weibo-trends-analyzer

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Chinese

Weibo Trends Analyzer - 微博热搜创意产品分析

微博热搜创意产品分析工具(Weibo Trends Analyzer)

Overview

概述

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
该技能可帮助你从微博热搜话题中挖掘创意产品机会。它会获取实时热搜数据,开展全面的背景调研,评估产品开发潜力,并通过交互式仪表盘呈现分析结果。
关键词:微博(Weibo)、热搜话题、热搜、产品构想、创意产品、市场分析、社交媒体趋势、中国市场

Workflow

工作流程

1. Fetch Weibo Trending Topics

1. 获取微博热搜话题

When the user requests Weibo trending analysis, fetch the current hot search list:
bash
curl -s "https://apis.tianapi.com/weibohot/index?key=4dfdf794141101d7bb8ece0294dbbc02"
API Response Processing:
The API returns data in this format:
json
{
  "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
当用户请求微博热搜分析时,获取当前热搜列表:
bash
curl -s "https://apis.tianapi.com/weibohot/index?key=4dfdf794141101d7bb8ece0294dbbc02"
API响应处理:
API返回数据格式如下:
json
{
  "code": 200,
  "msg": "success",
  "result": {
    "list": [
      {
        "hotword": "trending keyword",
        "hotwordnum": "1234567",
        "hottag": "新/热/荐"
      }
    ]
  }
}
字段映射:
  • hotword
    → 热搜关键词
  • hotwordnum
    → 热度值,可能包含分类前缀(如"综艺 587870")
  • hottag
    → 标签:"新"、"热"、"荐"或为空
  • 排名位置 → 从数组索引推断(从1开始计数)
解析说明:
  1. 检查
    code == 200
    以确认请求成功
  2. 提取
    result.list
    数组
  3. 对列表中的每个条目:
    • 排名 = 数组索引 + 1
    • 关键词 =
      hotword
    • 热度值 = 从
      hotwordnum
      中提取数值(若有分类前缀则移除)
    • 标签 =
      hottag
    • 分类 = 从
      hotwordnum
      的前缀中提取(如"综艺"、"剧集"、"盛典"、"演出")
  4. 限制分析前10-15个条目以控制处理时长
错误处理:
若API获取失败,遵循以下备选策略:
  1. API返回错误码(code ≠ 200):
    • 记录API响应中的错误信息
    • 告知用户:"API返回错误:{msg}。是否使用模拟数据替代?"
    • 建议检查API密钥或配额限制
    • 若用户同意,使用
      .claude/skills/weibo-trends-analyzer/weibo-mock-data.json
  2. 网络/连接失败:
    • 告知用户:"无法连接到API,可能存在网络问题。"
    • 提供使用模拟数据的选项:
      .claude/skills/weibo-trends-analyzer/weibo-mock-data.json
    • 建议检查网络连接
  3. 无效JSON响应:
    • 记录接收到的响应内容
    • 告知用户:"API返回的数据格式无效"
    • 建议检查API端点是否变更
    • 若有可用模拟数据则切换使用
  4. 数据为空或格式错误:
    • result.list
      为空或缺失
    • 告知用户:"API响应中未找到热搜话题"
    • 使用模拟数据作为备选

