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discovering-viral-tiktok-content-trends — Claude Code skill

This skill finds viral TikTok formats in a chosen niche and breaks down hashtags, reach, engagement, and hooks. Use it when planning content angles.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add apidojo-io/apidojo-skills --skill discovering-viral-tiktok-content-trends -a claude-code
Open on GitHub

What discovering-viral-tiktok-content-trends does

The skill runs apidojo~tiktok-scraper on Apify and gathers posts from keywords, hashtags, or URLs. It filters for strong playCount results, then groups recurring formats, classifies hooks, and scores how practical each trend is to reproduce.

The report covers hashtags, views, likes, comments, hook type, video-length tier, and the trend window. Results can be printed in chat or saved as CSV or JSON with scripts/run_actor.js. The run depends on APIFY_TOKEN being available in the environment or a .env file.

It flags patterns tied to one major creator, shared audio, or a small result set. Format classification uses captions and available metadata, so it does not inspect the video itself.

What it helps with

  • find viral TikTok formats for a niche
  • compare views and engagement across posts
  • break down hooks from popular videos
  • separate creator-led trends from repeatable formats

Example prompts for the agent

  • Find viral TikTok formats for a skincare niche and explain the recurring hooks.
  • Collect posts for these niche hashtags, filter the strongest results by views, and write a trend report.
  • Analyze trending sounds and content structures for this product category, including the trend window.

How to install discovering-viral-tiktok-content-trends

1Skills CLI (Vercel)

npx skills add apidojo-io/apidojo-skills --skill discovering-viral-tiktok-content-trends -a claude-code

2Manually: put the files in place

~/.claude/skills/discovering-viral-tiktok-content-trends/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/discovering-viral-tiktok-content-trends/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about discovering-viral-tiktok-content-trends

How do I install discovering-viral-tiktok-content-trends in Claude Code?

Run npx skills add apidojo-io/apidojo-skills --skill discovering-viral-tiktok-content-trends -a claude-code. The skill file will be at ~/.claude/skills/discovering-viral-tiktok-content-trends/SKILL.md.

What does discovering-viral-tiktok-content-trends do?

It collects TikTok posts through Apify, identifies recurring formats and hooks, and produces a report with post metrics, hashtags, and trend assessment.

What data does the skill use to classify formats?

It relies on captions and available metadata for classification. The video itself is not analyzed.

Source text

SKILL.md · Apache-2.0
---
name: discovering-viral-tiktok-content-trends
description: >
  Discovers viral content trends and trending formats on TikTok using apidojo's TikTok scraper
  on Apify. Triggers when the user asks to: find trending content formats on TikTok, discover
  what is going viral on TikTok in a niche, identify viral TikTok hooks or video styles to
  adapt, research TikTok trends for a product category, find what content formats are performing
  best on TikTok right now, discover trending sounds or concepts in a niche on TikTok, or
  analyze what drives viral TikTok engagement in a specific category.
  Returns trending hashtags, view counts, engagement metrics, content format patterns, and hook analysis.
  Ideal for TikTok content creators, brand social teams, and video content strategists.
license: Apache-2.0
metadata:
  author: apidojo
  version: "1.0"
  apify-actor: apidojo/tiktok-scraper
---

# Discovering Viral TikTok Content Trends

Identifies what's going viral on TikTok in a niche by analyzing high-performing posts. Extracts repeatable content formats, hooks, and structural patterns — the inputs needed to create content that rides existing momentum.

## Prerequisites

- `APIFY_TOKEN` environment variable set
- Optional: Apify MCP server installed

## Inputs

| Parameter | Type | Required | Default | Notes |
|-----------|------|----------|---------|-------|
| `startUrls` | array | Optional | `[]` | TikTok URLs — user profiles, hashtags, music pages, search, locations |
| `keywords` | array | Optional | `[]` | Search keywords/terms to find posts |
| `sortType` | string | Optional | `RELEVANCE` | Sort order for keyword results: `RELEVANCE`, `MOST_LIKED`, `DATE_POSTED` |
| `location` | string | Optional | — | ISO 3166-1 alpha-2 country code for regional filtering (e.g. `US`, `GB`) |
| `maxItems` | number | Optional | Unlimited | Maximum posts to return across the run |
| `includeSearchKeywords` | boolean | Optional | `false` | Add the matched search keyword field to each post |
| `customMapFunction` | string | Optional | — | JavaScript function to transform each output object |

## Workflow

```
Progress:
- [ ] Step 1: Search niche hashtags
- [ ] Step 2: Filter for high-performing posts
- [ ] Step 3: Analyze content formats and hooks
- [ ] Step 4: Score trend viability for replication
- [ ] Step 5: Deliver trend brief
```

### Step 1: Search Hashtags


**Recommended — run_actor.js (handles waiting, output, and file saving automatically):**
```bash
# Quick answer (prints table to chat)
node scripts/run_actor.js \
  --actor "apidojo~tiktok-scraper" \
  --input '{"param": "value"}'

# Save as CSV
node scripts/run_actor.js \
  --actor "apidojo~tiktok-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.csv --format csv

# Save as JSON
node scripts/run_actor.js \
  --actor "apidojo~tiktok-scraper" \
  --input '{"param": "value"}' \
  --output YYYY-MM-DD_results.json --format json
```
> `APIFY_TOKEN` must be set in environment or `.env` file.

