ClineShield

Inspiration

We built ClineShield because AI coding agents like Cline are genuinely impressive, but they can feel like handing your codebase to someone and just hoping for the best. There's no clear view into what's being changed, why, or how risky it is. Current tools give you the end result but none of the context, and by the time something breaks, tracing it back is a nightmare. We wanted to keep the speed and power of AI-assisted development without the anxiety that comes with it, so we built the visibility layer that should have existed from the start.

What it does

ClineShield wraps Cline's AI actions with real-time guardrails, automatically flagging or blocking risky edits before they hit your codebase. It tracks every change through a live dashboard and color-coded change map so you always know what your AI touched and how dangerous it was. Think of it as a seatbelt for AI-assisted development.

How we built it

We built ClineShield as a VS Code extension that sits on top of Cline and watches everything it does in real time. Whenever Cline tries to edit a file, run a command, or make an API call, our system intercepts it first, scores how risky it is, and decides whether to let it through or block it. We used TypeScript and the VS Code extension API to build the dashboard and change map, keeping everything lightweight so it wouldn't get in the way of the actual development workflow. The change map pulls from the action logs we collect throughout the session and turns them into a simple, visual overview of where Cline has been and what it changed.

Challenges we ran into

The biggest challenge was intercepting Cline's actions reliably without disrupting its workflow. Being too aggressive would block legitimate edits, but being too lenient defeated the purpose entirely. Defining what actually counts as "risky" was harder than expected, and getting the change map to update cleanly in real time took more iteration than we anticipated.

Accomplishments that we're proud of

We're proud of building a system that actually works in real time without getting in the way of the development flow. The change map turned out better than we expected, taking raw action logs and turning them into something visually useful and immediately actionable. Most of all we're proud of tackling a problem that not many people are talking about yet, bringing transparency to AI assisted development before it becomes a bigger issue.

What we learned

We learned that building on top of an agentic AI system is a completely different challenge than traditional software development. You're not just handling user input anymore, you're trying to reason about intent and risk in real time, which forces you to think differently about system design. We also learned that visibility and trust are just as important as functionality when it comes to AI tools, and that developers genuinely want more control over what their AI is doing, they just haven't had a good way to get it until now.

What's next for ClineShield

Next for ClineShield is expanding the hook system to cover a wider range of Cline's actions and improving the risk scoring to be smarter about context, so fewer false flags get in the way of real work. We also want to make the change map more interactive, letting developers drill deeper into specific edits and compare changes across sessions. Long term the goal is to make ClineShield the standard safety layer for any AI coding agent, not just Cline.