Agent Skills

discovering-brand-ambassadors-across-platforms

Discovers potential brand ambassadors across Instagram TikTok and Twitter using apidojo's scrapers. Triggers when the user asks to: find brand ambassadors across multiple platforms, discover cross-platform creators for brand ambassador programs, find creators who would make good ambassadors across social media, identify multi-platform influencers for ambassador recruitment, find creators with audiences on multiple platforms for a brand partnership, build a multi-platform brand ambassador pipelin

Install

npx skills add https://github.com/apidojo-io/apidojo-skills --skill discovering-brand-ambassadors-across-platforms
SKILL.md

Discovering Brand Ambassadors Across Platforms

Executes discovering brand ambassadors across platforms using apidojo scrapers. Part of the apidojo intelligence skills library.

Prerequisites

  • APIFY_TOKEN environment 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 output

Step 2: Run the Actor

Recommended — run_actor.js (handles waiting, output, and file saving automatically):

# 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 json

APIFY_TOKEN must be set in environment or .env file.

If Apify MCP is available:

Tool: apify:run-actor
Actor: "apidojo~instagram-scraper"
Input:
{
  "searchTerms": ["#[brand]", "#[brand]ambassador", "#[brand]fam"],
  "maxItems": 100
}

REST API fallback:

curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~instagram-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerms": ["#[brand]", "#[brand]ambassador", "#[brand]fam"], "maxItems": 100}'

Wait for SUCCEEDED. Fetch dataset:

curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"

Step 3: Classify Results

classification: MEGA (combined reach > 500K) | MACRO (100K-500K) | MICRO (10K-100K) | NANO (1K-10K)

Step 4: Score Each Result

score = combined_reach = IG_followers + TikTok_followers * 0.8 + Twitter_followers * 0.5  # platform-weighted

Step 5: Edge Cases

  • The same creator on multiple platforms often has very different audience sizes per platform — list per-platform stats separately, don't just sum

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

# Discovering Brand Ambassadors Across Platforms
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.

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