hot_topics_selector

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财经热点选题工具

Financial Hot Topic Selection Tool

本 Skill 用于从财经热点中筛选出适合引导投资理财的优质选题。

This Skill is used to filter high-quality topics suitable for guiding investment and financial management from financial hot spots.

核心工作流

Core Workflow

Phase 0: 数据抓取（Python）
   → 获取133个新闻标题
Phase 1: Agent 智能筛选（Markdown 提示词）
   → 筛选出5个选题
Phase 2: 内容抓取（Python）
   → 抓取5篇新闻详细内容
Phase 3: Agent 智能解析（Markdown 提示词）
   → 生成5个完整选题方案

职责分离：

Python 脚本：数据抓取（Phase 0, 2）
Agent：智能筛选和解析（Phase 1, 3）

Phase 0: Data Crawling (Python)
   → Obtain 133 news headlines
Phase 1: Agent Intelligent Screening (Markdown Prompt)
   → Filter out 5 topics
Phase 2: Content Crawling (Python)
   → Crawl detailed content of 5 news articles
Phase 3: Agent Intelligent Parsing (Markdown Prompt)
   → Generate 5 complete topic plans

Separation of Responsibilities:

Python Scripts: Data Crawling (Phase 0, 2)
Agent: Intelligent Screening and Parsing (Phase 1, 3)

Phase 0: 数据抓取

Phase 0: Data Crawling

执行方式：

bash

cd scripts
python3 fetch_hot_topics.py

输出：

/tmp/hot_topics.json

包含内容：

133个新闻标题（5个平台）
微博、百度、今日头条、抖音、财联社

数据格式：

json

{
  "fetch_time": "2026-02-13T19:36:24+08:00",
  "total_items": 133,
  "data": {
    "weibo": { "items": [...], "count": 30 },
    "baidu": { "items": [...], "count": 30 }
  }
}

Execution Method:

bash

cd scripts
python3 fetch_hot_topics.py

Output:

/tmp/hot_topics.json

Included Content:

133 news headlines (from 5 platforms)
Weibo, Baidu, Toutiao, Douyin, Cailianshe

Data Format:

json

{
  "fetch_time": "2026-02-13T19:36:24+08:00",
  "total_items": 133,
  "data": {
    "weibo": { "items": [...], "count": 30 },
    "baidu": { "items": [...], "count": 30 }
  }
}

Phase 1: Agent 智能筛选

Phase 1: Agent Intelligent Screening

Agent 执行提示词：

你是一个财经内容选题专家。请根据以下新闻标题，筛选出5个最适合引导证券开户/基金投资的选题。

Agent Execution Prompt:

You are a financial content topic selection expert. Please filter out 5 topics most suitable for guiding securities account opening/fund investment based on the following news headlines.

标题列表

Headline List

{从 /tmp/hot_topics.json 读取的133个标题}

{133 headlines read from /tmp/hot_topics.json}

筛选标准（投资关联性为核心）

Screening Criteria (Investment Relevance as Core)

最高优先级（90-100分）

Highest Priority (90-100 points)

可直接关联投资产品：

赚钱故事 → AI基金/科技股票/券商产品
投资案例 → 黄金ETF/资产配置
理财话题 → 基金定投/证券开户

示例：

"AI月入200万" → 可推荐AI基金（95分）
"黄金赚196万" → 可推荐黄金ETF（92分）

Can directly link to investment products:

Money-making stories → AI funds/tech stocks/brokerage products
Investment cases → Gold ETF/asset allocation
Financial management topics → Fund fixed-investment/securities account opening

Examples:

"AI earns 2 million yuan per month" → Can recommend AI funds (95 points)
"Gold earns 1.96 million yuan" → Can recommend Gold ETF (92 points)

高优先级（80-89分）

High Priority (80-89 points)

可关联理财规划：

薪资话题 → 工资收入vs投资收入
储蓄话题 → 存钱vs投资
消费话题 → 理财规划

示例：

"年终奖1.8亿" → 可推荐基金定投（85分）

Can link to financial planning:

