公众号爆款选题雷达

v1.0.0

聚合多平台热点,智能评估选题潜力,提供爆款切入角度、竞品分析及差异化内容方案,助力公众号内容创作。

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for sxzxlj/wechat-topic-radar.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "公众号爆款选题雷达" (sxzxlj/wechat-topic-radar) from ClawHub.
Skill page: https://clawhub.ai/sxzxlj/wechat-topic-radar
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install wechat-topic-radar

ClawHub CLI

Package manager switcher

npx clawhub@latest install wechat-topic-radar
Security Scan
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Benign
high confidence
Purpose & Capability
Name/description (hot-topic aggregator for public platforms) aligns with required code and network activity. The code implements multiple collectors and an analysis/reporting pipeline consistent with the stated purpose; requested environment/configuration is limited to a local YAML file and Python deps.
Instruction Scope
SKILL.md instructions only direct the agent to run the provided Python scripts and to read the config file. The runtime steps (scan/quick/analyze/compare) map directly to functions implemented in the code; there are no instructions to read unrelated system files, access credentials, or transmit local files to unknown endpoints.
Install Mechanism
No install spec (instruction-only metadata) — lowest installer risk. However the package includes Python scripts and a requirements.txt; running it will install standard Python packages from PyPI (requests, numpy, plotly, jieba, pyyaml). Nothing in the install is unusual or obfuscated.
Credentials
The skill does not request environment variables or secrets (good). It makes many outbound network requests to third‑party aggregator endpoints (e.g., http://api.xcvts.cn, https://tenapi.cn, https://weibo.com, sogou weixin search). These calls are proportional to the declared function but do expose queries and the host's IP to external services; api.xcvts.cn is contacted over plain HTTP in the code (privacy concern).
Persistence & Privilege
always:false and no code that modifies other skills or global agent configuration. The skill writes report files to ./data/reports (local only) and does not request elevated or persistent platform privileges.
Assessment
This skill appears coherent with its description: it scrapes/queries public trending sources, ranks topics, and writes HTML/JSON reports. Before installing/running: 1) Review and accept that the tool will make outbound HTTP(S) requests to third‑party aggregator services (api.xcvts.cn, tenapi.cn, sogou, weibo, etc.), which will see your IP and any query strings. 2) Note one endpoint is called via plain HTTP (api.xcvts.cn) — consider changing to HTTPS or using a trusted proxy if privacy is a concern. 3) The generated HTML includes a Plotly CDN script (loads remote JS when you open reports) — if you need air‑gapped usage, host Plotly locally or set include_plotlyjs appropriately. 4) Check that scraping/collection complies with the target platforms' terms of service. 5) If you require higher assurance, review the collector code paths that call external APIs and optionally pin/replace endpoints with ones you trust.

Like a lobster shell, security has layers — review code before you run it.

latestvk9754d9g1a5jk7te0b5h7cyzp183vych
125downloads
1stars
1versions
Updated 4w ago
v1.0.0
MIT-0

Skill: 公众号爆款选题雷达


version: "1.0.0" name: "wechat-topic-radar" display_name: "公众号爆款选题雷达" description: | 全网热点聚合分析工具,智能发现公众号爆款选题。 采集知乎、微博、小红书、公众号等多平台热点, 通过综合热度算法识别高潜力选题, 提供切入角度建议、竞品分析和内容差异化方案。 author: "liujian" tags: ["内容创作", "公众号", "热点分析", "选题工具", "数据分析"]


功能特性

🔥 多平台热点采集 (20+平台)

  • 国内热点: 百度热搜、微博热搜、知乎热榜、今日头条、抖音热搜、B站热搜/日榜
  • 技术社区: 掘金、CSDN、GitHub、V2EX、HackerNews
  • 新闻资讯: 网易新闻、少数派、爱范儿
  • 自动故障转移: 多源备份,确保数据稳定采集

🌡️ 综合热度算法

基于5大维度评估选题价值:

  • 平台热度 (20%):原始热度数据
  • 互动热度 (25%):点赞/评论/分享数据
  • 趋势热度 (20%):新鲜度和增长趋势
  • 内容质量 (15%):标题质量和完整性
  • 爆款潜力 (20%):情绪价值和传播潜力

🎯 智能选题建议

  • 切入角度推荐:5种角度类型(情感共鸣/实用干货/观点评论/数据洞察/故事叙事)
  • 标题优化建议:基于爆款标题公式生成
  • 文章结构规划:提供完整的内容大纲
  • 情绪定位分析:匹配目标读者情绪

📊 竞品分析

  • 相似话题识别:发现同主题竞品内容
  • 角度分布分析:避免同质化竞争
  • 差异化策略:提供独特的切入建议

📈 可视化报告

  • HTML交互报告:美观的可视化分析
  • 热度趋势图表:TOP10热度排行、雷达图分析
  • 关键词云图:热点词汇提取
  • JSON数据导出:便于二次分析

