midudev/github-sentinel — explained in plain English
Analysis updated 2026-05-18
Automatically get a summary and risk level for every new issue on a repo you maintain.
See which source files are most likely involved in a reported bug.
Run the agent continuously on a home server or mini PC to triage issues around the clock.
Point the agent at a local, offline language model to keep issue data off the internet.
| midudev/github-sentinel | davidhdev/rbp-portfolio | drakkar-softwares/polymarket-kalshi-arbitrage-bot | |
|---|---|---|---|
| Stars | 29 | 29 | 29 |
| Language | TypeScript | TypeScript | TypeScript |
| Setup difficulty | moderate | easy | moderate |
| Complexity | 3/5 | 2/5 | 3/5 |
| Audience | developer | designer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires Bun as the runtime and an OpenAI-compatible language model endpoint, plus a GitHub token to poll issues.
GitHub Sentinel is a self-hosted agent that monitors one or more GitHub repositories around the clock, detects newly opened issues, analyzes each one with a language model, and displays the results in a local web dashboard. It is designed to run continuously on a small machine such as a mini PC or home server running Windows or macOS. On a configurable schedule (defaulting to every 30 minutes), the agent polls the GitHub REST API for new issues and stores each one in a local SQLite database to avoid processing the same issue twice. For each new issue, it sends the text to a language model of your choice and gets back a summary, a category (bug, feature request, documentation, or question), a risk level (low, medium, or high), the source files most likely involved, and a proposed solution. The dashboard is a minimal React interface styled with terminal-inspired fonts. It supports filtering and searching through analyzed issues. The backend exposes a small API that lets you add or remove repositories to watch, trigger an immediate scan, and force re-analysis of specific issues. The project is built on Bun, a JavaScript runtime that also bundles the frontend and provides a built-in SQLite driver, so there are no external runtime dependencies beyond Bun itself. The language model endpoint is configurable to any OpenAI-compatible API, including local model servers on the same network, so all data can stay off the public internet. Service installation scripts are included for both Windows (using NSSM) and macOS (using launchd), with automatic restart on failure and log rotation. The full README is longer than what was shown.
A self-hosted agent that watches GitHub repos for new issues, analyzes each one with an AI model, and shows summaries, risk level, and suggested fixes on a dashboard.
Mainly TypeScript. The stack also includes TypeScript, Bun, React.
The full README is longer than what was shown, so license terms are not confirmed here.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.