Salary topics → Wage income vs investment income
Savings topics → Saving money vs investment
Consumption topics → Financial planning

Example:

"Year-end bonus of 180 million yuan" → Can recommend fund fixed-investment (85 points)

中优先级（60-79分）

Medium Priority (60-79 points)

勉强可关联：

教育话题 → 教育基金
养老话题 → 养老金投资

示例：

"衡水中学变了" → 可关联教育基金（70分）

Barely can link:

Education topics → Education funds
Pension topics → Pension investment

Example:

"Hengshui High School has changed" → Can link to education funds (70 points)

不选择（<60分）

Not Selected (<60 points)

无法关联投资：

纯娱乐八卦
纯社会新闻
与财经无关的话题

Cannot link to investment:

Pure entertainment gossip
Pure social news
Topics unrelated to finance

输出格式（JSON）

Output Format (JSON)

json

{
  "selected_indices": [1, 3, 5, 7, 9],
  "reasons": {
    "1": "✅ 可直接关联：AI赚钱 → AI基金投资。投资关联度95分，大众关注度高",
    "3": "✅ 可直接关联：黄金案例 → 黄金ETF。投资关联度92分，数据冲击强"
  },
  "investment_angles": {
    "1": "可以推荐：AI主题基金、科技股票、券商AI产品",
    "3": "可以推荐：黄金ETF、券商黄金产品、资产配置服务"
  },
  "investment_relevance_score": {
    "1": 95,
    "3": 92
  }
}

严格要求：

固定选择5个标题（不多不少）
每个标题投资关联度 ≥80分
说明具体的投资产品推荐方向
优先选择可直接关联产品的选题（≥90分）

json

{
  "selected_indices": [1, 3, 5, 7, 9],
  "reasons": {
    "1": "✅ Can directly link: AI money-making → AI fund investment. Investment relevance 95 points, high public attention",
    "3": "✅ Can directly link: Gold case → Gold ETF. Investment relevance 92 points, strong data impact"
  },
  "investment_angles": {
    "1": "Can recommend: AI-themed funds, tech stocks, brokerage AI products",
    "3": "Can recommend: Gold ETF, brokerage gold products, asset allocation services"
  },
  "investment_relevance_score": {
    "1": 95,
    "3": 92
  }
}

Strict Requirements:

Fixed selection of 5 headlines (no more, no less)
Each headline has an investment relevance score ≥80 points
Specify the recommended investment product directions
Prioritize topics that can directly link to products (≥90 points)

Phase 2: 内容抓取

Phase 2: Content Crawling

执行方式：

bash

cd scripts
python3 fetch_news_content.py \
  --input /tmp/hot_topics.json \
  --indices 1,3,5,7,9 \
  --output /tmp/news_content.json

输入：Phase 1 输出的5个选题索引

输出：

/tmp/news_content.json

包含内容：

5篇新闻的完整内容
标题、URL、平台、正文、关键词

数据格式：

json

{
  "fetch_time": "2026-02-13T21:00:00+08:00",
  "total_articles": 5,
  "articles": [
    {
      "index": 1,
      "title": "杭州大哥开1人公司靠AI月入200万",
      "url": "https://...",
      "platform": "微博",
      "content": "完整新闻内容...",
      "keywords": ["AI", "创业", "月入200万"]
    }
  ]
}

Execution Method:

bash

cd scripts
python3 fetch_news_content.py \
  --input /tmp/hot_topics.json \
  --indices 1,3,5,7,9 \
  --output /tmp/news_content.json

Input: 5 topic indices output from Phase 1

Output:

/tmp/news_content.json

Included Content:

Complete content of 5 news articles
Headline, URL, platform, body text, keywords

Data Format:

json

{
  "fetch_time": "2026-02-13T21:00:00+08:00",
  "total_articles": 5,
  "articles": [
    {
      "index": 1,
      "title": "Hangzhou guy runs a 1-person company and earns 2 million yuan per month with AI",
      "url": "https://...",
      "platform": "Weibo",
      "content": "Complete news content...",
      "keywords": ["AI", "entrepreneurship", "earn 2 million per month"]
    }
  ]
}

Phase 3: Agent 智能解析

Phase 3: Agent Intelligent Parsing

Agent 执行提示词：

你是一个财经内容策划专家。请根据以下5篇新闻内容，为每篇新闻生成完整的选题方案。

Agent Execution Prompt:

You are a financial content planning expert. Please generate a complete topic plan for each news article based on the following 5 news contents.

