Finding authentic, relevant open-source projects to contribute to is overwhelming—especially during Hacktoberfest. My close friend and college peer was stuck in endless repository searches: filtering through dead repositories, outdated labels, non-reproducible environments, and ambiguous issue descriptions. Every October, contributors want to dive in, but they spend 80% of their time scouting for issues that match their exact stack and experience level, only to hit a wall.
To solve this, I built Scout—an intelligent, autonomous open-source triage and scout companion designed to discover, inspect, and evaluate open-source opportunities tailored to a developer's specific skillset.
Instead of treating issue discovery as basic keyword matching, Scout uses open-source AI to act as a personal code scout:
Experience Scout in action:
The complete source code for Scout is open source and hosted on GitHub:
Single-file desktop app for finding GitHub issues you can actually do. Written in V.
Setup (once, or after updating the webview module) v ~/.vmodules/ttytm/webview/build.vsh (Linux/macOS) v %USERPROFILE%.vmodules\ttytm\webview\build.vsh (Windows PowerShell)
Install deps: v install ttytm.webview Linux also needs: sudo apt install libgtk-3-dev libwebkit2gtk-4.0-dev Build: build.bat (Windows) or ./build.sh (Linux/macOS) Run: Scout.exe or ./Scout — opens in its own native window, no browser, no console Run: Scout.exe (opens its own window, no browser tabs to manage)
Data (keys, skills, issues) is stored in a data\scout.db folder next to Scout.exe — copy or move the whole Scout folder and your data goes with it, same as a portable app. If that folder can't be written to (e.g. Scout sits in Program Files), it falls back to %APPDATA%\Scout\scout.db
The server listens only on 127.0.0.1:8787. The UI is embedded in the exe.
Everything is entered in the app: tokens, skills you know, skills you…
Feel free to star, fork, and inspect the architecture.
Scout was architected with a strict focus on minimalism, raw compiled execution speed, open-weight language models, and zero platform lock-in.
Generate structured, step-by-step contribution roadmaps for the user.
Open-Weight Intelligence via Groq (GPT-OSS-120B): Scout leverages GPT-OSS-120B, a powerful open-weight language model, accessed through Groq's LPU inference API. This delivers near-instantaneous token generation speeds for issue summarization, diff explanations, and codebase triaging without waiting on high-latency proprietary backends.
BYOK (Bring Your Own Key) Architecture: Scout operates on a transparent, client-side BYOK model. Users provide their own API credentials directly. No user requests or repository tokens pass through an intermediary backend proxy, guaranteeing complete user ownership, zero vendor lock-in, and zero operational markup.
Embedded State with SQLite (No Heavy Vector DBs): Instead of introducing the overhead and operational friction of standalone vector databases, Scout uses an embedded SQLite engine. SQLite manages structured schema caching, repository metadata indexing, local history, and state tracking directly on disk with zero external dependencies.
When building developer tooling—especially tools meant for the open-source community—relying on closed, proprietary AI APIs is counter to the mission: