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.
npx gooseworks install --all # then, in Claude Code, Cursor, or Codex: /gooseworks use the trending-ad-hook-spotter skill
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.
APIFY_API_TOKEN — required for Reddit scraping (optional if using only web_search + HN API)web_search or equivalent for Twitter/X and LinkedIn lookupsUse 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:
Score each tweet/thread by engagement velocity (likes + retweets relative to account size and age).
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=$APIFY_API_TOKENWhen status is SUCCEEDED, fetch results:
GET https://api.apify.com/v2/datasets/{DATASET_ID}/items?token=$APIFY_API_TOKENOutput fields: Each item has dataType ("post" or "comment"), title (posts only), body, communityName, upVotes, numberOfComments (posts), url, createdAt.
Look for:
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:
Identify high-engagement posts on topics relevant to your product category.
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=20Search 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=20Get front page stories (current trending):
GET https://hn.algolia.com/api/v1/search?tags=front_page&hitsPerPage=30The 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:
Group collected signals into trends. A "trend" is:
| 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:
For each trend scoring 50+, generate:
[Trend reference] + [Your unique angle] + [CTA tied to the moment]# 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).
| 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) |
APIFY_API_TOKEN — for Reddit scraping via Apify (optional — skill works without it using web_search fallback for Reddit)https://hn.algolia.com/api/v1/)requests or equivalent) and web_search.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.
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.
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.