Nostr #damus AI Powered Reporting + Gmail + Telegram
This workflow automatically monitors and aggregates social content tagged with #damus on the Nostr platform. It utilizes an AI language model for in-depth topic analysis, generating detailed reports that are promptly pushed through two major channels: Gmail and Telegram. This process effectively reduces the tediousness of manual information collection, enhancing the efficiency of community management, market analysis, and content planning, helping users quickly gain insights into community dynamics and user needs.
Workflow Name
Nostr #damus AI Powered Reporting + Gmail + Telegram
Key Features and Highlights
This workflow is built on the Nostr social networking platform, aggregating posts tagged with #damus. It leverages Google Gemini (PaLM) large language model for in-depth topic extraction and analysis, automatically generating comprehensive thematic reports. The reports are then synchronized and pushed through both Gmail and Telegram channels. The workflow supports Markdown to HTML conversion to enhance readability and visual appeal.
Core Problems Addressed
- Automatically monitors and aggregates social content tagged with #damus on the Nostr platform, eliminating the hassle of manual data collection.
- Utilizes AI-driven analysis to deeply uncover themes and underlying motivations in user posts, aiding in understanding community dynamics and user needs.
- Enables multi-channel automated report delivery to ensure timely dissemination to relevant stakeholders, improving communication efficiency.
Use Cases
- Community managers or product teams needing regular insights into trending discussions and user feedback around the #damus topic.
- Market analysts or content strategists aiming to quickly obtain and analyze thematic content from social media.
- Technical teams monitoring social ecosystems via automation to support decision-making and optimize product experiences.
Main Workflow Steps
- Workflow initiation via scheduled trigger or manual trigger.
- Fetch Nostr posts tagged with #damus using the “Nostr Read #damus” node.
- Aggregate the fetched content data through the “Aggregate #damus Content” node.
- Invoke Google Gemini language model for two rounds of analysis:
- Extract a list of themes (#damus Themes List)
- Conduct in-depth analysis of themes and common threads to generate a detailed report (#damus Themes & Threads Report)
- Convert AI analysis results from Markdown to HTML format to enhance presentation.
- Send the report via Gmail node to designated email addresses.
- Push the report content to predefined Telegram chat groups using the Telegram node.
Systems and Services Involved
- Nostr: Source of social content, fetching posts tagged with #damus.
- Google Gemini (PaLM) API: Powerful AI language model for topic extraction and deep analysis.
- Gmail: Email service used for report delivery.
- Telegram: Instant messaging platform for report distribution to chat groups.
- n8n platform nodes: Including schedule trigger, Markdown to HTML conversion, data aggregation, text merging, and other functional nodes.
Target Users and Value Proposition
- Community Operators: Efficiently monitor community trends and capture user hot topics and feedback.
- Product Managers and Market Analysts: Leverage AI insights to better understand user needs and market trends.
- Content Creators and Strategists: Quickly access social media thematic content to optimize content strategies.
- Developers and Automation Enthusiasts: Learn and reference multi-system integration and AI-powered automation workflow design.
This workflow enables users to automatically collect, intelligently analyze, and share Nostr #damus community content across multiple channels, significantly enhancing information processing efficiency and decision support capabilities.