How to stop manually searching for competitors' content: 8 n8n workflows for monitoring, rewriting, and auto-publishing

The familiar pain: you have a content plan, but no time for it

You run a blog, a Telegram channel, or content for clients. Every day you need to produce fresh material, keep an eye on the news landscape, and stay aware of what competitors are publishing. But instead of strategy, you spend hours on routine: opening dozens of tabs, copying articles, rewriting them by hand, checking them for plagiarism, adapting them to your Tone of Voice, uploading them to the CMS. By evening, you have no energy left for analytics and growth.

The problem isn't that you're not working hard enough. The problem is that your processes aren't automated. The good news: you can build this chain once in n8n — and it will run without your involvement. Below is a practical guide on how to do it step by step.

What exactly needs to be automated

The full cycle of competitor-based content production consists of five stages:

1. Source monitoring — tracking new publications via RSS feeds and competitors' site sitemaps.

2. Extraction and reworking — retrieving the text and rewriting or adapting it with an LLM.

3. Quality control — checking uniqueness and compliance with your Tone of Voice.

4. Formatting — preparing it for a specific platform (WordPress, Telegram).

5. Publishing — automatically uploading it to the CMS or messenger.

Each stage can be implemented as a separate workflow or combined into a chain. The main thing is that data transfer between steps is seamless.

Step 1. Set up RSS and sitemap monitoring

Start with the sources. Most blogs and media outlets have RSS feeds, and if they don't, use sitemap.xml. n8n has ready-made nodes for HTTP requests and XML parsing. The logic is simple:

• A trigger runs once an hour or once a day.
• The workflow requests the competitor's RSS feed or sitemap.
• It compares the list of URLs with those already processed (store them in Google Sheets, Airtable, or a database).
• It sends new links to the next stage.

If you do this manually, it's easy to miss an important publication or spend half a day sorting. Automation eliminates this routine.

Step 2. Extract the text and rewrite it with an LLM

Once new URLs are found, you need to get their content. Use the HTTP Request node or a specialized parser for this. Then the text is sent to an LLM (for example, via the OpenAI API, Anthropic, or a local model).

Important points:

• The prompt must be strict. Clearly describe what needs to be preserved — the facts and meaning — but with changed wording.
• Take Tone of Voice into account. Pass examples of your style or instructions into the prompt: "write in a friendly way, without bureaucratic language, with short paragraphs."
• Don't copy one-to-one. The goal isn't plagiarism, but reworking and adapting for your audience.

At this stage, it's convenient to use ready-made workflow templates so you don't have to build everything from scratch. For example, the "Competitor Content Factory: 8 n8n workflows for auto-monitoring, rewriting, and publishing" set already includes scenarios for monitoring, rewriting, and publishing — you just plug in your API keys and sources.

Step 3. Check uniqueness and quality

After rewriting, the text needs to be checked. This is done automatically in two ways:

• Via uniqueness-checking service APIs (for example, Text.ru, Advego, or similar). The HTTP Request node sends the text and receives a uniqueness percentage.
• Via comparison with the source using embeddings or simple similarity analysis. If the text is too similar to the original, the workflow can send it for another rewrite or flag it for manual review.

Don't skip this step: search engines and readers don't like blatant copy-paste. Automatic checking saves time and reduces risks.

Step 4. Adapt it to your Tone of Voice and platform

The same material looks different for WordPress and Telegram. WordPress needs a headline, a meta description, and possibly HTML markup. Telegram needs short paragraphs, emoji, links, and no complex formatting.

In n8n, you can create branching: if you're publishing to WordPress, you form one set of fields; if to Telegram, another. You can ask the LLM to separately rewrite the text for each platform. This won't take much time if the templates are already ready.

Step 5. Set up auto-publishing

The final stage is sending the content. For WordPress, use the REST API or XML-RPC. For Telegram, use the Bot API. n8n has ready-made nodes for both cases.

What's important to plan for:

• Schedule. Don't publish everything at once — publish according to your content plan. You can add delays or a queue.
• Drafts. At first, it's better to send materials to drafts so you can review them before publishing.
• Logging. Save what was published and when, so you don't duplicate posts.

If you work with video, check out the short video pipeline on n8n — it helps automate voiceover, editing, and publishing to TikTok, Reels, and Shorts. But for text content, the chain described above is enough.

Step-by-step implementation plan

To avoid drowning in details, proceed like this:

1. Identify 3–5 competitors and collect their RSS or sitemap.

2. Create a table to store processed URLs.

3. Build the first workflow — monitoring and extracting new links.

4. Add LLM rewriting with a clear prompt tailored to your Tone of Voice.

5. Connect uniqueness checking and set a threshold below which the text goes back for revision.

6. Create the publishing branch to WordPress or Telegram.

7. Run it in test mode on several pieces of material and check the quality.

8. Gradually increase the frequency and volume once you're sure everything works reliably.

Common mistakes and how to avoid them

• A prompt that's too broad. The LLM starts hallucinating or changing the meaning. Solution: add a requirement to the prompt to preserve facts and not add new information.
• Ignoring uniqueness. Even a rewrite can be too close to the original. Always check.
• Publishing without moderation. At the start, it's better to leave drafts so you can control quality.
• No logging. Without a history of processed URLs, you risk publishing duplicates.

The bottom line

Automating monitoring, rewriting, and publishing isn't about "replacing a human" — it's about freeing up time for strategy and creativity. A ready-made set of 8 n8n workflows lets you launch such a system without months of development. You get proven logic that you just need to adapt to your sources and style.

Take a look at "Competitor Content Factory: 8 n8n workflows for auto-monitoring, rewriting, and publishing" — it's a practical way to start automating content today, without building every step by hand.