp
- Total trends analyzed count
- Summary statistics (average score, top categories, etc.)

B. Highlight Section – Top Performers Display products by score tiers:

• 🏆 Outstanding (优秀) – Score ≥ 80:

  • Prominent display with gold/premium styling
  • Enlarged cards with detailed breakdown
  • Recommended action: “优先开发推荐”

• ⭐ Good (良好) – Score 60-79:

  • Standard card layout with highlighted borders
  • Recommended action: “可考虑开发”

• 📋 Other Products – Score < 60:

  • Compact list view
  • Recommended action: “观望或需优化”

C. Product Cards

Each product card should display:

<div class="product-card score-tier-{excellent/good/other}">
  <div class="trend-info">
    <h3>{Trending Keyword}</h3>
    <span class="rank">热搜排名: #{rank}</span>
    <span class="heat">热度: {heat_value}</span>
  </div>

  <div class="product-concept">
    <h4>{Product Name}</h4>
    <div class="total-score">{Total Score}/100</div>
    <div class="score-badge">{优秀/良好/其他}</div>

    <div class="details">
      <p><strong>市场赛道:</strong> {market_category}</p>
      <p><strong>目标人群:</strong> {target_audience}</p>
      <p><strong>产品描述:</strong> {description}</p>
      <p><strong>生产特点:</strong> {manufacturing_details}</p>
    </div>

    <div class="score-breakdown">
      <h5>评分详情</h5>
      <div class="score-bar">
        <span>可发展度</span>
        <progress value="{score}" max="40"></progress>
        <span>{score}/40</span>
      </div>
      <div class="score-bar">
        <span>有趣度</span>
        <progress value="{score}" max="20"></progress>
        <span>{score}/20</span>
      </div>
      <div class="score-bar">
        <span>生活有用度</span>
        <progress value="{score}" max="20"></progress>
        <span>{score}/20</span>
      </div>
      <div class="score-bar">
        <span>生产容易度</span>
        <progress value="{score}" max="20"></progress>
        <span>{score}/20</span>
      </div>
    </div>

    <div class="analysis">
      <h5>分数分析</h5>
      <p>{score_justification}</p>
    </div>
  </div>

  <div class="research-summary">
    <h5>背景研究</h5>
    <ul>
      <li><strong>社交媒体:</strong> {social_media_insights}</li>
      <li><strong>新闻背景:</strong> {news_background}</li>
      <li><strong>用户洞察:</strong> {user_insights}</li>
    </ul>
  </div>
</div>

D. Dashboard Styling Requirements

/* Color Scheme */
- Excellent products (≥80): Gold/amber theme (#FFD700, #FFA500)
- Good products (60-79): Blue/cyan theme (#4A90E2, #50C8E8)
- Other products (<60): Gray/neutral theme (#95A5A6, #BDC3C7)

/* Design Guidelines */
- Responsive layout (grid or flexbox)
- Clean, modern aesthetics
- Clear visual hierarchy
- Easy-to-read typography (Chinese + English support)
- Interactive hover effects
- Sortable/filterable options
- Progress bars for score visualization
- Badge system for quick identification

E. Interactive Features

Include JavaScript for:

• Sort by score (highest to lowest, lowest to highest)
• Filter by score tier (优秀/良好/其他)
• Filter by market category
• Search functionality for keywords
• Expandable/collapsible detailed sections
• Export to PDF option (bonus)

F. Footer Section

- Disclaimer about trend volatility
- Recommendation to conduct further market research
- Generation metadata (API source, analysis timestamp)
- Skill version information

5. File Output

Generate the following files:

1. weibo-trends-analysis-{YYYY-MM-DD}.html: Complete interactive dashboard
2. weibo-trends-data-{YYYY-MM-DD}.json: Raw structured data for further processing (optional)

Error Handling for File Generation:

1. File Write Permission Denied:

   • Try alternative filename with timestamp: weibo-trends-analysis-{YYYY-MM-DD-HHmmss}.html
   • If still fails, inform user: “Unable to write files. Please check directory permissions.”
   • Suggest user-provided output path

2. HTML Generation Error:

   • If template rendering fails, create simplified HTML version with basic table layout
   • Ensure at minimum: product names, scores, and basic descriptions are included
   • Log error details for troubleshooting

3. Data Validation Before Output:

   • Verify at least 1 product concept was generated
   • Check all scores are within valid ranges (0-40, 0-20, etc.)
   • Ensure required fields are present (product name, score, description)
   • If validation fails, inform user which topics had issues

4. Large File Handling:

   • If analyzing >20 topics, warn user about large file size
   • Consider generating paginated HTML or summary + detailed sections
   • Ensure browser compatibility for large datasets

Best Practices

Research Quality:

• Perform 2 focused web searches per trending topic (optimized for efficiency)
• Synthesize information from multiple sources within each search
• Verify factual accuracy
• Note information freshness
• Prioritize quality over quantity in search results

Product Ideation:

• Think beyond obvious connections
• Consider cultural context and Chinese consumer behavior
• Evaluate both short-term trend exploitation and long-term product viability
• Be creative but realistic

Scoring Objectivity:

• Use consistent criteria across all products
• Justify scores with specific evidence
• Avoid bias toward certain product categories
• Consider manufacturing realities in China

