Companion workflow for Facebook node docs
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Find Facebook Hidden Interests via Telegram
Overview This n8n workflow is designed to extract specific interests from messages in a Telegram chat and retrieve related information using the Facebook Graph API. It aims to provide a streamlined solution for parsing and analyzing user-provided interests within the Telegram platform. Features Interest Extraction:** Automatically identifies and extracts interests from messages that start with the hashtag "#interest". Data Retrieval:** Utilizes the Facebook Graph API to retrieve information related to the extracted interests. Structured Outputs:** Presents the retrieved data in an organized format for further analysis and review. Requirements Operational instance of n8n (self-hosted or cloud version). Basic understanding of n8n workflows and nodes. Setup and Configuration Import Workflow: Load the provided JSON workflow into your n8n instance. Configure Telegram Trigger Node: Ensure the Telegram trigger node is set up with the appropriate credentials and webhook ID. Configure and Test Nodes: Adjust node parameters as necessary and test the workflow to ensure proper functionality. How it Works Telegram Trigger: Listens for incoming messages in a specified Telegram chat. Check Messag
Get Comments from Facebook Page
This workflow automates the collection of comments from posts on a Facebook Page. Providing clean, structured data for analysis or further automation. What this workflow does Fetches recent posts from a Facebook Page. Retrieves comments for each post. Outputs structured data of Comments and Posts for further use. Setup Facebook Graph API: Connect your Access Token with the required permissions (pages_read_engagement, pages_read_user_content). Workflow: Set the Page ID and the number of posts to fetch in the "Set Number of Latest Posts to Fetch" node.
WMonitor Meta CAPI event match quality with Meta Graph API and Claude
Quick overview This workflow runs on demand to monitor Meta Conversions API Event Match Quality across the pixels in a Meta ad account, calculates a weighted 0–100 match-quality score from Graph API stats, and uses Anthropic Claude to summarize risks and fixes for any pixels below an alert threshold. How it works Runs when you manually trigger the workflow. Loads configuration for which pixels to monitor, how far back to consider pixels active, which conversion events to weight more heavily, and the alert threshold. Uses the Meta Graph API to discover recently active pixels (or uses a provided list of pixel IDs) and pulls per-event “had_pii” coverage stats for each pixel. Computes a weighted match-quality score per pixel (conversion events count triple) and builds a scorecard sorted from lowest to highest. Sends the scorecard to Anthropic Claude to generate a short JSON summary with a one-line risk and a concrete fix for each pixel below the threshold. Prints a formatted EMQ scorecard with alerts and Claude’s recommendations to the execution log. Setup Create a Meta access token with permissions to read pixel stats, and set META_ACCESS_TOKEN, META_AD_ACCOUNT_ID, and (optionally) ME