skills/composites/trending-ad-hook-spotter/SKILL.md
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 skillsauth add athina-ai/goose-skills trending-ad-hook-spotterInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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=$APIFY_API_TOKEN
When status is SUCCEEDED, fetch results:
GET https://api.apify.com/v2/datasets/{DATASET_ID}/items?token=$APIFY_API_TOKEN
Output fields: Each item has dataType ("post" or "comment"), title (posts only), body, communityName, upVotes, numberOfComments (posts), url, createdAt.
Look for:
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=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:
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.content-media
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