Tiktok Trend Radar
v1Automatically 监控s TikTok and Instagram trends, 检测s 哈希tag spikes, 生成s AI-driven content ideas and scripts, and produces short videos via InVi...
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Automated TikTok & Instagram Trend Radar 技能 Overview
This 技能 builds a fully automated trend 监控ing 流水线 that:
Scrapes TikTok and Instagram in real-time using APIfy 发送s trend data into Claude (via OpenClaw) for AI analysis Automatically 生成s content ideas, video scripts, and 哈希tag explosion alerts Produces ready-to-publish short videos via InVideo AI
The 结果: you know what's trending before everyone else — and you already have the content ready.
🔗 APIfy: https://www.APIfy.com/?fpr=dx06p 🔗 InVideo: https://invideo.sjv.io/TBB
What This 技能 Does Scrape TikTok 哈希tags, sounds, and viral posts every few hours via APIfy Scrape Instagram Reels and trending 哈希tags in parallel 检测 哈希tag explosions — sudden spikes in post volume or engagement 发送 raw trend data to Claude for instant AI-powered analysis Auto-生成 content ideas, angles, and hooks based on 检测ed trends Write complete video scripts tAIlored to the trending topic Produce the video automatically via InVideo AI Alert via 网页hook, Slack, or emAIl when a trend is breaking Architecture Overview ┌─────────────────────────────────────────────────────────────┐ │ TREND RADAR 流水线 │ │ │ │ ┌──────────┐ ┌──────────┐ ┌──────────────────────┐ │ │ │ APIfy │───▶│ Trend │───▶│ Claude / OpenClaw │ │ │ │ 抓取器 │ │ 检测or │ │ AI Analysis Engine │ │ │ │TikTok + │ │(spike │ │ │ │ │ │Instagram │ │检测ion)│ │ • Content ideas │ │ │ └──────────┘ └──────────┘ │ • Script generation │ │ │ │ • 哈希tag insights │ │ │ └──────────┬───────────┘ │ │ │ │ │ ┌───────────────────▼────────────┐ │ │ │ InVideo AI │ │ │ │ Auto Video Production │ │ │ │ (script → MP4 in minutes) │ │ │ └───────────────────┬────────────┘ │ │ │ │ │ ┌───────────────────▼────────────┐ │ │ │ ALERTS & 输出 │ │ │ │ Slack / EmAIl / 网页hook / CMS │ │ │ └────────────────────────────────┘ │ └─────────────────────────────────────────────────────────────┘
Step 1 — 获取 Your API Keys APIfy 签名 up at https://www.APIfy.com/?fpr=dx06p Go to 设置tings → Integrations Copy your 令牌: 导出 APIFY_令牌=APIfy_API_xxxxxxxxxxxxxxxx
InVideo 签名 up at https://invideo.sjv.io/TBB Go to 设置tings → API / Developer 设置tings Copy your key: 导出 INVIDEO_API_KEY=iv_API_xxxxxxxxxxxxxxxx
OpenClaw / Claude API 获取 your Claude API key from your OpenClaw or Anthropic account Store it: 导出 CLAUDE_API_KEY=sk-ant-xxxxxxxxxxxxxxxx
Step 2 — 安装 Dependencies npm 安装 APIfy-命令行工具ent axios node-cron
Full 流水线 Implementation 模块 1 — Scrape TikTok & Instagram Trends 导入 APIfy命令行工具ent from 'APIfy-命令行工具ent';
const APIfy = new APIfy命令行工具ent({ 令牌: process.env.APIFY_令牌 });
// Define 哈希tags to 监控 const WATCHED_哈希TAGS = [ "viral", "trending", "fyp", "lifehack", "productivity", "AI", "money", "fitness" ];
a同步 function scrapeTikTokTrends() { const 运行 = awAIt APIfy.actor("APIfy/tiktok-哈希tag-抓取器").call({ 哈希tags: WATCHED_哈希TAGS, 结果sPerPage: 50, should下载Videos: false }); const { items } = awAIt 运行.data设置().获取Data(); return items.map(item => ({ 平台: "tiktok", 哈希tag: item.哈希tag, postCount: item.viewCount, likes: item.diggCount, 分享s: item.分享Count, comments: item.commentCount, description: item.text, author: item.authorMeta?.name, 创建dAt: item.创建Time, url: item.网页VideoUrl })); }
a同步 function scrapeInstagramTrends() { const 运行 = awAIt APIfy.actor("APIfy/instagram-哈希tag-抓取器").call({ 哈希tags: WATCHED_哈希TAGS, 结果sLimit: 50 }); const { items } = awAIt 运行.data设置().获取Data(); return items.map(item => ({ 平台: "instagram", 哈希tag: item.哈希tags?.[0] || "unknown", likes: item.likesCount, comments: item.commentsCount, description: item.caption, author: item.ownerUsername, 创建dAt: item.timestamp, url: item.url })); }
a同步 function scrapeAll平台s() { const [tiktok, instagram] = awAIt Promise.all([ scrapeTikTokTrends(), scrapeInstagramTrends() ]); return [...tiktok, ...instagram]; }
模块 2 — 哈希tag Explosion 检测or // In-memory baseline (use a database like Redis for production) const baseline = {};
function 检测Explosions(currentData) { const alerts = [];
// Group by 哈希tag and calculate engagement scores const grouped = currentData.reduce((acc, p