Morning Course Digest for Coaches Node Logic Deep Dive

At 6:15 am a coach opens their laptop to review yesterday’s student messages. Before coffee is finished, a Slack notification pings: "New course digest ready." The workflow has already gathered the latest articles from three RSS feeds, extracted the key takeaways, and posted a formatted summary to the #coaching‑updates channel. This is what the Morning Course Digest for Coaches workflow does each morning.

At a glance

• Built for: coaches and course creators
• Difficulty: beginner
• Starts with: Schedule Trigger (scheduleTrigger)
• Steps: 5 nodes
• Tools: n8n, Slack, RSS Feed

Schedule Trigger – scheduleTrigger

The workflow begins with the scheduleTrigger node. It is configured to run at 06:00 local time every weekday. When the trigger fires, it passes an empty execution context to the next node. No input data is required; the trigger simply starts the cycle at the set interval.

Fetch RSS Feed – httpRequest

The httpRequest node receives the empty context from the schedule trigger and issues GET requests to the three selected RSS feed URLs. Each response contains an XML payload with items, each item having a title, link, and description. The node outputs an array of RSS items; each item includes the raw XML fields plus any metadata the node adds, such as the fetch timestamp. A typical output item looks like { "title": "Advanced Python Techniques", "link": "https://example.com/python-tips", "description": "Learn decorators and context managers." }.

Split RSS Items – splitInBatches

The splitInBatches node receives the array of RSS items from the httpRequest node. It separates the items into individual batches so that each item can be processed independently in the code node. The node does not alter the item structure; it simply outputs one execution per RSS item, passing the full item object down the branch. This allows the code node to run once per article rather than once for the entire feed.

Summarize Content – code

The code node receives one RSS item at a time from the splitInBatches node. Inside the node’s JavaScript function, the raw description text is extracted and trimmed. A simple prompt is constructed using an expression: {{$json["description"]}}. The function then generates three concise, actionable points: the main topic, a practical takeaway, and a suggested next step for a coach. The output is a new JSON object attached to the execution, for example { "summary": "Topic: Using decorators to reduce boilerplate. Takeaway: Wrap repetitive logging. Next step: Apply to your onboarding emails." }.

Post to Slack – slack

The slack node gathers the summarized outputs from all code executions. It formats the results into a single message block, prepending the article title and linking back to the source. The node then posts the formatted text to the chosen Slack channel. The final message might read:
"📚 Advanced Python Techniques
Learn decorators and context managers.
• Topic: Using decorators to reduce boilerplate.
• Takeaway: Wrap repetitive logging.
• Next step: Apply to your onboarding emails.
Read more: https://example.com/python-tips"

Worked Example

Input (RSS item):
{ "title": "Time‑boxing Coaching Sessions", "link": "https://coachingblog.com/timeboxing", "description": "A quick method to structure 30‑minute client calls with clear start, middle, and end phases." }

After splitInBatches:
The item is passed to the code node as a single execution context.

After code:
The node produces { "summary": "Topic: Time‑boxing structure for 30‑min calls. Takeaway: Define start, middle, end phases. Next step: Map your own client intake flow." }.

After slack:
The Slack message posted reads:
"📚 Time‑boxing Coaching Sessions
A quick method to structure 30‑minute client calls with clear start, middle, and end phases.
• Topic: Time‑boxing structure for 30‑min calls.
• Takeaway: Define start, middle, end phases.
• Next step: Map your own client intake flow.
Read more: https://coachingblog.com/timeboxing"

Watch Out For

The httpRequest node relies on the RSS feeds being well‑formed. If a feed returns HTML error pages or missing description fields, the code node may throw an error or produce incomplete summaries. Adding a Set node before the code step to check for the existence of description can prevent failures.

Key takeaways

• The scheduleTrigger starts the workflow each morning without manual input.
• The httpRequest node fetches raw RSS data from selected feeds, outputting individual items.
• The splitInBatches node isolates each item so the code node can summarize them one at a time.
• The code node generates concise actionable points from the article description.
• The slack node posts the formatted summary to a chosen channel, linking back to the source article.

Before you import it

• A running n8n instance (cloud or self-hosted).
• n8n account
• Slack workspace access
• RSS feed URLs for course content
• Sample data to test with, before pointing it at real records.

Get the free workflow

The importable JSON for Morning Course Digest for Coaches is free to download: https://lanexbuilds.com/library

This workflow was generated with AI assistance. Test it with sample data before using it on real data.

Cover photo by StartupStockPhotos on Pixabay