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-affiliate-marketers-on-social-mediaPrima 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 Affiliate Marketers On Social Media
Executes finding affiliate marketers on social media using apidojo scrapers. Part of the apidojo intelligence skills library.
Prerequisites
APIFY_TOKENenvironment variable set- Optional: Apify MCP server installed
Inputs
| Parameter | Type | Required | Default | Notes |
|---|---|---|---|---|
startUrls | array | ✅ | [] | Instagram URLs — profiles, hashtags, locations, audio pages, reels |
until | string | Optional | — | Scrape posts until this date (YYYY-MM-DD) |
maxItems | number | Optional | Unlimited | Maximum posts to return |
customMapFunction | string | Optional | — | JavaScript function to transform each output object |
Workflow
Progress:
- [ ] Step 1: Define parameters
- [ ] Step 2: Run instagram-scraper
- [ ] Step 3: Filter and classify results
- [ ] Step 4: Score by quality and relevance
- [ ] Step 5: Deliver outputStep 2: Run the Actor
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~instagram-scraper" \
--input '{"param": "value"}'
# Save as CSV
node scripts/run_actor.js \
--actor "apidojo~instagram-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.csv --format csv
# Save as JSON
node scripts/run_actor.js \
--actor "apidojo~instagram-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~instagram-scraper"
Input:
{
"searchTerms": ["#affiliate[niche]", "#[niche]code", "use code [NICHE]", "#commissioned"],
"maxItems": 100
}REST API fallback:
bash
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~instagram-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"searchTerms": ["#affiliate[niche]", "#[niche]code", "use code [NICHE]", "#commissioned"], "maxItems": 100}'Wait for SUCCEEDED. Fetch dataset:
bash
curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"Step 3: Classify Results
classification: ACTIVE_AFFILIATE (> 3 promo posts in 30 days) | OCCASIONAL_PROMOTER (1-3 posts) | AFFILIATE_AUDIENCE (uses affiliate content but doesn't produce it)Step 4: Score Each Result
score = affiliate_signal = (promo_code_post_count / total_posts * 100) * (avg_views_on_affiliate_posts / 1000)Step 5: Edge Cases
- Distinguish genuine affiliates from brand employees — employees promote brand without code; affiliates promote with a trackable code or unique URL
Additional fallbacks:
- < 20 results: Broaden search terms; remove secondary filters
- No results: Verify the search terms are correct; try alternate phrasings
- Data quality issues: Remove entries with missing key fields; note count in output
Output Format
# Finding Affiliate Marketers On Social Media
Results: [N] | Date: [DATE]
| # | [Key Field] | [Metric 1] | [Metric 2] | [Classification] | [Score] |
|---|------------|-----------|-----------|-----------------|---------|
| 1 | [value] | [value] | [value] | [type] | [0.XX] |
## Summary
Top result: [description]
Key finding: [insight]Troubleshooting
Too few results: Broaden the primary search term; remove restrictive filters. Low quality results: Apply minimum score threshold (≥ 0.50) to filter noise. Actor fails to run: Verify API key; check actor status at apify.com/apidojo.