Dashboard Quality:

• Ensure all Chinese characters display correctly (UTF-8 encoding)
• Test responsiveness on different screen sizes
• Validate HTML/CSS/JS syntax
• Include fallback fonts for Chinese text
• Make data visualizations clear and intuitive

Example Usage Flow

User: "分析微博热搜"
或
User: "分析今日微博热搜并生成产品创意"

Claude:
1. Fetches trending data from default API (https://apis.tianapi.com/weibohot/index?key=...)
   - If API fails, offers to use mock data
2. Parses the result.list array and extracts top 10-15 trending topics
3. For each topic:
   - Performs 2 focused web searches for background research
   - Handles search failures gracefully with fallback strategies
   - Analyzes market potential and user needs
   - Generates creative product concepts
   - Calculates detailed scores
4. Validates all generated data
5. Compiles all data into structured format
6. Generates interactive HTML dashboard with error indicators if needed
7. Saves output files

Output:
- weibo-trends-analysis-2026-01-11.html
- weibo-trends-data-2026-01-11.json (optional)

Limitations and Considerations

API Dependencies:

• Requires valid Weibo API endpoint provided by user
• API rate limits may affect number of trends that can be analyzed
• API response format may vary – adapt parsing as needed

Web Search Constraints:

• Search results quality depends on keyword specificity
• Chinese language content may require specific search strategies
• Information recency is critical for trend analysis

Scoring Subjectivity:

• Despite structured framework, some scoring involves judgment
• Market conditions change rapidly
• Manufacturing feasibility requires domain expertise validation

Dashboard Limitations:

• Static HTML file (not a live web application)
• Requires modern browser for best experience
• Large datasets (>50 products) may impact page performance

Technical Requirements

Tools Available:

• Bash: For API calls using curl
• WebSearch: For researching trending topics (REQUIRED)
• Write: For generating HTML and JSON output files

Dependencies:

• No external libraries required for basic functionality
• Modern web browser for viewing dashboard
• Internet connection for API and web searches

Quality Checklist

Before finalizing output, verify:

• All trending topics have been researched (2 focused searches each)
• Search failures handled gracefully with appropriate fallbacks
• Every product concept includes all required fields
• Scores are calculated correctly and sum to totals
• Data limitations marked clearly (⚠️ indicators where applicable)
• HTML renders correctly with proper UTF-8 encoding
• Chinese characters display properly
• Interactive features (sort, filter, search) work
• Styling differentiates score tiers clearly
• All links and references are functional
• Dashboard is responsive on different screen sizes
• Data accuracy has been verified

Advanced Features (Optional)

If time and context allow, consider adding:

Trend Tracking:

• Compare with previous analyses to identify rising/falling trends
• Track keyword position changes over time
• Identify recurring themes or patterns

Competitive Analysis:

• Check for existing similar products on Taobao/Tmall/JD
• Analyze pricing strategies
• Identify market gaps

Visual Enhancements:

• Charts and graphs for score distributions
• Trend heat maps
• Category breakdowns (pie charts)
• Timeline visualizations

Export Options:

• CSV export for spreadsheet analysis
• PDF generation for presentations
• API-ready JSON for integration with other systems

Version History

• v1.2 (2026-01-17): Error handling & performance optimization
  • Comprehensive error handling for API, web searches, and file generation
  • Optimized web searches from 3-5 to 2 focused searches per topic
  • Improved reliability with graceful fallbacks
  • 33-40% faster processing time
• v1.1 (2026-01-11): API integration with TianAPI
  • Built-in Weibo trending API
  • Updated data parsing for real API format
• v1.0 (2026-01-11): Initial skill creation
  • Core workflow: API fetch → Research → Scoring → Dashboard
  • 100-point scoring system
  • Interactive HTML dashboard with tier-based highlighting

References and Resources

Weibo Trending Data:

• Official Weibo Hot Search: https://s.weibo.com/top/summary
• Alternative APIs may provide different data structures

Product Development Resources:

• Alibaba 1688: For manufacturing partner research
• Taobao/Tmall: For market research and competitive analysis
• Pinduoduo: For trending product categories

Design Inspiration:

• Product Hunt: For creative product naming and positioning
• Xiaohongshu (小红书): For lifestyle product trends
• Douyin (抖音): For viral product concepts

Support and Troubleshooting

Common Issues:

1. API Returns Empty Data:

   • Verify API endpoint is correct and accessible
   • Check API authentication if required
   • Try alternative Weibo trending API sources

2. Web Search Not Finding Relevant Information:

   • Refine search queries to be more specific
   • Try different keyword combinations (Chinese + English)
   • Use site-specific searches (site:weibo.com, site:baidu.com)

3. HTML Dashboard Not Displaying Correctly:

   • Ensure file uses UTF-8 encoding
   • Check for JavaScript errors in browser console
   • Verify all HTML tags are properly closed

4. Scores Seem Inconsistent:

   • Review scoring guidelines in Section 3
   • Ensure all criteria are evaluated objectively
   • Document reasoning for borderline scores

Getting Help:

• Review official Claude Code skills documentation
• Check example skills for similar patterns
• Validate JSON data structure before generating HTML

License: MIT License – Free to use and modify Author: Claude Code Skills Framework Last Updated: 2026-01-17 Version: 1.2