name: trending-ad-hook-spotter description: > Monitor Twitter/X, Reddit, LinkedIn, and Hacker News for trending narratives, viral posts, and hot-button topics in your space. Maps trends to ad hook opportunities with timing urgency scores. Tells you what to run ads about right now while the topic is hot. tags: [ads]
Trending Ad Hook Spotter
Scan social platforms for what's trending in your space right now — viral posts, hot debates, breaking news, memes — and translate each trend into a concrete ad hook you can run while the topic is still hot.
Core principle: The highest-performing ads ride cultural and industry moments. This skill finds those moments before your competitors do and tells you exactly how to capitalize.
When to Use
- "What's trending in our space that we could run ads about?"
- "Find viral hooks for our paid campaigns"
- "What topics are hot in [industry] right now?"
- "I want to ride a trend with a paid campaign"
- "What should we be running ads about this week?"
Prerequisites
- Environment variable:
APIFY_API_TOKEN— required for Reddit scraping (optional if using only web_search + HN API) - Web search access — your AI agent must support
web_searchor equivalent for Twitter/X and LinkedIn lookups - No API key needed for Hacker News (Algolia HN API is free and public)
Phase 0: Intake
- Your product — Name + one-line description
- Industry/category — What space are you in? (e.g., "AI sales tools", "developer infrastructure")
- ICP keywords — 5-10 keywords that define your buyer's world
- Competitor names — So we can spot when they become part of a trend
- Platforms to scan (default: all):
- Twitter/X
- Reddit (specific subreddits if known)
- Hacker News
- Content velocity — How fast can you create ads? (Same-day / 2-3 days / Weekly)
Phase 1: Social Scanning
1A: Twitter/X Trend Scan (web_search)
Use web_search with site:x.com or site:twitter.com to find trending posts — no scraper or credentials needed:
# Industry trending topics
web_search: "<industry keyword> (viral OR trending OR hot take OR thread) site:x.com"
# Competitor mentions (momentum signals)
web_search: "<competitor1> OR <competitor2> (raised OR launched OR shut down OR acquired OR outage) site:x.com"
# Pain/frustration spikes
web_search: "<category> (broken OR frustrating OR tired of OR switched from) site:x.com"
Run 3-5 queries to cover:
- Industry trending topics and hot takes
- Competitor momentum signals (launches, outages, funding)
- Pain/frustration spikes in the category
- Viral threads with high engagement
Score each tweet/thread by engagement velocity (likes + retweets relative to account size and age).
1B: Reddit Trend Scan (Apify)
Use the trudax/reddit-scraper-lite actor to scan relevant subreddits for hot posts:
Browse specific subreddits (for trending/hot posts):
POST https://api.apify.com/v2/acts/trudax~reddit-scraper-lite/runs?token=$APIFY_API_TOKEN
Content-Type: application/json
{
"startUrls": [
{"url": "https://www.reddit.com/r/SUBREDDIT1/hot/"},
{"url": "https://www.reddit.com/r/SUBREDDIT2/hot/"}
],
"maxItems": 30
}
Search by keyword (for specific topics):
POST https://api.apify.com/v2/acts/trudax~reddit-scraper-lite/runs?token=$APIFY_API_TOKEN
Content-Type: application/json
{
"searches": ["<industry keyword> OR <competitor>"],
"maxItems": 30
}
Poll until the run finishes:
GET https://api.apify.com/v2/acts/trudax~reddit-scraper-lite/runs/{RUN_ID}?token=$APIFY_API_TOKEN
When status is SUCCEEDED, fetch results:
GET https://api.apify.com/v2/datasets/{DATASET_ID}/items?token=$APIFY_API_TOKEN
Output fields: Each item has dataType ("post" or "comment"), title (posts only), body, communityName, upVotes, numberOfComments (posts), url, createdAt.
Look for:
- Posts with unusually high upvote/comment ratios
- "What do you use for [X]?" threads (buying intent)
- Complaint threads about incumbents
- "I just switched from X to Y" posts
1C: LinkedIn Trend Scan (web_search)
Use web_search with site:linkedin.com/posts to find high-engagement KOL posts — no scraper or credentials needed:
web_search: "<industry keyword> site:linkedin.com/posts"
web_search: "<competitor_name> site:linkedin.com/posts"
web_search: "<KOL_name> <industry keyword> site:linkedin.com/posts"
web_search: "<trending topic> site:linkedin.com/pulse"
Run queries for:
- 5-10 key opinion leaders (KOLs) in the space — search their names + topic keywords
- Industry-level keyword searches to find viral posts
- Competitor mentions from thought leaders
Identify high-engagement posts on topics relevant to your product category.
