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weibo-trends-analyzer微博趋势分析器

Agent Skill

weibo-trends-analyzer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:weibo-trends-analyzer(微博趋势分析器)
来源仓库:https://github.com/yitongcodes/weibo_trends_analyzer_web
仓库路径:skills/weibo-trends-analyzer
安装命令:
npx skills add https://github.com/yitongcodes/weibo_trends_analyzer_web --skill weibo-trends-analyzer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/yitongcodes/weibo_trends_analyzer_web --skill weibo-trends-analyzer

简介

weibo-trends-analyzer 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装并使用。
  • 安装前需确认权限范围、维护状态,注意是否触发联网、命令执行或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

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")

  1. 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

  1. 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

  1. 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

  1. 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"

  1. 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

  1. 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"

  1. 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)

  1. Interest Level (有趣度): 20 points

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

  1. 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)

  1. 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

  1. 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

  1. 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

  1. 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:

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

  1. 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)

  1. 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

  1. 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

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