2. Deep Research Each Trending Topic

2. 深度调研每个热搜话题

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"
针对每个热搜话题,执行2次定向网络搜索以收集关键背景信息:
搜索策略(每个话题2次搜索):
搜索1:背景与上下文 将社交媒体讨论与新闻背景整合为一个搜索查询:
  • 搜索查询示例:
    • "{keyword} 微博 新闻背景"
    • "{keyword} 热搜原因 讨论"
    • "{keyword} latest news 用户看法"
目标:了解该趋势的内容及走红原因
搜索2:用户洞察与市场潜力 聚焦消费者视角与产品机会:
  • 搜索查询示例:
    • "{keyword} 用户需求 产品"
    • "{keyword} 消费者痛点"
    • "{keyword} 产品创意 市场"
目标:识别用户需求、痛点及产品开发机会
需提取的信息: 从两次搜索中收集:
  • ✅ 社交媒体讨论量与舆情倾向
  • ✅ 新闻背景与事件上下文
  • ✅ 目标人群与受众规模
  • ✅ 用户痛点与未被满足的需求
  • ✅ 现有产品或市场空白
  • ✅ 文化/社会意义
网络搜索错误处理:
  1. 搜索无结果:
    • 记录:"未找到{keyword}的搜索结果"
    • 将调研标记为"可用数据有限"
    • 仅使用关键词本身及通用市场知识继续分析
    • 在仪表盘中标注:"⚠️ 背景研究受限"
  2. 搜索超时或失败:
    • 使用简化查询(仅关键词,无附加术语)重试一次
    • 若重试失败,标记为"搜索不可用"
    • 使用已有数据继续分析
    • 在产品分析中注明限制
  3. 搜索结果不相关:
    • 若结果与热搜话题上下文不符:
    • 尝试使用不同关键词的备选查询
    • 借助通用行业知识进行分析
    • 记录:"基于通用市场分析"
  4. 部分搜索成功(2次中1次成功):
    • 使用可用的搜索数据继续
    • 注明缺失的维度(背景或用户洞察)
    • 对缺失信息做出保守估计
    • 在仪表盘中标记:"⚠️ 部分数据"

3. AI-Powered Product Ideation & Scoring

3. AI驱动的产品创意与评分

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
针对每个热搜话题,采用以下评分框架分析并生成创意产品构想:
评分体系(总分:100分)
  1. 产品可发展度:40分
    • 市场规模与可扩展性(15分)
    • 技术可行性(10分)
    • 趋势持续性(10分)
    • 竞争格局(5分)
  2. 有趣度:20分
    • 创意独特性(10分)
    • 情感吸引力(5分)
    • 传播/病毒潜力(5分)
  3. 生活有用度:20分
    • 日常生活融入度(10分)
    • 问题解决能力(5分)
    • 目标受众规模(5分)
  4. 小规模生产容易度:20分
    • 制造复杂度(10分)
    • 材料可获取性(5分)
    • 小批量成本效率(5分)
产品概念要求:
针对每个趋势,生成1-3个创意产品概念,包含:
  • 市场赛道:所属产品类别(如家居装饰、时尚配饰、文具、科技小物、生活方式产品、玩具等)
  • 产品名称: catchy、易记的名称
  • 目标受众:特定人群(年龄、兴趣、收入水平、生活方式)
  • 批量生产特点:
    • 生产方式(如3D打印、注塑成型、丝网印刷、激光切割)
    • 材料要求
    • 最小起订量(MOQ)可行性
    • 交付周期预估
    • 成本结构(不同批量的单位成本)
  • 详细描述:产品与热搜话题的关联
  • 总分:四个维度得分之和
  • 评分分析:各得分项的简要理由
评分指南:
  • 客观、现实
  • 考虑中国市场环境
  • 结合当前制造能力
  • 考量趋势周期时机

4. Generate Interactive HTML Dashboard

4. 生成交互式HTML仪表盘

Create a comprehensive, visually appealing HTML dashboard with the following structure:
Dashboard Components:
A. Header Section
html
- 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:
html
<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
css
/* 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
html
- Disclaimer about trend volatility
- Recommendation to conduct further market research
- Generation metadata (API source, analysis timestamp)
- Skill version information
创建全面、视觉美观的HTML仪表盘,结构如下:
仪表盘组件:
A. 头部区域
html
- 标题: "微博热搜创意产品分析报告 - Weibo Trends Product Analysis"
- 生成时间戳
- 分析的热搜总数
- 汇总统计数据(平均得分、热门类别等)
B. 亮点区域 - 高分产品 按得分层级展示产品:
  • 🏆 优秀 - 得分≥80:
    • 金色/高端风格突出展示
    • 放大卡片,包含详细分解
    • 推荐行动:"优先开发推荐"
  • ⭐ 良好 - 得分60-79:
    • 标准卡片布局,带高亮边框
    • 推荐行动:"可考虑开发"
  • 📋 其他产品 - 得分<60:
    • 紧凑列表视图
    • 推荐行动:"观望或需优化"
C. 产品卡片
每个产品卡片应包含:
html
<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. 仪表盘样式要求
css
/* 配色方案 */
- 优秀产品(≥80分):金色/琥珀色主题(#FFD700, #FFA500- 良好产品(60-79分):蓝色/青色主题(#4A90E2, #50C8E8- 其他产品(<60分):灰色/中性色主题(#95A5A6, #BDC3C7
/* 设计指南 */
- 响应式布局(网格或弹性布局)
- 简洁现代的美学风格
- 清晰的视觉层级
- 易读的排版(支持中英文)
- 交互式悬停效果
- 可排序/筛选选项
- 进度条可视化得分
- 徽章系统用于快速识别
E. 交互功能
包含以下JavaScript功能:
  • 按得分排序(从高到低、从低到高)
  • 按得分层级筛选(优秀/良好/其他)
  • 按市场类别筛选
  • 关键词搜索功能
  • 可展开/折叠的详细区域
  • 导出为PDF选项(附加功能)
F. 底部区域
html
- 关于趋势波动性的免责声明
- 建议开展进一步市场调研
- 生成元数据(API来源、分析时间戳)
- 技能版本信息

