Come usare
- Copia il comando e controlla il pacchetto prima di installarlo nel tuo ambiente agente.
- Controlla strumenti, credenziali e ambienti richiesti nel documento originale.
- Descrivi input e risultato desiderato; confronta l’output con le fonti.
npx skills add https://github.com/apidojo-io/apidojo-skills --skill finding-brand-collaborations-on-tiktokPrima di iniziare
- L’installazione non include abbonamenti, quote API o accesso ai file.
- Stelle e installazioni indicano attività, non un test indipendente di qualità o sicurezza.
Documento Skill originale
Contenuto dal repository con titoli, esempi, codice, tabelle, link e immagini preservati.
Finding Brand Collaborations on TikTok
Maps active brand-creator partnerships in a product category. Identifies which brands are investing in TikTok influencer marketing, which creators they're working with, and the performance benchmarks for sponsored content.
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 sponsored content hashtags for category
- [ ] Step 2: Filter for sponsored signals
- [ ] Step 3: Extract brand and creator pairs
- [ ] Step 4: Analyze collaboration patterns
- [ ] Step 5: Deliver brand-creator mapStep 1: Search Posts
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": ["#ad", "#sponsored", "#[category]partner", "#[category]collab"],
"keywords": ["[BRAND_NAME] sent", "use code", "thanks to [CATEGORY] brand"],
"maxItems": 300
}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": ["#ad", "#sponsored", "#fitnesspartner"],
"maxItems": 300
}'Step 2: Extract Brand-Creator Pairs
From each sponsored post, extract:
brand_name: From caption mention (@[brand],[Brand] sent me,thanks to [Brand])creator_handle:authorMeta.namepost_views:playCountpost_date:createTimecollaboration_type:#gifted(product seeding) vs.#ad/#sponsored(paid)
Step 3: Score Campaign Performance
sponsored_performance = playCount / 1000 (views in thousands)
creator_roi_proxy = playCount / followerCount (view-to-follower ratio for sponsored post)Brand collaboration frequency per creator:
collab_depth = count(posts where same brand appears) / total_posts_in_date_rangeStep 4: Edge Cases
- No #ad hashtag but clearly sponsored: Also scan for
"gifted","c/o","partnership"in caption; TikTok disclosure is inconsistently applied - Brand name ambiguous (e.g. "Nike" in sports context): Verify by checking if creator's bio mentions brand partnership or if post has dedicated product showcase format
- < 20 sponsored posts found: Category may be under-sponsored on TikTok; check if brands are using darker patterns (no disclosure) — widen search to product names alone
Output Format
# TikTok Brand Collaboration Map: [CATEGORY]
Posts analyzed: [N] | Sponsored posts identified: [N] | Unique brands: [N] | Date: [DATE]
## Brands Running Active TikTok Campaigns
| Brand | # Creators Used | # Posts | Avg Views/Post | Collaboration Type |
|-------|----------------|---------|----------------|-------------------|
| [brand] | [N] | [N] | [N] | [Gifted/Paid/Mixed] |
## Creator-Brand Pairs
| Creator | @Handle | Brand | Posts | Avg Views | Collab Type | Est. Reach |
|---------|---------|-------|-------|-----------|-------------|-----------|
| [name] | @[handle] | [brand] | [N] | [N] | [Gifted/Paid] | [N] |
## Benchmark: Sponsored Post Performance in [CATEGORY]
- Median views for sponsored posts: [N]
- Top-performing brand campaign: [brand] — [N] avg views
- Most-used creator tier: [micro/macro/mega]Troubleshooting
Disclosure data sparse: TikTok doesn't always surface #ad in scraped captions. Check for brand mentions in text and product codes. Results outside the category: Refine search by combining #ad with a niche keyword: "#ad #fitness" or "#sponsored #skincare". Can't find competitor campaigns: If competitor avoids disclosure, search for their brand @mention directly in TikTok search.