使用方法

完整扫描

# 执行完整的热点扫描和分析
python scripts/radar_main.py scan

# 指定平台和数量
python scripts/radar_main.py scan -p zhihu weibo -l 30

快速扫描

# 快速获取热点概览
python scripts/radar_main.py quick

# 按关键词筛选
python scripts/radar_main.py quick -k 职场

单选题分析

# 分析单个选题
python scripts/radar_main.py analyze "为什么年轻人都不结婚了?"

多选题对比

# 对比多个选题
python scripts/radar_main.py compare "标题1" "标题2" "标题3"

Python API调用

from scripts.radar_main import WechatTopicRadar

# 初始化雷达
radar = WechatTopicRadar('config/config.yaml')

# 执行完整扫描
result = radar.scan()

# 获取TOP10热门选题
top_topics = result['scores'][:10]
for score in top_topics:
    print(f"{score.topic.title} - 热度: {score.total_score}")

# 快速扫描
quick_result = radar.quick_scan(keyword="职场")

# 分析单个选题
analysis = radar.analyze_topic("你的选题标题")
print(analysis.angles[0]['suggested_title'])

输出示例

控制台输出

============================================================
🔥 公众号爆款选题雷达 - 开始扫描
============================================================
📱 扫描平台: zhihu, weibo, xiaohongshu, wechat
📊 每平台采集: 50 条
⏰ 开始时间: 2024-01-15 09:30:00
------------------------------------------------------------

📡 Step 1: 多平台数据采集...
   ✅ 共采集 156 条热点数据

🌡️  Step 2: 综合热度计算...
   ✅ 计算完成,89 条达到热度阈值

📈 Step 3: 热点趋势分析...
   ✅ 提取 45 个关键词
   ✅ 识别 23 个上升话题

🔍 Step 4: 选题深度分析...
   ✅ 完成 10 个选题深度分析

📄 Step 5: 生成分析报告...
   ✅ HTML报告: ./data/reports/topic_radar_report_20240115_093015.html
   ✅ JSON数据: ./data/topic_data_20240115_093015.json

============================================================
✨ 扫描完成!
============================================================
🏆 TOP 5 热门选题:
   1. [知乎] 2024年最赚钱的10个行业... (热度: 92.5)
   2. [微博] 为什么年轻人都不结婚了?... (热度: 89.3)
   ...

分析报告内容

  • 📊 数据概览:采集统计、平台分布
  • 📈 可视化图表:热度排行、雷达图、关键词图
  • 精选推荐:当下最热/高潜力/被低估选题
  • 🔍 深度分析:TOP5选题的切入角度、差异化建议

配置说明

配置文件位置:config/config.yaml

# 扫描平台配置
data_collection:
  platforms:
    - zhihu
    - weibo
    - xiaohongshu
    - wechat
  limit_per_platform: 50

# 热度算法权重
heat_algorithm:
  weights:
    platform: 0.20
    interaction: 0.25
    trend: 0.20
    quality: 0.15
    potential: 0.20

# 报告配置
report:
  output_dir: ./data/reports

项目结构

wechat-topic-radar/
├── SKILL.md                    # Skill定义文件
├── README.md                   # 项目说明
├── requirements.txt            # Python依赖
├── config/
│   └── config.yaml            # 配置文件
├── scripts/
│   ├── radar_main.py          # 主控模块
│   ├── data_collector.py      # 数据采集
│   ├── heat_algorithm.py      # 热度算法
│   ├── topic_analyzer.py      # 选题分析
│   └── report_generator.py    # 报告生成
├── data/                      # 数据存储
│   └── reports/              # 报告输出
└── assets/                    # 静态资源

技术栈

  • Python 3.8+
  • requests:网络数据采集
  • jieba:中文分词和关键词提取
  • numpy:数值计算
  • plotly:交互式可视化
  • pyyaml:配置管理

数据来源

平台类型数据源
百度热搜综合热点小尘API
微博热搜社交媒体小尘API
知乎热榜问答社区小尘API
今日头条新闻资讯小尘API
抖音热搜短视频小尘API
B站热搜/日榜视频社区小尘API
掘金技术社区小尘API
CSDN技术社区小尘API
GitHub开源社区小尘API
网易新闻新闻资讯小尘API
少数派科技媒体小尘API
爱范儿科技媒体小尘API
V2EX技术社区官方API
HackerNews技术社区官方API

注意事项

  1. 数据准确性:网络数据采集可能存在延迟或波动
  2. 合规使用:请遵守各平台的数据使用规范
  3. 热点时效:热点内容具有时效性,建议及时跟进
  4. 人工判断:算法建议仅供参考,最终选题需结合人工判断

更新计划

  • 接入更多数据源(抖音、B站、今日头条等)
  • AI智能标题生成
  • 历史热点趋势分析
  • 个性化推荐算法
  • 定时自动推送报告

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