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Better tools made Copilot code review worse. Here’s how we actually improved it.

Napalys Klicius 2026年07月10日 23:57 2 次阅读 来源:GitHub Blog

How migrating Copilot code review to shared Unix-style code exploration tools reduced review cost by reshaping agent workflows around pull request evidence. The post Better tools made Copilot code review worse. Here’s how we actually improved it. appeared first on The GitHub Blog .

Give an agent better tools and it should do better work. That’s the instinct, anyway. When you open a pull request, Copilot code review reads the diff and explores the surrounding code to find the problems that matter before they ship. To do that, it used its own code exploration tools. So when we swapped in the better-maintained, shared tools that power the Copilot CLI, grep , glob , and view , we expected a clean upgrade. Instead, in our benchmarks, we found that the cost of reviews was higher and fewer issues were being caught. But the tools weren’t the problem. The instructions were. Once we rewrote them for the way a reviewer actually reads a pull request, the regression flipped into a win: roughly 20% lower average review cost , while maintaining the same review quality. This is the story of how adjusting the workflows around the tools led us to a fix. Same tools, wrong instincts If you’ve built on top of an agent framework, you’ve probably inherited its tools too. They work, so you keep them, until the day your use case drifts far enough from what they were designed for that they quietly start working against you. That’s the situation we were in. Before trying to use the shared CLI tools, Copilot code review used its own code exploration tools. That tool layer was inspired by earlier agentic systems, including ideas from SWE-agent-style repository navigation and GitHub Copilot Autofix : list directories, search files, search directories, and read code. Those tools worked, but they were specific to Copilot code review, and they were designed for how models behaved at the time. Earlier agentic coding models made fewer tool calls and were worse at automatically pulling in necessary context. This meant it was more important to include all relevant information in the few tool calls that the model made. Meanwhile, the Copilot CLI harness has a shared set of Unix-inspired code exploration tools: grep, glob, and view. That harness is also used by a growing number of
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