
Apify Influencer Brand Collabs
- 109 installs
- 239 repo stars
- Updated June 29, 2026
- apify/awesome-skills
apify-influencer-brand-collabs is a Claude skill that chains Apify Instagram and brand-collaboration actors against Meta's Ad Library to surface branded-content partnerships between brands and creators.
About
This skill surfaces Instagram branded-content partnerships by chaining Apify Actors against Meta's Ad Library. A developer uses it to see who collabs with a brand, which brands a creator has done paid posts for, or to audit an influencer's sponsorship history. It detects direction (brand vs creator) empirically and can optionally enrich results with engagement metrics and partner profiles.
- Chains four Apify Actors against Meta's Ad Library to surface Instagram branded-content partnerships
- Works both directions: brand to creators or creator to brands, detecting direction from the data
- Optional enrichment adds engagement metrics and partner profile data
Apify Influencer Brand Collabs by the numbers
- 109 all-time installs (skills.sh)
- Ranked #430 of 853 Sales & Marketing skills by installs in the Skillselion catalog
- Data as of Aug 4, 2026 (Skillselion catalog sync)
apify-influencer-brand-collabs capabilities & compatibility
Requires Apify MCP tools and an Apify account; enrichment toggles add cost and time per run.
- Capabilities
- influencer discovery · web scraping · social listening
- Use cases
- marketing · research · web scraping
- Runs
- Runs locally
- Pricing
- Bring your own API key
What apify-influencer-brand-collabs says it does
Surface Instagram branded-content partnerships by chaining four Apify Actors against Meta's Ad Library.
Works in either direction — brand → creators or creator → brands — and detects direction from the data, so don't ask the user to declare it.
npx skills add https://github.com/apify/awesome-skills --skill apify-influencer-brand-collabsAdd your badge
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| Installs | 109 |
|---|---|
| repo stars | ★ 239 |
| Last updated | June 29, 2026 |
| Repository | apify/awesome-skills ↗ |
What it does
Discover and audit Instagram brand-creator paid partnerships via Meta's Ad Library.
Who is it for?
Auditing an account's branded-content history or building a brand's influencer roster.
Skip if: Organic mentions or tags, TikTok or YouTube collabs, or generic competitor ads.
When should I use this skill?
The user asks who collabs with a brand, what brands a creator has sponsored posts for, or to audit an influencer's brand deals.
What you get
Headline collab counts, unique partners, engagement, top collabs, and per-partner cards.
- Collab counts, partner list, engagement metrics, per-partner cards
By the numbers
- 4 Apify Actors chained
- default 90-day lookback window
- Top 5 collabs by engagement
Files
Influencer–Brand Collaborations
Surface Instagram branded-content partnerships by chaining four Apify Actors against Meta's Ad Library. Distilled from the production influencer-brand-collabs mini-tool.
When to use
- "Who has Nike paid to promote them this quarter?"
- "What brands does @bellahadid do sponsored posts for?"
- Auditing an account's branded-content history
- Building a competitor's influencer roster
Don't use for: organic mentions or tags (use a hashtag/mentions scraper), TikTok or YouTube collabs (different platforms), generic competitor ads (query Meta Ad Library directly).
Inputs to gather
1. Instagram handle or URL — @adidas or https://www.instagram.com/adidas/ 2. Lookback window — days; default 90 3. Enrichment toggles (each adds cost + time):
- Content insights — likes, comments, views per collab
- Profile enrichment — followers, bio, verified status of the other side
Direction (brand vs creator) is detected empirically. Do not ask.
The pipeline
| # | Actor | Purpose | Required |
|---|---|---|---|
| 1 | apify/instagram-profile-scraper | Resolve the target's Facebook fbid | ✓ |
| 2 | apify/brand-collaboration-scraper | Pull branded-content posts from Meta's Ad Library | ✓ |
| 3 | apify/instagram-post-scraper + apify/instagram-reel-scraper | Engagement metrics | optional |
| 4 | apify/instagram-profile-scraper (again) | Enrich the result-side partners | optional |
Call each via mcp__claude_ai_Apify__call-actor. Use mcp__claude_ai_Apify__fetch-actor-details first if you've never run one of these and want the exact input schema.
Step 1 — Resolve the target
// actor: apify/instagram-profile-scraper
{ "usernames": ["adidas"] }Grab fbid from the first item. No `fbid` → can't query Ad Library → stop and tell the user. Most common cause: private account.
Step 2 — Build the Meta Ad Library URL
https://www.facebook.com/ads/library/branded_content/?id={fbid}&query={username}&target=instagram&start_date={YYYY-MM-DD}&end_date={YYYY-MM-DD}Date range = the lookback window (default 90 days, ending today).
Step 3 — Fetch collaborations
// actor: apify/brand-collaboration-scraper
{ "startUrls": ["<ad library url>"], "resultsLimit": 10 }Schema is fixed: every item has creator (always the influencer side) and brandPartners[0] (always the brand side). Do not try to infer direction from these fields.
Step 4 — Detect direction empirically
Count how often the target username appears on each side of the results:
- target appears more on
creatorside → target is the influencer; results are the brands - target appears more on
brandPartnersside → target is the brand; results are the creators
⚠️ Do not useisBusinessAccountto infer this. It's unreliable — e.g.@fifaworldcupis a
business account but appears as the creator of its own branded content.
