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:

• Check if code == 200 to confirm success

• Extract the result.list array

• 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")

• Limit analysis to top 10-15 items to manage processing time

Error Handling:

If API fetch fails, follow this fallback strategy:

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

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

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

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:

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"

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

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"

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)

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)

Interest Level (有趣度): 20 points

• Creative uniqueness (10 points)

• Emotional appeal (5 points)

• Share-ability/viral potential (5 points)

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)

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:

• weibo-trends-analysis-{YYYY-MM-DD}.html : Complete interactive dashboard

• weibo-trends-data-{YYYY-MM-DD}.json : Raw structured data for further processing (optional)

Error Handling for File Generation:

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

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

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

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:

API Returns Empty Data:

• Verify API endpoint is correct and accessible

• Check API authentication if required

• Try alternative Weibo trending API sources

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)

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

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