tiktok-trend-radar

// This skill builds a **fully automated trend monitoring pipeline** that:

$ git log --oneline --stat

stars:1,933

forks:367

updated:March 4, 2026

SKILL.mdreadonly

Automated TikTok & Instagram Trend Radar Skill

Overview

This skill builds a fully automated trend monitoring pipeline that:

Scrapes TikTok and Instagram in real-time using Apify
Sends trend data into Claude (via OpenClaw) for AI analysis
Automatically generates content ideas, video scripts, and hashtag explosion alerts
Produces ready-to-publish short videos via InVideo AI

The result: 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 Skill Does

Scrape TikTok hashtags, sounds, and viral posts every few hours via Apify
Scrape Instagram Reels and trending hashtags in parallel
Detect hashtag explosions — sudden spikes in post volume or engagement
Send raw trend data to Claude for instant AI-powered analysis
Auto-generate content ideas, angles, and hooks based on detected trends
Write complete video scripts tailored to the trending topic
Produce the video automatically via InVideo AI
Alert via webhook, Slack, or email when a trend is breaking

Architecture Overview

┌─────────────────────────────────────────────────────────────┐
│                    TREND RADAR PIPELINE                     │
│                                                             │
│  ┌──────────┐    ┌──────────┐    ┌──────────────────────┐  │
│  │  Apify   │───▶│  Trend   │───▶│   Claude / OpenClaw  │  │
│  │ Scraper  │    │ Detector │    │   AI Analysis Engine │  │
│  │TikTok +  │    │(spike    │    │                      │  │
│  │Instagram │    │detection)│    │ • Content ideas      │  │
│  └──────────┘    └──────────┘    │ • Script generation  │  │
│                                  │ • Hashtag insights   │  │
│                                  └──────────┬───────────┘  │
│                                             │               │
│                         ┌───────────────────▼────────────┐ │
│                         │       InVideo AI               │ │
│                         │   Auto Video Production        │ │
│                         │   (script → MP4 in minutes)    │ │
│                         └───────────────────┬────────────┘ │
│                                             │               │
│                         ┌───────────────────▼────────────┐ │
│                         │         ALERTS & OUTPUT        │ │
│                         │  Slack / Email / Webhook / CMS │ │
│                         └────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────┘

Step 1 — Get Your API Keys

Apify

Sign up at https://www.apify.com/?fpr=dx06p
Go to Settings → Integrations

Copy your token:

export APIFY_TOKEN=apify_api_xxxxxxxxxxxxxxxx

InVideo

Sign up at https://invideo.sjv.io/TBB
Go to Settings → API / Developer Settings

Copy your key:

export INVIDEO_API_KEY=iv_api_xxxxxxxxxxxxxxxx

OpenClaw / Claude API

Get your Claude API key from your OpenClaw or Anthropic account

Store it:

export CLAUDE_API_KEY=sk-ant-xxxxxxxxxxxxxxxx

Step 2 — Install Dependencies

npm install apify-client axios node-cron

Full Pipeline Implementation

Module 1 — Scrape TikTok & Instagram Trends

import ApifyClient from 'apify-client';

const apify = new ApifyClient({ token: process.env.APIFY_TOKEN });

// Define hashtags to monitor
const WATCHED_HASHTAGS = [
  "viral", "trending", "fyp", "lifehack",
  "productivity", "ai", "money", "fitness"
];

async function scrapeTikTokTrends() {
  const run = await apify.actor("apify/tiktok-hashtag-scraper").call({
    hashtags: WATCHED_HASHTAGS,
    resultsPerPage: 50,
    shouldDownloadVideos: false
  });
  const { items } = await run.dataset().getData();
  return items.map(item => ({
    platform: "tiktok",
    hashtag: item.hashtag,
    postCount: item.viewCount,
    likes: item.diggCount,
    shares: item.shareCount,
    comments: item.commentCount,
    description: item.text,
    author: item.authorMeta?.name,
    createdAt: item.createTime,
    url: item.webVideoUrl
  }));
}

async function scrapeInstagramTrends() {
  const run = await apify.actor("apify/instagram-hashtag-scraper").call({
    hashtags: WATCHED_HASHTAGS,
    resultsLimit: 50
  });
  const { items } = await run.dataset().getData();
  return items.map(item => ({
    platform: "instagram",
    hashtag: item.hashtags?.[0] || "unknown",
    likes: item.likesCount,
    comments: item.commentsCount,
    description: item.caption,
    author: item.ownerUsername,
    createdAt: item.timestamp,
    url: item.url
  }));
}

async function scrapeAllPlatforms() {
  const [tiktok, instagram] = await Promise.all([
    scrapeTikTokTrends(),
    scrapeInstagramTrends()
  ]);
  return [...tiktok, ...instagram];
}

