Continue

Continue adds automated quality control to your pull request workflow by running AI checks you define directly in your repo. You write the checks as Markdown files, commit them alongside your code, and Continue enforces them on every PR as native GitHub status checks. When code misses the mark, it surfaces suggested fixes inline.

The core idea is specificity. Unlike generic AI code reviewers that surface unsolicited opinions or broad style feedback, Continue only enforces what you've explicitly told it to catch. That means no surprise flags, no noise, and no drift from your actual standards.

Key capabilities:

• Source-controlled checks written in Markdown, versioned with your codebase so standards evolve alongside the code
• Native GitHub status checks that integrate directly into your existing PR workflow without separate dashboards
• Suggested fixes delivered when a check fails, reducing back-and-forth between author and reviewer
• Consistent enforcement across every PR, regardless of who wrote the code or how fast the team is shipping

It's built for engineering teams that have already defined what good looks like and want that enforced mechanically, not left to whoever has bandwidth for review. The checks cover areas like security, code reuse, and custom standards your team sets.

Tools like CodeRabbit or Qodo take a broader approach to AI review. Continue's value is the opposite: narrow, deliberate, and fully under your control. Your standards, your checks, your call on what gets enforced.