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.
适合你,如果你需要紧跟热点来策划广告投放。
npx oh-my-skill add gooseworks-ai/goose-skills/trending-ad-hook-spottercurl -fsSL https://oh-my-skill.com/install.sh | bash -s -- gooseworks-ai/goose-skills/trending-ad-hook-spotternpx oh-my-skill verify gooseworks-ai/goose-skills/trending-ad-hook-spotter怎么用
技能原文 SKILL.md
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"