Module 2 — Hashtag Explosion Detector

// In-memory baseline (use a database like Redis for production)
const baseline = {};

function detectExplosions(currentData) {
  const alerts = [];

  // Group by hashtag and calculate engagement scores
  const grouped = currentData.reduce((acc, post) => {
    if (!acc[post.hashtag]) acc[post.hashtag] = { posts: 0, totalLikes: 0, platforms: new Set() };
    acc[post.hashtag].posts++;
    acc[post.hashtag].totalLikes += post.likes || 0;
    acc[post.hashtag].platforms.add(post.platform);
    return acc;
  }, {});

  for (const [hashtag, stats] of Object.entries(grouped)) {
    const prev = baseline[hashtag] || { posts: 0, totalLikes: 0 };
    const growthRate = prev.posts > 0
      ? ((stats.posts - prev.posts) / prev.posts) * 100
      : 100;

    // Alert if posts grew more than 40% since last check
    if (growthRate > 40) {
      alerts.push({
        hashtag,
        growthRate: Math.round(growthRate),
        currentPosts: stats.posts,
        previousPosts: prev.posts,
        totalLikes: stats.totalLikes,
        platforms: [...stats.platforms],
        detectedAt: new Date().toISOString(),
        severity: growthRate > 100 ? "EXPLOSIVE" : "RISING"
      });
    }

    // Update baseline
    baseline[hashtag] = stats;
  }

  return alerts.sort((a, b) => b.growthRate - a.growthRate);
}

Module 3 — AI Analysis with Claude (OpenClaw)

import axios from 'axios';

async function analyzeWithClaude(trendData, explosionAlerts) {
  const prompt = `
You are a viral content strategist. Analyze these trending social media data and provide actionable output.

## TRENDING DATA (last scrape)
${JSON.stringify(trendData.slice(0, 20), null, 2)}

## EXPLOSION ALERTS
${JSON.stringify(explosionAlerts, null, 2)}

Respond ONLY in this exact JSON format, no preamble:
{
  "topTrends": [
    {
      "hashtag": "#example",
      "whyItsTrending": "brief explanation",
      "targetAudience": "who this appeals to",
      "contentAngle": "unique angle to take on this trend"
    }
  ],
  "contentIdeas": [
    {
      "title": "video title idea",
      "hashtag": "#hashtag",
      "hook": "first 3 seconds script",
      "format": "tutorial | reaction | storytime | list | pov",
      "estimatedViralPotential": "high | medium | low",
      "reasoning": "why this would perform well"
    }
  ],
  "urgentAlerts": [
    {
      "hashtag": "#hashtag",
      "message": "alert message",
      "recommendedAction": "what to do right now",
      "windowOfOpportunity": "estimated hours before trend peaks"
    }
  ],
  "bestTimeToPost": "recommendation based on trend timing"
}
`;

  const response = await axios.post(
    'https://api.anthropic.com/v1/messages',
    {
      model: "claude-opus-4-5",
      max_tokens: 2000,
      messages: [{ role: "user", content: prompt }]
    },
    {
      headers: {
        'x-api-key': process.env.CLAUDE_API_KEY,
        'anthropic-version': '2023-06-01',
        'Content-Type': 'application/json'
      }
    }
  );

  const raw = response.data.content[0].text;
  const clean = raw.replace(/```json|```/g, '').trim();
  return JSON.parse(clean);
}

Module 4 — Auto Script Generation

async function generateVideoScript(contentIdea, trendContext) {
  const prompt = `
Write a complete short-form video script for this content idea.

