I Built an Agent That Reads So I Don't Have To
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady What I Built Overnight is a small agent that reads the things I don't want to read, overnight, and hands me a two-line brief per item in the morning. You point it at a folder, a single file, a URL, or stdin. It reads every item, runs an open-weight model on my own machine , and writes a two-sentence brief…
This submission for the Hacktoberfest Open-Source AI Challenge Week 3 is an overnight agent that reads emails, files, URLs, or stdin, and generates a two-sentence brief per item in the morning. The user points it to a folder, a file, a URL, or stdin, and it reads every item, runs an open-weight model on the machine, and writes the two-sentence briefs to a markdown file.
The agent saves the user's attention by performing the task while they sleep, rather than making them read lengthy content. The summariser is a locally stored GGUF model using Qwen 2.5 1.5B Q4_K_M. The harness is around 250 lines of Python, interacting with llama-cli or llama-server on localhost:8080. The main advantage of this open-source tool is that the reading remains the user's, as there is no third party to leak data to.
The agent runs offline, is trustworthy due to its open nature, and allows the user to swap models or fine-tune them on their vocabulary. The project is honest about its limitations, such as the small size of the model, the language it is trained on, and the occasional inaccurate summaries.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
