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discovering-brand-ambassadors-across-platforms — Claude Code skill

Finds prospective brand ambassadors across Instagram, TikTok, and Twitter using Apify scrapers. Calculates combined reach and groups creators into tiers.

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

What discovering-brand-ambassadors-across-platforms does

This skill coordinates Apify scrapers across Instagram, TikTok, and Twitter to locate potential partners. It expects a list of Instagram URLs in startUrls covering profiles, hashtags, locations, audio pages, or reels. Execution runs via scripts/run_actor.js, an Apify MCP tool apify:run-actor, or fallback REST API requests.

Collected profiles are categorized into NANO, MICRO, MACRO, and MEGA tiers based on cross-platform volume. Scoring applies weighted values: full weight for Instagram followers, 0.8 for TikTok, and 0.5 for Twitter. Outputs arrive formatted as a table with audience metrics and assigned ambassador tiers.

Without the APIFY_TOKEN environment variable, the underlying actors cannot run. Per-platform follower numbers should be reviewed separately because identical creators frequently show disparate reach across different networks.

What it helps with

  • identify potential brand ambassadors across multiple social networks
  • calculate platform-weighted combined reach for multi-channel creators
  • segment discovered influencers into ambassador tiers from nano to mega
  • filter low-quality leads using a minimum relevance score

Example prompts for the agent

  • Find prospective brand ambassadors across social platforms using our brand hashtags
  • Discover cross-platform creators from startUrls and classify them into ambassador tiers
  • Evaluate multi-platform influencers who mention our brand and export results to CSV

How to install discovering-brand-ambassadors-across-platforms

1Skills CLI (Vercel)

npx skills add apidojo-io/apidojo-skills --skill discovering-brand-ambassadors-across-platforms -a claude-code

2Manually: put the files in place

~/.claude/skills/discovering-brand-ambassadors-across-platforms/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/discovering-brand-ambassadors-across-platforms/

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

Questions about discovering-brand-ambassadors-across-platforms

How to install discovering-brand-ambassadors-across-platforms in Claude Code?

Run npx skills add apidojo-io/apidojo-skills --skill discovering-brand-ambassadors-across-platforms -a claude-code in your terminal.

What does discovering-brand-ambassadors-across-platforms do?

It scrapes creator data across Instagram, TikTok, and Twitter using Apify actors, computes platform-weighted reach, and categorizes influencers into tiers.

What is required before running the scrapers?

You must set the APIFY_TOKEN environment variable or place it in a .env file. You can also optionally install the Apify MCP server.

Source text

SKILL.md · Apache-2.0
---
name: discovering-brand-ambassadors-across-platforms
description: >
  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 pipeline, or discover creators with authentic brand affinity across channels.
  Returns creator handle per platform, combined reach estimate, brand affinity signals, engagement metrics, and ambassador tier.
  Ideal for brand partnership teams, DTC brands, and ambassador program managers needing multi-channel reach.
license: Apache-2.0
metadata:
  author: apidojo
  version: "1.0"
  apify-actors: apidojo/instagram-scraper, apidojo/tiktok-scraper, apidojo/twitter-user-scraper
---

# 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):**
```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 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:**
```bash
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:
```bash
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.

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

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