新闻列表

News List

{从 /tmp/news_content.json 读取的5篇新闻}

{5 news articles read from /tmp/news_content.json}

解析要求

Parsing Requirements

1. 新闻内容概要

1. News Content Summary

提取核心信息（100-150字）
保留关键数据和案例
突出与投资相关的信息

Extract core information (100-150 words)
Retain key data and cases
Highlight investment-related information

2. 选题理由

2. Topic Selection Reasons

说明投资关联度（80-100分）
分析大众关注度
预测传播潜力

Explain investment relevance (80-100 points)
Analyze public attention
Predict viral potential

3. 引导策略

3. Guidance Strategy

切入点：如何从新闻话题切入
转折点：如何自然转向投资
产品推荐：具体推荐哪些投资产品
话术示例：2-3句引导话术

示例引导策略：

切入点：AI创业月入200万，引发"我也能吗"的思考
转折点：普通人不会技术，但可以通过投资分享红利
产品推荐：AI主题基金、科技ETF、券商AI产品
话术示例：
  "想参与AI红利？不需要会技术，投资AI基金就能分一杯羹"
  "开户买AI基金，普通人也能享受AI发展的红利"

Entry Point: How to start from the news topic
Turning Point: How to naturally shift to investment
Product Recommendation: Specific investment products to recommend
Script Examples: 2-3 guiding scripts

Example Guidance Strategy:

Entry Point: AI entrepreneurship earns 2 million per month, triggering the thought "Can I do it too?"
Turning Point: Ordinary people don't have the skills, but can share the dividends through investment
Product Recommendation: AI-themed funds, tech ETFs, brokerage AI products
Script Examples:
  "Want to participate in AI dividends? No need to have technical skills, investing in AI funds allows you to get a share"
  "Open an account to buy AI funds, ordinary people can also enjoy the dividends of AI development"

4. 原始链接

4. Original Link

保留完整的新闻URL
方便后续查阅和引用

Retain the complete news URL
Facilitate subsequent review and citation

输出格式（JSON）

Output Format (JSON)

json

{
  "topic_plans": [
    {
      "index": 1,
      "title": "杭州大哥开1人公司靠AI月入200万",
      "summary": "杭州一创业者通过AI工具运营1人公司，月收入达200万。主要业务是...",
      "selection_reason": {
        "investment_relevance": 95,
        "mass_attention": "高（AI+赚钱话题）",
        "viral_potential": "极强（月入200万数据冲击）"
      },
      "guidance_strategy": {
        "entry_point": "AI创业月入200万，引发'我也能吗'的思考",
        "turning_point": "普通人不会技术，但可以通过投资分享AI红利",
        "product_recommendation": "AI主题基金、科技ETF、券商AI产品",
        "script_examples": [
          "想参与AI红利？投资AI基金就能分一杯羹",
          "开户买AI基金，普通人也能享受AI发展红利"
        ]
      },
      "source_url": "https://..."
    }
  ]
}

