trending-ad-hook-spotter

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?"

Phase 0: Intake

1. Your product — Name + one-line description
2. Industry/category — What space are you in? (e.g., "AI sales tools", "developer infrastructure")
3. ICP keywords — 5-10 keywords that define your buyer's world
4. Competitor names — So we can spot when they become part of a trend
5. Platforms to scan (default: all):
   • Twitter/X
   • Reddit (specific subreddits if known)
   • LinkedIn
   • Hacker News
6. Content velocity — How fast can you create ads? (Same-day / 2-3 days / Weekly)

Phase 1: Social Scanning

1A: Twitter/X Trend Scan

Run twitter-scraper with multiple queries:

# Industry trending topics
python3 skills/twitter-scraper/scripts/scrape_twitter.py \
  --query "<industry keyword> (viral OR trending OR hot take OR unpopular opinion OR thread)" \
  --max-results 50 \
  --sort top

# Competitor mentions (momentum signals)
python3 skills/twitter-scraper/scripts/scrape_twitter.py \
  --query "<competitor1> OR <competitor2> (raised OR launched OR shut down OR acquired OR outage)" \
  --max-results 30

# Pain/frustration spikes
python3 skills/twitter-scraper/scripts/scrape_twitter.py \
  --query "<category> (broken OR frustrating OR tired of OR switched from)" \
  --max-results 30

Score each tweet/thread by engagement velocity (likes + retweets relative to account size and age).

1B: Reddit Trend Scan

Run reddit-scraper:

python3 skills/reddit-scraper/scripts/scrape_reddit.py \
  --subreddits "<relevant_subreddits>" \
  --sort hot \
  --time week \
  --limit 30

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

Run linkedin-profile-post-scraper for 5-10 KOLs in the space:

python3 skills/linkedin-profile-post-scraper/scripts/scrape_linkedin_posts.py \
  --urls "<kol_profile_urls>" \
  --max-posts 10

Identify high-engagement posts on topics relevant to your product category.

1D: Hacker News Scan

Run hacker-news-scraper:

python3 skills/hacker-news-scraper/scripts/scrape_hn.py \
  --query "<industry keyword>" \
  --type story \
  --sort points \
  --limit 20

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:

1. Trend summary — What's happening in 2 sentences
2. Why it's an ad opportunity — Connection to your product/ICP
3. 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")
4. Recommended format — Static / video / carousel / search ad
5. Recommended platform — Where the trend is hottest
6. 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] | ▲▲▲ | ▲▲ | ▲ | — | 92 | 24h |
| [Trend 2] | ▲▲ | — | ▲▲▲ | ▲ | 78 | 5d |
| [Trend 3] | ▲ | ▲▲ | — | ▲▲ | 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 clients/<client-name>/ads/trending-hooks-[YYYY-MM-DD].md.

Scheduling

Run weekly or on-demand when you need fresh hooks:

0 8 * * 1 python3 run_skill.py trending-ad-hook-spotter --client <client-name>

Cost

Component	Cost
Twitter scraper (3 queries)	~$0.15-0.30 (Apify)
Reddit scraper	~$0.05-0.10 (Apify)
LinkedIn scraper (5-10 KOLs)	~$0.25-0.50 (Apify)
HN scraper	Free
Analysis & hook generation	Free (LLM reasoning)
Total	~$0.45-0.90

Tools Required

• Apify API token — APIFY_API_TOKEN env var
• Upstream skills: twitter-scraper, reddit-scraper, linkedin-profile-post-scraper, hacker-news-scraper

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"