Firecrawl AI駆動のマーケットインテリジェンスロボット：自動ニュースインサイトの配送

• •Slack Bot Token または Webhook URL
• •ターゲットAPIの認証情報が必要な場合あり
• •OpenAI API Key

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        "content": "# AI-Powered Market Intelligence Bot\n\n## Overview\nThis n8n workflow automatically monitors TechCrunch for AI-related articles, using Firecrawl's AI-powered web scraping to extract clean, structured data and OpenAI to generate actionable summaries delivered directly to your team's Slack channel.\n\n## 🚀 1. Trigger & Scheduling\n\n### Daily Method Research Trigger\n- Initiates automated TechCrunch monitoring on a scheduled basis\n- Default: Daily execution to capture fresh AI industry news and trends\n- Configurable for different frequencies based on market velocity\n- Ensures consistent intelligence gathering without manual intervention\n\n## 🔍 2. Web Scraping & Data Collection\n\n### Firecrawl Integration (HTTP Request Node)\n- Targets TechCrunch specifically: `https://techcrunch.com` (though, can obviously be changed)\n- Crawls a specificed amount of articles with `\"limit\" -- by default this is set to 20, otherwise it would keep scraping. You can remove this limit to scrape all. \n- Focuses on current year content with `\"includePaths\": [\"2025/\"]` In 2026, you'll need to update this.\n- Extracts markdown format for clean, structured content\n- Uses `\"onlyMainContent\": true` to avoid ads and navigation clutter\n- Built-in anti-bot detection bypass and automatic JavaScript rendering\n\n### Code Text/Concat Processing\n- Filters scraped TechCrunch articles for AI relevance\n- AI research assistant determines if articles relate to artificial intelligence, machine learning, AI companies, or AI technology\n- Automatically excludes non-AI content with \"NOT_AI_RELATED\" filtering\n- Processes article titles, descriptions, and full content for comprehensive analysis\n\n## ⏱️ 3. Processing Flow Control\n\n### Wait Node\n- Implements controlled delays to respect TechCrunch's server resources\n- Enough time to receive results back"
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        "content": "## 🔧 Configuration & Customization\n\n### TechCrunch Scraping Setup\n- Configured to crawl `https://techcrunch.com` with 20 article limit\n- Focuses on current year content with date path filtering\n- Markdown extraction for clean, readable content processing\n- 4-hour cache setting (`\"maxAge\": 14400000`) for efficiency\n\n### AI Relevance Detection\n- Built-in AI research assistant determines article relevance\n- Filters specifically for artificial intelligence, machine learning, AI companies, and AI technology\n- Binary classification: AI-related articles get summarized, others get filtered out\n- Reduces noise by focusing only on AI industry developments\n\n### Slack Integration\n- TechCrunch-specific formatting with source attribution\n- AI-focused message structure with bullet point summaries\n- Integration with Slack threads for AI trend discussions\n- Notification preferences for AI industry updates\n\n## 💡 Best Practices\n\n1. **Monitor TechCrunch Coverage**: Track how much AI content TechCrunch publishes daily\n2. **AI Relevance Accuracy**: Review filtered articles to ensure important AI stories aren't missed\n3. **Summary Quality**: Periodically check that 3-bullet summaries capture key AI insights\n4. **Team Engagement**: Use Slack reactions to identify most valuable AI trends\n5. **Source Verification**: Always include TechCrunch links for fact-checking and deeper reading\n\n## 🔄 Maintenance & Monitoring\n\n- **TechCrunch Access**: Monitor Firecrawl success rates for TechCrunch crawling\n- **AI Classification**: Track accuracy of AI relevance detection\n- **Content Freshness**: Ensure date filtering captures latest AI articles\n- **Delivery Success**: Confirm AI summaries reach Slack channels consistently\n- **Cost Management**: Monitor OpenAI usage for TechCrunch article processing\n\n## 🎯 Business Impact\n\nThis workflow transforms AI market intelligence from manual TechCrunch reading into an automated pipeline that delivers:\n\n- **Daily AI-focused insights** from TechCrunch without manual browsing\n- **Filtered relevance** ensuring only AI industry news reaches your team\n- **Structured summaries** optimized for quick consumption of AI trends\n- **Team awareness** of AI developments through integrated Slack discussions\n- **Source credibility** with direct links to TechCrunch articles\n\nPerfect for AI product teams, tech investors, and executives who need to stay current on artificial intelligence developments without spending time manually browsing TechCrunch."
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        "content": "## 🤖 4. AI-Powered Analysis & Summarization\n\n### OpenAI Summarizer (AI Agent)\n- Uses GPT-4o-mini for cost-effective, high-quality analysis\n- AI research assistant prompt determines AI relevance before summarizing\n- For AI-related articles: generates 3 bullet point summaries\n- For non-AI articles: responds with \"NOT_AI_RELATED\" to filter out\n- Processes TechCrunch article title, description, and full content\n- Maintains source attribution with original TechCrunch URLs\n\n### Split Output Processing\n- Distributes processed TechCrunch articles across parallel analysis streams\n- Enables simultaneous processing of multiple articles\n- Optimizes workflow performance for large news batches\n- Maintains data integrity during multi-path processing\n\n## 📊 5. Intelligence Filtering & Quality Control\n\n### Filter Messages Node\n- Removes articles marked as \"NOT_AI_RELATED\" by the AI assistant\n- Applies relevance scoring to prevent information overload\n- Ensures only AI-focused TechCrunch content reaches stakeholders\n- Customizable filtering logic based on AI relevance confidence\n\n## 📤 6. Delivery & Distribution\n\n### Send Summary to Slack\n- Delivers formatted AI intelligence from TechCrunch to specified channels\n- Message format includes: Article title + 3 bullet point summary + TechCrunch source link\n- Supports threaded conversations for team discussions about AI trends\n- Click-through links to original TechCrunch articles for deeper research\n- Rich formatting optimized for mobile and desktop consumptio"
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