Monitors analytics across YouTube, TikTok, and Skool, collects data and transcripts, computes week-over-week growth, analyzes drivers with AI, generates a polished HTML report, and emails it to you while archiving the data.
The AI Agent automatically gathers data from YouTube, TikTok, and Skool, including video metrics and transcripts. It computes week-over-week growth against the last Airtable baseline. It generates a polished HTML report and emails it to you, while archiving raw data for future reference.
A concise summary of the agent’s end-to-end workflow.
Fetches weekly metrics from YouTube, TikTok, and Skool.
Aggregates data into Airtable for baseline tracking.
Calculates exact week-over-week growth for followers and subscribers.
Extracts transcripts to inform the AI analysis.
Analyzes performance drivers and trends using an OpenRouter-based AI model.
Generates a formatted HTML report and emails it, then archives raw data.
Two sentences of explanation.
A simple 3-step flow turns raw data into a ready-to-share report.
Collects live follower counts and recent video transcripts from YouTube, TikTok, and Skool, storing results in Airtable.
Compares current numbers with last week's baseline to compute exact gains.
Feeds data into the OpenRouter LLM to identify performance drivers and generate the HTML report.
A realistic weekly scenario showing task, time, and outcome.
Scenario: A creator with three channels schedules a Sunday run to fetch seven days of metrics and transcripts, compute growth, generate a polished HTML report, and email it to stakeholders. Time: about 5–10 minutes per run, plus 2 minutes to review the emailed report. Outcome: a clear growth summary, actionable trends, and a baseline updated in Airtable for next week.
One supporting sentence.
Needs regular, accurate multi-channel performance insights without manual data wrangling.
Must deliver consistent client reporting across multiple accounts.
Tracks Skool engagement alongside YouTube and TikTok metrics.
Wants concrete performance drivers tied to content strategy.
Produces automated dashboards and client-ready reports.
Provides data-backed recommendations to clients.
One supporting sentence with short explanation.
Scrapes TikTok and Skool data for up-to-date metrics.
Runs the LLM to analyze data and generate the HTML report.
Stores baselines, current data, and growth calculations.
Emails the final HTML report to your inbox.
Fetches YouTube metrics and video data.
Supports data retrieval and API access for scraping.
Six practical scenarios where this AI agent shines.
One supporting sentence with short explanation.
The agent is designed to run on a weekly cycle by default, typically on Sundays, to align with the weekly reporting cadence. You can adjust the Schedule Trigger to a different day or frequency. The run collects seven days of data, computes growth against the last baseline, and generates an HTML report delivered by email. Credentials and API keys remain securely managed within your n8n and integration environments. If you need more frequent updates, you can enable a separate on-demand trigger for special reports.
Supported sources include YouTube (Data API for metrics), TikTok (via Apify scraping), and Skool (via Apify scraping). The workflow also reads from Airtable to maintain the growth baseline and to store prior results. Transcripts and video data are incorporated to enhance AI-driven insights. If you want to add LinkedIn or Instagram, you can enable additional scrapers with corresponding credentials. Data is collected with explicit permission from each platform’s data endpoints and terms.
A baseline is required for accurate growth calculations. You’ll need to manually input one row of current stats into the linked Airtable template before the first scheduled run. After that, the agent compares live data to this baseline to compute growth. You can update the baseline any time to reflect new starting points. If you’re new, set a one-time initialization run to populate Airtable before enabling the weekly schedule.
Yes. The agent architecture supports adding or removing platforms with corresponding scrapers or APIs. You can enable additional data sources by configuring the Scrapers (Apify actors) and updating the data flow in n8n. The AI analysis still compiles a single report from all active sources. When introducing new platforms, ensure you have the necessary credentials and consent for data access.
OpenRouter is the default pathway, but you can swap in a preferred model (such as Claude 3.5 or GPT-4o) by updating the OpenRouter node configuration. The change affects the depth and style of the narrative in the generated report. For most users, the default model provides balanced, actionable insights. Advanced users can test different models on a copy of the workflow to compare results.
The agent delivers the HTML report via email and archives the raw data in Airtable. You can modify the delivery channel, such as emailing a PDF version or posting to a collaboration channel, by adding or adjusting nodes in n8n. The archival step ensures you always have a reproducible baseline for future weeks. If you need examples, duplicate the reporting step and configure alternative recipients or destinations.
All credentials are managed within your own accounts (Airtable, Gmail, API keys). Data access follows platform terms of service and your organization’s privacy policies. The workflow minimizes data exposure by using scoped API permissions and short-lived tokens where possible. Regular audits of access logs are recommended to maintain security.
Monitors analytics across YouTube, TikTok, and Skool, collects data and transcripts, computes week-over-week growth, analyzes drivers with AI, generates a polished HTML report, and emails it to you while archiving the data.
