apify-ads-intelligence

这段内容是审核时保存的快照。外部来源才是完整且最新的版本。

---
name: apify-ads-intelligence
description: Research, spy on, and analyze ads across Meta (Facebook & Instagram), Google (Ads Transparency Center + paid search results), TikTok (Ads Library + Creative Center), LinkedIn Ad Library, and X (Twitter — promoted tweets, best-effort) using Apify Actors. Use when user asks about competitor ads, ad library research, winning creatives, ad copy analysis, landing page audits from ads, cross-platform ad audits, brand transparency checks, or any task involving paid ad creatives, advertiser data, or ad targeting from public ad libraries.
author: Sameh Jarour
author_url: https://github.com/samehjarour
---

# Ads Intelligence Cluster

Answer natural language questions about ads, ad libraries, and competitor advertising activity by routing to the right Apify Actor and delivering a synthesized answer.

**CLI rules:** Always pass `--user-agent apify-awesome-skills/apify-ads-intelligence`, `--json` (or the relevant `--format` flag on `datasets get-items`), and `2>/dev/null`. The `--user-agent` flag is critical for telemetry — never omit it.

## Note on platform coverage

- **Meta, Google, TikTok, LinkedIn**: real public ad libraries with rich data (creatives, targeting, dates, reach where disclosed).
- **X (Twitter)**: no public ad library exists. Coverage is a **best-effort workaround** that scrapes a brand's tweets and flags items with non-empty `card` field or `source` containing "Ads" as likely promoted. Always include the caveat in synthesis output.

## Note on overlap with `apify-ecommerce`

That skill has an `ads-intelligence` intent that routes to `apify/facebook-ads-scraper` for shallow Meta-ad lookups. This skill is the deep dive across all five platforms. If you only need Meta ads as a side detail of an ecommerce question, stay in `apify-ecommerce`. If ads are the main task, use this skill.

## Prerequisites

(No need to check it upfront)

- Apify CLI v1.5.0+ (`npm install -g apify-cli`)
- `jq` (recommended for response parsing and filtering; `brew install jq` on macOS, `apt install jq` on Linux)
- Authentication via one of:
  - `apify login` (OAuth, opens browser)
  - `APIFY_TOKEN` env variable (e.g. `export APIFY_TOKEN=...` or `.env` file)
  - Token from [Apify Console → Settings → Integrations](https://console.apify.com/settings/integrations)

Verify auth: `apify info --user-agent apify-awesome-skills/apify-ads-intelligence` — should show username and userId.

## Workflow

Copy this checklist and track progress:

```
Task Progress:
- [ ] Step 1: Detect intent and select Actor(s)
- [ ] Step 2: Fetch Actor schema
- [ ] Step 3: Ask user preferences (output format, result count, country)
- [ ] Step 4: Run the Actor (or Actors in parallel for cross-platform-audit) and fetch results
- [ ] Step 5: Synthesize a direct answer (not a data dump)
```

### Step 1: Detect Intent and Select Actor

Classify the user's message into an intent, then pick the right Actor.

**Intent signals:**

| Signals in user message | Intent |
|-------------------------|--------|
| "what ads is X running", "competitor [brand] ads", "[brand] FB/Google/TikTok/LinkedIn/X/Twitter ads", "show ads from [page]", "promoted tweets from [brand]" | `competitor-ads` |
| "ads about [topic]", "find [keyword] ads", "ads for [vertical]", "fitness/fintech/saas ads" | `keyword-ads` |
| "trending ads", "winning ads", "top ads", "best performing", "long-running ads", "creative inspiration" | `top-creatives` |
| "where do these ads go", "landing pages from ads", "click destinations", "ad funnels" | `landing-page-audit` |
| "compare X's ads across platforms", "all ads from [brand]", "cross-platform ad audit" | `cross-platform-audit` |

If multiple intents detected, ask: *"Do you want [intent A] or [intent B]?"*

**Actor routing — always try Primary first, switch to Fallback only if it fails or returns 0 results:**

| Intent | Platform | Primary Actor | Fallback Actor |
|--------|----------|---------------|----------------|
| `competitor