1D: Hacker News Scan (Algolia HN API)
Use the free Algolia HN Search API — no API key needed:
Search for relevant stories:
GET https://hn.algolia.com/api/v1/search?query=KEYWORD&tags=story&hitsPerPage=20
Search for recent stories (past 7 days):
GET https://hn.algolia.com/api/v1/search?query=KEYWORD&tags=story&numericFilters=created_at_i>UNIX_TIMESTAMP_7_DAYS_AGO&hitsPerPage=20
Get front page stories (current trending):
GET https://hn.algolia.com/api/v1/search?tags=front_page&hitsPerPage=30
The response includes points, num_comments, title, url, and created_at for each story. Sort by points to find the highest-engagement discussions.
Run queries for:
- Each ICP keyword
- Each competitor name
- The product category
- Check front page for anything tangentially related
Phase 2: Trend Identification & Scoring
Trend Detection Framework
Group collected signals into trends. A "trend" is:
- A topic appearing across 2+ platforms within the past 7 days
- A single post/thread with exceptional engagement (10x+ the norm)
- A breaking event (funding, acquisition, outage, launch) with cascading conversation
Score Each Trend
| Factor | Weight | Description |
|---|---|---|
| Recency | 25% | How fresh? (< 24h = max, > 7 days = low) |
| Velocity | 25% | Is engagement accelerating or decelerating? |
| Cross-platform | 20% | Appearing on multiple platforms? |
| ICP relevance | 20% | Does your target buyer care about this? |
| Product fit | 10% | Can you credibly connect your product to this trend? |
Total score out of 100. Urgency tiers:
- 90-100: Run today — this peaks within 24-48h
- 70-89: Run this week — 3-5 day window
- 50-69: Worth testing — stable trend, less time pressure
- Below 50: Monitor — not actionable yet
Phase 3: Hook Translation
For each trend scoring 50+, generate:
Ad Hook Formula
[Trend reference] + [Your unique angle] + [CTA tied to the moment]
Per Trend, Produce:
- Trend summary — What's happening in 2 sentences
- Why it's an ad opportunity — Connection to your product/ICP
- 3 hook variants:
- Newsjack hook — Reference the trend directly ("Everyone's talking about X. Here's what they're missing...")
- Contrarian hook — Take the opposite stance ("Hot take: [trend] doesn't matter. Here's what does...")
- Practical hook — Offer a solution related to the trend ("[Trend] means you need [your feature] now")
- Recommended format — Static / video / carousel / search ad
- Recommended platform — Where the trend is hottest
- Time window — How long before this trend fades
Phase 4: Output Format
# Trending Ad Hooks — [DATE]
Industry: [category]
Platforms scanned: [list]
Trends identified: [N]
Actionable hooks (score 50+): [N]
---
## Run Today (Score 90+)
### Trend: [Trend Title]
**What's happening:** [2-sentence summary]
**Engagement signal:** [X likes/comments across Y platforms in Z hours]
**Time window:** [Estimated hours/days before this fades]
**Hook 1 (Newsjack):** "[Ad headline]"
> [1-2 sentence body copy]
- Format: [Static/Video/Carousel]
- Platform: [Twitter/Meta/Google/LinkedIn]
**Hook 2 (Contrarian):** "[Ad headline]"
> [Body copy]
**Hook 3 (Practical):** "[Ad headline]"
> [Body copy]
---
## Run This Week (Score 70-89)
[Same format]
---
## Worth Testing (Score 50-69)
[Same format, briefer]
---
## Trend Velocity Dashboard
| Trend | Twitter | Reddit | LinkedIn | HN | Score | Window |
|-------|---------|--------|----------|----|----|--------|
| [Trend 1] | High | Medium | Low | — | 92 | 24h |
| [Trend 2] | Medium | — | High | Low | 78 | 5d |
| [Trend 3] | Low | Medium | — | Medium | 61 | 2w |
---
## Competitor Trend Involvement
| Trend | Competitor Riding It? | Their Angle | Your Counter-Angle |
|-------|----------------------|-------------|-------------------|
| [Trend] | [Y/N — who] | [Their take] | [Your differentiated take] |
Save to trending-hooks-[YYYY-MM-DD].md in the current working directory (or user-specified path).
Cost
| Component | Cost |
|---|---|
| Twitter/X (web_search) | Free |
| Reddit scraper (Apify) | ~$0.05-0.10 |
| LinkedIn (web_search) | Free |
| Hacker News (Algolia API) | Free |
| Analysis & hook generation | Free (LLM reasoning) |
| Total | ~$0.05-0.10 (or free if skipping Reddit Apify scraper) |
Tools Required
- Environment variable:
APIFY_API_TOKEN— for Reddit scraping via Apify (optional — skill works without it using web_search fallback for Reddit) - Web search — built into your AI agent (for Twitter/X, LinkedIn)
- Hacker News Algolia API — free, no key needed (
https://hn.algolia.com/api/v1/) - No third-party libraries needed. All data collection uses HTTP APIs (
requestsor equivalent) and web_search.
Trigger Phrases
- "What's trending we could run ads about?"
- "Find viral hooks for our campaigns"
- "What's hot in [space] this week?"
- "Newsjacking opportunities for [client]"
- "Run the trending hook spotter"