trend-monitor

name Trend Monitor description Monitor and store trending topics from X, Google Trends, Hacker News, Product Hunt, Reddit, and GitHub. Save browser-extracted trends, query latest data, and get AI-filtered topic suggestions for content planning. version 1.0.0 category content skillType claude-skill assignableRoles ["content-strategist","product-manager","generalist"] triggers ["trending topics","what is trending","trend monitor","hot topics","content ideas","topic suggestions"] tags ["trends","monitoring","content","social-media","hackernews","producthunt","x-twitter","marketing"] execution {"type":"script","script":{"file":"execute.sh","interpreter":"bash","timeoutMs":15000}} Trend Monitor Monitor trending topics across platforms using browser automation, then store and query them for content planning. Architecture This skill has two parts: Browser scanning (agent-driven) — You use Playwright MCP or Chrome browser tools to visit pages and extract trends Data management (execute.sh) — Save, query, and get suggestions from stored trend data Data Actions (execute.sh) save — Store trends from a browser scan Parameter Required Description action Yes "save" source Yes x-trending , google-trends , hackernews , producthunt , reddit , github-trending , custom trends Yes JSON array of trend objects (see schema below) projectPath No Project path for storage location Trend object schema: { "title" : "Topic or headline" , "url" : "https://source-url" , "description" : "Brief description" , "engagement" : "500 points / 200 comments" , "relevanceScore" : 8 , "tags" : [ "ai" , "agents" , "automation" ] } relevanceScore (1-10): How relevant to AI Agent / Crewly content. Score guide: 9-10: Directly about AI agents, orchestration, multi-agent systems 7-8: About AI tools, LLMs, automation, developer tooling 5-6: About SaaS, startups, productivity, SMB 3-4: General tech, not directly relevant 1-2: Not relevant list — List available trend scan files Parameter Required Description action Yes "list" source No Filter by source date No Filter by date (YYYY-MM-DD) limit No Max files to return (default: 10) latest — Get the most recent trends Parameter Required Description action Yes "latest" source No Filter by source limit No Max items (default: 20) suggest — Get AI-filtered topic suggestions Parameter Required Description action Yes "suggest" line No Content line: crewly or personal (default: crewly) limit No Max suggestions (default: 5) Browser Scanning Guide Step-by-step: How to scan each source The agent should perform these browser operations, then pass the extracted data to execute.sh save . Source 1: Hacker News (hackernews) URL: https://news.ycombinator.com Steps: Navigate to https://news.ycombinator.com Take a snapshot of the page Extract from each story row: Title text URL (href from titleline link) Points and comment count (from subline) Score relevance (AI/agent/automation related = high score) Save top 20 stories Alternative (faster): Use WebSearch with query site:news.ycombinator.com AI agents for targeted results. Example save: bash execute.sh '{"action":"save","source":"hackernews","projectPath":"/path/to/project","trends":[ {"title":"Show HN: Open-source AI agent framework","url":"https://news.ycombinator.com/item?id=123","engagement":"342 points, 89 comments","relevanceScore":9,"tags":["ai","agents","open-source"]}, {"title":"Why we moved from n8n to custom orchestration","url":"https://example.com/post","engagement":"156 points, 43 comments","relevanceScore":8,"tags":["automation","n8n","orchestration"]} ]}' Source 2: X/Twitter Trending (x-trending) URL: https://x.com/explore/tabs/trending Steps: Navigate to https://x.com/explore/tabs/trending (or https://x.com/explore ) Take a snapshot Extract trending topics and hashtags For each trend, note: Topic name / hashtag Tweet count or category if shown Brief context if available Score relevance to AI/tech/startup Alternative: Use WebSearch with site:x.com trending AI agents or check https://trends24.in/united-states/ Source 3: Product Hunt (producthunt) URL: https://www.producthunt.com Steps: Navigate to https://www.producthunt.com Take a snapshot of today's launches Extract from each product: Product name and tagline Upvote count URL Category/tags Filter for AI/automation/developer tools Score relevance Source 4: Google Trends (google-trends) URL: https://trends.google.com/trending?geo=US Steps: Navigate to https://trends.google.com/trending?geo=US Take a snapshot Extract daily trending searches Filter for tech/AI related terms Score relevance Alternative: Use WebSearch with Google Trends AI agents 2026 for curated results. Source 5: Reddit (reddit) URLs: https://www.reddit.com/r/artificial/hot/ https://www.reddit.com/r/LocalLLaMA/hot/ https://www.reddit.com/r/SideProject/hot/ Steps: Navigate to each subreddit Extract top 10 posts: title, score, comment count, URL Score relevance Source 6: GitHub Trending (github-trending) URL: https://github.com/trending Steps: Navigate to https://github.com/trending Extract: repo name, description, stars today, language Filter for AI/agent/automation repos Score relevance Recommended Scan Schedule Time Source Frequency Morning Hacker News + Product Hunt Daily Afternoon X Trending + Reddit Daily Weekly Google Trends + GitHub Trending Monday Workflow Integration 1. Agent runs browser scans → saves via execute.sh save 2. Agent calls execute.sh suggest → gets AI-filtered topics 3. Agent feeds suggestions to content-writer skill 4. Agent adds chosen topics to content-calendar Example: Full Daily Scan # After scanning HN via browser and extracting data: bash execute.sh '{"action":"save","source":"hackernews","projectPath":"/path","trends":[...]}' # After scanning PH via browser: bash execute.sh '{"action":"save","source":"producthunt","projectPath":"/path","trends":[...]}' # Get suggestions for content: bash execute.sh '{"action":"suggest","line":"crewly","projectPath":"/path"}' # Check latest across all sources: bash execute.sh '{"action":"latest","limit":"10","projectPath":"/path"}'