--- 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?" ## 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: " (viral OR trending OR hot take OR thread) site:x.com" # Competitor mentions (momentum signals) web_search: " OR (raised OR launched OR shut down OR acquired OR outage) site:x.com" # Pain/frustration spikes web_search: " (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": [" OR "], "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: " site:linkedin.com/posts" web_search: " site:linkedin.com/posts" web_search: " site:linkedin.com/posts" web_search: " 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: 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 ```markdown # 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 (`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"