ads

Trending Ad Hook Spotter

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.

Gooseby Athina AI
Install
Terminal
npx gooseworks install --all

# then, in Claude Code, Cursor, or Codex:
/gooseworks use the trending-ad-hook-spotter skill
About This Skill

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_search or equivalent for Twitter/X and LinkedIn lookups
  • No API key needed for Hacker News (Algolia HN API is free and public)

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 (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

FactorWeightDescription
Recency25%How fresh? (< 24h = max, > 7 days = low)
Velocity25%Is engagement accelerating or decelerating?
Cross-platform20%Appearing on multiple platforms?
ICP relevance20%Does your target buyer care about this?
Product fit10%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] | 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

ComponentCost
Twitter/X (web_search)Free
Reddit scraper (Apify)~$0.05-0.10
LinkedIn (web_search)Free
Hacker News (Algolia API)Free
Analysis & hook generationFree (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 (requests or 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"

What's included

·
"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?"
You Might Also Like

Render VO Anchored Motion Listicle

Assemble an expert/educator motion-graphic LISTICLE video ad from a config — a spoken authoritative voiceover carries a numbered listicle while N web-animated hyperframe beats (HTML plus the Web Animations API, one branded design system of alternating tiles, big hero numerals, and glass-pill callouts) are rendered frame-by-frame via Playwright and anchored to the VO's word-level timestamps, periodic color-graded B-roll windows give visual breath, and captions burn ONLY inside those B-roll windows (2-word chunks, ASS Format header carrying a Name field so none drop) with the VO mixed under a low music bed. This is the FREE deterministic assembly stage (Playwright beat render plus ffmpeg concat plus window-masked caption burn plus VO-and-music mix plus final composite) — the VO, the music bed, and the stock B-roll come from create-vo-elevenlabs, create-music-elevenlabs, and media-proxy. Use for the vo-anchored-motion-listicle format.

Render Stopmotion Hand Swatch Cycle

Assemble a stop-motion hand-swatch-cycle product-demo ad from a config — a sequence of still PLATES (one hand swiping a single-barrel cosmetic across a cream skin-patch, the barrel + swatch changing per plate while the hand, background, crop, and lighting stay locked) is PNG→mp4 loop-encoded at each plate's own stop-motion hold (fast motion frames 150–250ms, per-shade ~380ms, hero beats 1100–1800ms), concat-demuxed with HARD cuts into a silent master, closed on a Playwright HTML-rendered branded end card (serif tagline + sans subtitle + real logo SVG over a hero BG, never AI-rendered text), and muxed with a pre-sourced music track playing under the end card with a fade tail (no VO). This is the FREE deterministic assembly stage (loop-encode + concat-demux + end-card render + music mux); the master-anchor plate, shade plates, and end-card BG come from create-image-gpt-image-fal and the track from create-music-elevenlabs. Use for the stopmotion-hand-swatch-cycle format.

Render Split Screen Creator

Assemble a split-screen creator ad from a config — a two-zone vertical composite where a supplied AI-creator lip-sync take fills the BOTTOM ~48% while real 16:9 product/demo clips run uncropped in the TOP ~52%, each top clip contain-fit with a darkened blurred cover-scale fill of the same clip (never black bars), a 3px brand-color divider between the zones, the creator slice cover-fit per the per-scene VO timing, scenes hard-concatenated with the body audio being the concatenated creator VO slices, an end card held on the last sharp frame ~3s, then the ASSEMBLED cut transcribed with local Whisper (not the raw VO — concat drops inter-scene silence) and word-level captions burned in the chosen style. This is the FREE deterministic assembly + caption stage (two-zone composite + blurred fill + divider + hard-concat + end card + captions); the VO comes from create-vo-elevenlabs, the anchor from create-image-gpt-image-fal, and the whole-VO lip-sync from a paid VEED Fabric 1.0 take (a no-atom upstream input). Use for the split-screen-creator format.

Newsletter

Learn to build Growth systems with AI

2-3 compounding systems per week using Claude Code, OpenClaw, and more.