5. File Output

5. 文件输出

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
生成以下文件:
  1. weibo-trends-analysis-{YYYY-MM-DD}.html
    :完整的交互式仪表盘
  2. weibo-trends-data-{YYYY-MM-DD}.json
    :用于后续处理的原始结构化数据(可选)
文件生成错误处理:
  1. 文件写入权限被拒绝:
    • 尝试使用带时间戳的备选文件名:
      weibo-trends-analysis-{YYYY-MM-DD-HHmmss}.html
    • 若仍失败,告知用户:"无法写入文件,请检查目录权限。"
    • 请求用户提供输出路径
  2. HTML生成错误:
    • 若模板渲染失败,创建包含基础表格布局的简化HTML版本
    • 确保至少包含产品名称、得分及基本描述
    • 记录错误详情以便排查
  3. 输出前数据验证:
    • 验证至少生成了1个产品概念
    • 检查所有得分在有效范围内(0-40、0-20等)
    • 确保必填字段存在(产品名称、得分、描述)
    • 若验证失败,告知用户哪些话题存在问题
  4. 大文件处理:
    • 若分析超过20个话题,提醒用户文件体积较大
    • 考虑生成分页HTML或摘要+详细内容的结构
    • 确保大数据集的浏览器兼容性

Best Practices

最佳实践

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
调研质量:
  • 每个热搜话题执行2次定向网络搜索(优化效率)
  • 整合每次搜索中多个来源的信息
  • 验证事实准确性
  • 标注信息时效性
  • 优先考虑搜索结果的质量而非数量
产品创意:
  • 跳出明显关联的局限
  • 考虑中国市场的文化背景与消费者行为
  • 同时评估短期趋势利用与长期产品可行性
  • 创意十足但符合实际
评分客观性:
  • 对所有产品采用一致的评分标准
  • 用具体证据支撑得分
  • 避免对特定产品类别的偏见
  • 结合中国当前的制造实际情况
仪表盘质量:
  • 确保所有中文字符显示正确(UTF-8编码)
  • 在不同屏幕尺寸下测试响应性
  • 验证HTML/CSS/JS语法正确性
  • 为中文文本设置备选字体
  • 确保数据可视化清晰直观

Example Usage Flow

示例使用流程

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

Claude:
1. 从默认API(https://apis.tianapi.com/weibohot/index?key=...)获取热搜数据
   - 若API失败,提供使用模拟数据的选项
2. 解析result.list数组,提取前10-15个热搜话题
3. 针对每个话题:
   - 执行2次定向网络搜索进行背景调研
   - 优雅处理搜索失败,采用备选方案
   - 分析市场潜力与用户需求
   - 生成创意产品概念
   - 计算详细得分
4. 验证所有生成的数据
5. 将所有数据编译为结构化格式
6. 生成交互式HTML仪表盘(若有需要,包含错误标记)
7. 保存输出文件

输出:
- weibo-trends-analysis-2026-01-11.html
- weibo-trends-data-2026-01-11.json(可选)