严格要求：

每个选题都要有完整的4个部分
引导策略要具体、可操作
产品推荐要与券商/基金相关
话术要自然、不生硬

json

{
  "topic_plans": [
    {
      "index": 1,
      "title": "Hangzhou guy runs a 1-person company and earns 2 million yuan per month with AI",
      "summary": "A Hangzhou entrepreneur operates a 1-person company through AI tools, with a monthly income of 2 million yuan. The main business is...",
      "selection_reason": {
        "investment_relevance": 95,
        "mass_attention": "High (AI + money-making topic)",
        "viral_potential": "Extremely strong (data impact of 2 million yuan monthly income)"
      },
      "guidance_strategy": {
        "entry_point": "AI entrepreneurship earns 2 million per month, triggering the thought 'Can I do it too?'",
        "turning_point": "Ordinary people don't have the skills, but can share AI dividends through investment",
        "product_recommendation": "AI-themed funds, tech ETFs, brokerage AI products",
        "script_examples": [
          "Want to participate in AI dividends? Investing in AI funds allows you to get a share",
          "Open an account to buy AI funds, ordinary people can also enjoy the dividends of AI development"
        ]
      },
      "source_url": "https://..."
    }
  ]
}

Strict Requirements:

Each topic plan must have all 4 sections
Guidance strategy must be specific and operable
Product recommendations must be related to brokerages/funds
Scripts must be natural and not forced

使用示例

Usage Example

完整流程

Complete Workflow

bash

undefined

bash

undefined

Step 1: 数据抓取

Step 1: Data Crawling

python3 scripts/fetch_hot_topics.py

Step 2: Agent 智能筛选

Step 2: Agent Intelligent Screening

Agent 读取本文件 Phase 1 提示词并执行

Agent reads the Phase 1 prompt in this file and executes it

Step 3: 内容抓取

Step 3: Content Crawling

python3 scripts/fetch_news_content.py
--input /tmp/hot_topics.json
--indices 1,3,5,7,9

Step 4: Agent 智能解析

Step 4: Agent Intelligent Parsing

Agent 读取本文件 Phase 3 提示词并执行

Agent reads the Phase 3 prompt in this file and executes it


**总耗时**：约15分钟

---


**Total Time Consumption**: Approximately 15 minutes

---

脚本说明

Script Explanation

scripts/fetch_hot_topics.py

功能：调用 TrendRadar API，抓取5个平台的热点新闻标题

输出：133个新闻标题（JSON）

Function: Calls the TrendRadar API to crawl hot news headlines from 5 platforms

Output: 133 news headlines (JSON)

scripts/fetch_news_content.py

功能：根据选题索引，抓取新闻详细内容

输入：选题索引（如 1,3,5,7,9）

输出：5篇新闻完整内容（JSON）

Function: Crawls detailed news content based on topic indices

Input: Topic indices (e.g., 1,3,5,7,9)

Output: Complete content of 5 news articles (JSON)

参考资料

Reference Materials

references/选题方法论.md

references/Topic Selection Methodology.md

包含财经新媒体大V的选题方法论，包括：

5大核心方法论（痛点驱动、情绪共鸣、数据冲击、故事表达、实用导向）
选题公式（数字+冲突+结果、痛点+解决方案等）
评估标准（传播性40%、相关性30%、实用性20%、合规性10%）

Agent 可根据需要参考此文件优化选题策略。

Includes topic selection methodologies from top financial new media influencers, including:

5 core methodologies (pain point-driven, emotional resonance, data impact, story expression, practical orientation)
Topic formulas (number + conflict + result, pain point + solution, etc.)
Evaluation criteria (virality 40%, relevance 30%, practicality 20%, compliance 10%)

Agent can refer to this file to optimize topic selection strategies as needed.

注意事项

Notes

投资关联性为核心：每个选题都必须可以自然转向证券开户或基金投资
固定输出5个选题：不多不少，确保质量
投资关联度 ≥80分：低于80分的选题会被排除
Python 负责数据：Agent 不需要执行数据抓取
Agent 负责智能：筛选和解析由 Agent 完成

Investment relevance is core: Each topic must be able to naturally shift to securities account opening or fund investment
Fixed output of 5 topics: No more, no less, ensure quality
Investment relevance ≥80 points: Topics with scores below 80 will be excluded
Python is responsible for data: Agent does not need to perform data crawling
Agent is responsible for intelligence: Screening and parsing are completed by Agent