I built a custom news agent that skips the Google News and Apple News walled gardens. Eight prompts turn Claude into a personal news editor that reads my trusted RSS feeds, scores every story with a decision model, and delivers a clean daily page for about a dime a month.

Each week, pulling two or three good stories for my newsletter digest meant searching multiple sites by hand—hours of clicking and scrolling for a handful of usable links. RSS feeds already deliver that content; the missing piece was a judgment layer that could separate worthwhile stories from noise without the cost or latency of running everything through a full LLM.

I used Claude Cowork, Jev from TypeSafe AI, Vercel AI Gateway, RSS feeds, Python, and SQLite. Jev is a decision model rather than a chatbot: it returns a probability and confidence score instead of prose, does not hallucinate facts, and scores a story in a fraction of a second. That makes an automated daily judgment call inexpensive enough to run continuously.

Step-by-step

1. I set up a Claude project to hold the scripts, taste guide, database, and page.
2. I defined the goal and sections, then had Claude interview me to create a short “taste guide” describing what counts as a good story.
3. I found and live-tested the RSS feed for each trusted source instead of guessing feed URLs.
4. I fetched all working feeds into a deduplicated SQLite database and logged failures.
5. I used Jev through Vercel AI Gateway to score every story: first filtering ads and promotions, then ranking stories by section against my taste guide.
6. I selected the winners for each section, with Jev identifying near-duplicate stories so they would not appear twice.
7. I generated one-line summaries and fact-checked them against the source so nothing was invented.
8. I rendered a simple HTML page and scheduled the entire workflow to run every morning.

A few details matter. I used Cowork rather than a plain chat because several steps require Claude to work with files, run code, and access the network. I also created a Vercel account and AI Gateway API key manually before the scoring step. Finally, I saved everything to the Claude project instead of a local folder, which allows the morning run to happen in the cloud on its own schedule.

Scoring costs roughly $0.10 per month with Jev, compared with a few dollars for a full LLM doing the same job. The workflow turns a two-hour weekly slog into a page that is ready every morning, with each link going directly to the original publisher rather than a Google or Apple aggregator.

Full build walkthrough: onabetternote.substack.com/p/build-your-own-news-agent-with-claude — the Substack post includes the exact eight prompts to copy and paste, plus more detail on why a model like Jev matters for cost containment as agents become routine.