Step 5 — (optional) Content metrics
Split collab URLs by type:
/reel/...→ reel scraper/p/...or/tv/...→ post scraper
// actor: apify/instagram-post-scraper
{ "username": ["<post urls>"], "resultsLimit": 1, "dataDetailLevel": "basicData" }
// actor: apify/instagram-reel-scraper
{ "username": ["<reel urls>"], "resultsLimit": 1 }Match back to collabs via shortcode in the URL: /(p|reel|tv)/([A-Za-z0-9_-]+).
Engagement formula: likesCount + commentsCount + (videoViewCount ?? videoPlayCount ?? 0).
Run the two scrapers in parallel — they're independent.
Step 6 — (optional) Enrich the result side
Collect unique usernames from the side that is not the target. Then:
// actor: apify/instagram-profile-scraper
{ "usernames": [<unique result-side usernames>] }Only enrich the side the user actually cares about. The input handle is already known.
What to present
After aggregation, surface:
- Headline counts: total collabs, unique partners, total engagement (if metrics enriched)
- Top 5 collabs by engagement — only meaningful when content insights were toggled on
- Content-type mix: Post vs Reel; Reels usually dominate engagement
- Weekly timeline across the date range — spikes reveal campaign launches
- Per-partner card (when profiles enriched): handle, full name, followers, verified, category,
collabs in this run, avg engagement
For who-questions, the partner list alone is enough. Metrics only matter for which-was-best-questions.
URL parsing
Strip Instagram's _u/ and _n/ deep-link prefixes before extracting the handle:
/instagram\.com\/(?:_u\/|_n\/)?([A-Za-z0-9_.]+)/iThese slugs are not usernames — skip them: explore, reels, stories, direct, accounts, about, p, reel, tv, tags, locations, _u, _n.
Pitfalls
- Target is private → profile scraper returns no
fbid. Bail early with a clear message. - No results → try in order: widen the date range, double-check the handle (strip
_u/),
confirm the account actually runs branded content. Meta only indexes ads they've classified as branded content.
- Engagement is all zeros → user skipped content enrichment. Offer to re-run with it on.
- Direction looks wrong in the output → re-check the empirical count. Don't trust
isBusinessAccount.
- Brand collabs with no metrics are still answer-shaped for who questions — don't gate the
whole flow on enrichment.
Cost & time
Full 4-actor run: ~3–5 minutes, a few cents of Apify compute. Order of magnitude:
| Enrichment | Actors run | Approx time |
|---|---|---|
| None | 2 | 1–2 min |
| + Content | 3–4 | 2–4 min |
| + Profiles | +1 | +30–60 s |
If the user just needs a partner list, skip both toggles.
Reference implementation
Production route this skill was distilled from: mini-tools-main/src/app/api/tools/influencer-brand-collabs/route.ts — full transformation logic, error handling, and slimmed display shapes for each scraper's output.
influencer-brand-collabs (skill)
A Claude Code skill that teaches an agent how to surface Instagram brand–creator partnerships by chaining four Apify Actors against Meta's public Ad Library.
Distilled from the production mini-tool at mini-tools-main/src/app/api/tools/influencer-brand-collabs/route.ts.
What it covers
- Resolving a target's Facebook
fbidfrom their Instagram handle - Building the Meta Ad Library "branded content" URL
- Running
apify/brand-collaboration-scraperagainst that URL - Optional content enrichment (likes / comments / views) via the
Instagram post and reel scrapers
- Optional profile enrichment (followers, bio, verified) on the
result side — never the input
- Detecting direction (brand-to-creators vs creator-to-brands)
empirically from the data, not from isBusinessAccount
- The URL-parsing edge cases (
_u//_n/deep links, reserved
paths), engagement formula, and weekly timeline aggregation
When it activates
Natural-language asks like:
- "Who collabs with Nike on Instagram?"
- "What brands has @bellahadid done sponsored posts for?"
- "Show me Adidas's recent influencer roster"
- "Audit @cristiano's branded-content history"
See the description: block in SKILL.md for the full trigger list.
Requirements
Apify MCP tools must be available in the session:
mcp__claude_ai_Apify__call-actormcp__claude_ai_Apify__fetch-actor-detailsmcp__claude_ai_Apify__get-actor-output
Plus an Apify account with credits for: apify/instagram-profile-scraper, apify/brand-collaboration-scraper, apify/instagram-post-scraper, apify/instagram-reel-scraper.
Install
Pick one:
# Global — available in every Claude Code session
ln -s "$PWD" ~/.claude/skills/influencer-brand-collabs
# Project-local — only loaded in that repo
ln -s "$PWD" /path/to/repo/.claude/skills/influencer-brand-collabsUse a symlink (not a copy) so future edits to SKILL.md here propagate.
Files
| File | Purpose |
|---|---|
SKILL.md | The skill itself — loaded into the agent's context when triggered |
README.md | This file — human-facing overview |
Related skills
FAQ
Does it work brand-to-creator or creator-to-brand?
Both. It detects the direction empirically from the data by counting which side the target username appears on, so you do not declare it.
What does it require?
It requires Apify MCP tools and calls each actor via mcp__claude_ai_Apify__call-actor.