Mode d’emploi
- Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
- Consultez le document original pour les outils, identifiants et environnements requis.
- Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/apidojo-io/apidojo-skills --skill discovering-viral-tiktok-content-trendsAvant de commencer
- L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
- Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Document Skill original
Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.
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_TOKENenvironment 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 briefStep 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 jsonAPIFY_TOKENmust be set in environment or.envfile.
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 secondsStep 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) * 0.20Trend 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_viewsto 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.