Limitations and Considerations

限制与注意事项

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
API依赖:
  • 需要用户提供有效的微博API端点
  • API速率限制可能影响可分析的热搜数量
  • API响应格式可能变化,需调整解析逻辑
网络搜索限制:
  • 搜索结果质量取决于关键词的特异性
  • 中文内容可能需要特定的搜索策略
  • 信息时效性对趋势分析至关重要
评分主观性:
  • 尽管采用结构化框架,部分评分仍涉及主观判断
  • 市场条件变化迅速
  • 制造可行性需要领域专业知识验证
仪表盘限制:
  • 静态HTML文件(非实时Web应用)
  • 需要现代浏览器以获得最佳体验
  • 大数据集(>50个产品)可能影响页面性能

Technical Requirements

技术要求

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
可用工具:
  • Bash: 用于通过curl调用API
  • WebSearch: 用于调研热搜话题(必填)
  • Write: 用于生成HTML和JSON输出文件
依赖:
  • 基础功能无需外部库
  • 查看仪表盘需要现代Web浏览器
  • API与网络搜索需要互联网连接

Quality Checklist

质量检查清单

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
在最终输出前,验证:
  • 所有热搜话题均已完成调研(每个话题2次定向搜索)
  • 搜索失败已优雅处理,并采用了适当的备选方案
  • 每个产品概念包含所有必填字段
  • 得分计算正确,且总和无误
  • 数据限制已明确标注(适用处添加⚠️标记)
  • HTML采用UTF-8编码,渲染正确
  • 中文字符显示正常
  • 交互功能(排序、筛选、搜索)可正常工作
  • 样式可清晰区分不同得分层级
  • 所有链接与引用有效
  • 仪表盘在不同屏幕尺寸下具有响应性
  • 数据准确性已验证

Advanced Features (Optional)

高级功能(可选)

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
若时间与场景允许,可考虑添加:
趋势追踪:
  • 与之前的分析结果对比,识别上升/下降趋势
  • 追踪关键词位置随时间的变化
  • 识别重复出现的主题或模式
竞品分析:
  • 检查淘宝/天猫/京东上是否存在类似产品
  • 分析定价策略
  • 识别市场空白
视觉增强:
  • 得分分布图表
  • 趋势热度地图
  • 类别分解(饼图)
  • 时间线可视化
导出选项:
  • CSV导出,用于电子表格分析
  • PDF生成,用于演示
  • 可集成到其他系统的API友好型JSON

Version History

版本历史

  • 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
  • v1.2 (2026-01-17): 错误处理与性能优化
    • 为API、网络搜索和文件生成添加全面的错误处理
    • 将每个话题的网络搜索从3-5次优化为2次定向搜索
    • 通过优雅的备选方案提升可靠性
    • 处理速度提升33-40%
  • v1.1 (2026-01-11): 集成TianAPI
    • 内置微博热搜API
    • 针对真实API格式更新数据解析逻辑
  • v1.0 (2026-01-11): 初始技能创建
    • 核心工作流:API获取 → 调研 → 评分 → 仪表盘
    • 100分制评分体系
    • 基于层级高亮的交互式HTML仪表盘

References and Resources

参考资料

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
微博热搜数据:
产品开发资源:
  • 阿里巴巴1688:用于调研制造合作伙伴
  • 淘宝/天猫:用于市场调研与竞品分析
  • 拼多多:用于了解热门产品类别
设计灵感:
  • Product Hunt:用于创意产品命名与定位
  • 小红书:用于生活方式产品趋势
  • 抖音:用于病毒式产品概念

Support and Troubleshooting

支持与故障排除

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
常见问题:
  1. API返回空数据:
    • 验证API端点正确且可访问
    • 检查是否需要API认证
    • 尝试其他微博热搜API来源
  2. 网络搜索未找到相关信息:
    • 优化搜索查询,使其更具体
    • 尝试不同的关键词组合(中英文)
    • 使用站点特定搜索(site:weibo.com、site:baidu.com)
  3. HTML仪表盘显示异常:
    • 确保文件使用UTF-8编码
    • 检查浏览器控制台中的JavaScript错误
    • 验证所有HTML标签已正确闭合
  4. 得分看起来不一致:
    • 回顾第3节的评分指南
    • 确保所有标准均已客观评估
    • 记录临界得分的理由
获取帮助:
  • 查阅官方Claude Code技能文档
  • 参考类似技能的示例
  • 生成HTML前验证JSON数据结构

许可证: MIT License - 可免费使用与修改 作者: Claude Code Skills Framework 最后更新: 2026-01-17 版本: 1.2