CONTENT IDEA: ${JSON.stringify(contentIdea)}
TREND CONTEXT: ${trendContext}

Respond ONLY in this JSON format:
{
  "title": "video title",
  "duration": "estimated seconds",
  "hook": "opening line — first 3 seconds",
  "fullScript": "complete word-for-word script",
  "captions": ["caption 1", "caption 2", "..."],
  "hashtags": ["#tag1", "#tag2", "#tag3"],
  "cta": "call to action at the end",
  "thumbnailIdea": "description of ideal thumbnail"
}

Rules:
- Hook must create curiosity or shock in under 4 seconds
- Script must be 120–180 words for a 30–45 second video
- Conversational, energetic tone
- End with a strong CTA (follow, comment, share)
`;

  const response = await axios.post(
    'https://api.anthropic.com/v1/messages',
    {
      model: "claude-opus-4-5",
      max_tokens: 1000,
      messages: [{ role: "user", content: prompt }]
    },
    {
      headers: {
        'x-api-key': process.env.CLAUDE_API_KEY,
        'anthropic-version': '2023-06-01',
        'Content-Type': 'application/json'
      }
    }
  );

  const raw = response.data.content[0].text;
  return JSON.parse(raw.replace(/```json|```/g, '').trim());
}

Module 5 — Auto Video Production with InVideo

const invideo = axios.create({
  baseURL: 'https://api.invideo.io/v1',
  headers: { Authorization: `Bearer ${process.env.INVIDEO_API_KEY}` }
});

async function produceVideo(script) {
  // Start generation
  const { data } = await invideo.post('/videos/generate', {
    script: script.fullScript,
    format: "9:16",
    duration: "short",
    style: "dynamic",
    voiceover: { enabled: true, voice: "en-US-female-1", speed: 1.1 },
    captions: { enabled: true, style: "bold-bottom", highlight: true },
    music: { enabled: true, mood: "upbeat", volume: 0.25 },
    cta: { enabled: true, text: script.cta, position: "bottom" }
  });

  const videoId = data.videoId;

  // Poll until ready
  let exportUrl = null;
  while (!exportUrl) {
    await new Promise(r => setTimeout(r, 6000));
    const status = await invideo.get(`/videos/${videoId}/status`);
    if (status.data.state === "completed") exportUrl = status.data.exportUrl;
    if (status.data.state === "failed") throw new Error("Video generation failed");
    console.log(`  Video progress: ${status.data.progress}%`);
  }

  return { videoId, exportUrl, script };
}

Module 6 — Alerts & Notifications

async function sendAlert(alert, analysis) {
  const payload = {
    text: `🚨 *TREND ALERT: ${alert.hashtag}* — ${alert.severity}`,
    blocks: [
      {
        type: "section",
        text: {
          type: "mrkdwn",
          text: `*📈 ${alert.hashtag}* grew *${alert.growthRate}%* in the last check\n` +
                `Platforms: ${alert.platforms.join(', ')}\n` +
                `Window: ${analysis.urgentAlerts?.[0]?.windowOfOpportunity || 'Act now'}`
        }
      },
      {
        type: "section",
        text: {
          type: "mrkdwn",
          text: `*💡 Recommended action:*\n${analysis.urgentAlerts?.[0]?.recommendedAction || 'Create content immediately'}`
        }
      }
    ]
  };

  // Send to Slack webhook
  if (process.env.SLACK_WEBHOOK_URL) {
    await axios.post(process.env.SLACK_WEBHOOK_URL, payload);
  }

  // Or send to any custom webhook
  if (process.env.ALERT_WEBHOOK_URL) {
    await axios.post(process.env.ALERT_WEBHOOK_URL, {
      type: "trend_explosion",
      alert,
      analysis,
      timestamp: new Date().toISOString()
    });
  }
}

Main Orchestrator — Full Pipeline

import cron from 'node-cron';

async function runTrendRadar() {
  console.log(`\n🔍 Trend Radar scan started at ${new Date().toISOString()}`);

  try {
    // 1 — Scrape all platforms
    console.log("  [1/5] Scraping TikTok & Instagram...");
    const trendData = await scrapeAllPlatforms();
    console.log(`  ✅ ${trendData.length} posts collected`);

