Pattern 3: Newsletter Aggregation

Module 4 · Section 4 of 6

Pattern 3: Newsletter Aggregation

What it does: Pulls items from several RSS feeds on a schedule, filters for relevance, and compiles a list of links for review.

Why it exists: I read a lot of sources. Rather than checking each manually, I want a daily digest of items that match a set of topics.

The nodes:

1. Schedule trigger — Daily at 7:00.

2. RSS Read node (multiple) — One per feed. n8n’s RSS Read node fetches feed items and outputs them as individual objects. I merge the outputs from multiple RSS nodes using a Merge node.

3. Limit node — RSS feeds can return many items. I limit to the 20 most recent across all feeds to keep processing time reasonable.

4. Basic LLM Chain — For each item, passes the title and description to a model with a prompt:

   The following is an RSS item title and description.
   Topics I care about: AI tools, automation, self-hosting, developer tools, security.
   Is this relevant? Reply with only: yes or no.

5. IF node — Routes items where the classification returned yes to the output branch.

6. Aggregate node — Collects all the relevant items into a single list.

7. Code node — Formats the list as a readable block of text with titles and links.

8. Telegram node — Sends the digest.

What to adapt: Your feeds, your topics of interest, your classification prompt. The code node formatting is arbitrary — you could output Markdown, plain text, or HTML depending on your destination.

Note on cost: Running an LLM call per RSS item on a daily schedule adds up. For this workflow I use a local Ollama model. Haiku is also cheap enough that the cost is negligible for a personal workflow.

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