**If Apify MCP is available:**
```
Tool: apify:run-actor
Actor: "apidojo~tiktok-scraper"
Input:
{
  "keywords": ["#[niche]", "#[niche]tiktok", "#[niche]foryou"],
  "maxItems": 200
}
```

**REST API fallback:**
```bash
curl -X POST   "https://api.apify.com/v2/acts/apidojo~tiktok-scraper/runs?token=$APIFY_TOKEN"   -H "Content-Type: application/json"   -d '{"keywords": ["#skincaretips", "#skincaretiktok"], "maxItems": 200}'
```

Filter: `playCount >= min_views`

### Step 2: Analyze Content Patterns

From caption and available metadata, classify:

```
hook_type:
  QUESTION = caption starts with or contains "?", "have you", "do you", "did you know"
  LIST = "X things", "here are the", "number [N]"
  BEFORE_AFTER = "I did X for 30 days", "watch the transformation"
  STORY = first-person narrative opener ("I was struggling with...")
  CONTROVERSY = "unpopular opinion", "no one talks about", "this is controversial"
  TUTORIAL = "how to", "step by step", "the only guide you need"

content_length_tier:
  SHORT = video duration < 15 seconds
  MEDIUM = 15-60 seconds
  LONG = > 60 seconds
```

### Step 3: Score Trend Replicability

```
trend_score = (playCount / 1000000, max 1) * 0.30
            + (diggCount / playCount * 100 > 3 ? 1 : ratio/3) * 0.25
            + (commentCount / playCount * 100 > 0.5 ? 1 : ratio/0.5) * 0.25
            + (format_is_replicable: TUTORIAL/LIST/QUESTION = 1, BEFORE_AFTER = 0.8, STORY = 0.6) * 0.20
```

**Trend window:** posts all from the same 7-day period = `TRENDING NOW`; spread over 30 days = `ESTABLISHED FORMAT`

### Step 4: Edge Cases

- **Trend driven by a single mega-creator**: If top 3 posts are from same creator, it's a creator trend not a format trend — flag as `CREATOR_DRIVEN`; harder to replicate without their audience
- **Trend requires specific audio**: Note if posts share the same sound; audio trends are TikTok-specific and may expire quickly
- **Niche too small** (< 50 posts above threshold): Lower `min_views` to 25K; or report the top posts available with a note on data volume
- **International content dominates**: Filter by caption language; use English-language posts if targeting English-speaking audience

## Output Format

```
# TikTok Viral Trend Report: [NICHE]
Period: [DATE_RANGE] | Posts analyzed: [N] | Viral posts (>[MIN_VIEWS] views): [N] | Date: [DATE]

## Top Performing Formats
| Format | # Posts | Avg Views | Avg Like Rate | Best Example |
|--------|---------|-----------|--------------|-------------|
| Tutorial | [N] | [N] | [X%] | @[handle]: "[caption excerpt]" |
| List | [N] | [N] | [X%] | |

## Top Viral Posts
| Creator | Views | Likes | Comments | Hook Type | Caption Preview |
|---------|-------|-------|----------|----------|----------------|

## Hook Patterns Worth Replicating
1. "[Hook structure]" — used in [N] viral posts, avg [N] views
   Example: "[verbatim hook from top post]"

## Trend Window Assessment
- TRENDING NOW (< 7 days): [N] posts in format
- ESTABLISHED FORMAT (7-30 days): [N] posts
- FADING (> 30 days): [N] posts

## Recommended Content Angles for [NICHE]
1. [Format + hook recommendation with rationale]
2. [Format + hook recommendation]
```

## Troubleshooting

**All viral posts are from mega-creators**: Add filter `follower_count < 500K` to surface format trends from creators of all sizes.
**Format analysis is inconsistent**: Caption text is the only metadata available without video analysis; use it as a proxy and note this limitation.
**Trend is already declining**: TikTok trends typically peak and decline within 2-3 weeks; if freshness is low, recommend adapting the format with a new angle rather than copying directly.

© apidojo · Apache-2.0 · apidojo-io/apidojo-skills

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