    // 2 — Detect explosions
    console.log("  [2/5] Detecting explosions...");
    const alerts = detectExplosions(trendData);
    console.log(`  ✅ ${alerts.length} alerts detected`);

    // 3 — AI analysis
    console.log("  [3/5] Analyzing with Claude...");
    const analysis = await analyzeWithClaude(trendData, alerts);
    console.log(`  ✅ ${analysis.contentIdeas?.length} content ideas generated`);

    // 4 — Auto-generate scripts for top 2 ideas
    console.log("  [4/5] Generating video scripts...");
    const topIdeas = analysis.contentIdeas?.slice(0, 2) || [];
    const scripts = await Promise.all(
      topIdeas.map(idea => generateVideoScript(idea, JSON.stringify(analysis.topTrends)))
    );
    console.log(`  ✅ ${scripts.length} scripts written`);

    // 5 — Produce videos
    console.log("  [5/5] Producing videos with InVideo...");
    const videos = await Promise.all(scripts.map(produceVideo));
    console.log(`  ✅ ${videos.length} videos ready`);

    // 6 — Send alerts
    if (alerts.length > 0) {
      await sendAlert(alerts[0], analysis);
      console.log("  ✅ Alerts sent");
    }

    // Final report
    return {
      scannedAt: new Date().toISOString(),
      postsAnalyzed: trendData.length,
      explosionAlerts: alerts,
      contentIdeas: analysis.contentIdeas,
      videos: videos.map(v => ({ title: v.script.title, url: v.exportUrl })),
      bestTimeToPost: analysis.bestTimeToPost
    };

  } catch (err) {
    console.error("Radar error:", err.message);
    throw err;
  }
}

// Schedule: run every 4 hours automatically
cron.schedule('0 */4 * * *', () => {
  runTrendRadar().then(report => {
    console.log("\n📊 RADAR REPORT:", JSON.stringify(report, null, 2));
  });
});

// Also run immediately on startup
runTrendRadar();

Environment Variables

# .env
APIFY_TOKEN=apify_api_xxxxxxxxxxxxxxxx
INVIDEO_API_KEY=iv_api_xxxxxxxxxxxxxxxx
CLAUDE_API_KEY=sk-ant-xxxxxxxxxxxxxxxx

# Optional alerts
SLACK_WEBHOOK_URL=https://hooks.slack.com/services/xxx/xxx/xxx
ALERT_WEBHOOK_URL=https://your-app.com/webhooks/trends

Normalized Radar Report Schema

{
  "scannedAt": "2025-02-25T10:00:00Z",
  "postsAnalyzed": 400,
  "explosionAlerts": [
    {
      "hashtag": "#aitools",
      "severity": "EXPLOSIVE",
      "growthRate": 187,
      "platforms": ["tiktok", "instagram"],
      "windowOfOpportunity": "4–8 hours"
    }
  ],
  "contentIdeas": [
    {
      "title": "5 AI tools that replaced my entire team",
      "hashtag": "#aitools",
      "hook": "I fired my team. Here's what I replaced them with.",
      "format": "list",
      "estimatedViralPotential": "high"
    }
  ],
  "videos": [
    {
      "title": "5 AI tools that replaced my entire team",
      "url": "https://cdn.invideo.io/exports/iv_xxx.mp4"
    }
  ],
  "bestTimeToPost": "Post within the next 3 hours while the trend is rising"
}

Best Practices

Run the radar every 2–4 hours — trends peak fast and fade within 24–48h
Monitor 8–15 hashtags max per run to stay within Apify free tier
Always produce content within the rising phase — never wait for the peak
Use node-cron for local scheduling or Apify Schedules for cloud automation
Store baseline data in Redis or a database for accurate spike detection in production
Pipe the video URLs directly into your social media scheduler (Buffer, Later, etc.)

Requirements

Apify account → https://www.apify.com/?fpr=dx06p
InVideo account → https://invideo.sjv.io/TBB
Claude / OpenClaw API key
Node.js 18+
Optional: Slack workspace for real-time alerts
Optional: Social media scheduler (Buffer, Later) for auto-publishing