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continuedev/continue

📈 Trending33,256TypeScriptAudience · developerComplexity · 3/5ActiveLicenseSetup · moderate

TLDR

AI-powered code review automation that runs checks on every pull request using rules you define in text files, flagging issues and suggesting fixes automatically.

Mindmap

mindmap
  root((Continue))
    What it does
      Automated code review
      PR status checks
      Suggests code fixes
    How to use
      Write check files
      Store in .continue folder
      Runs on pull requests
    Tech stack
      TypeScript
      Large language models
      GitHub integration
    Use cases
      Enforce security rules
      Validate API endpoints
      Catch style violations
    Audience
      Development teams
      Code quality focused
      CI/CD workflows

Things people build with this

USE CASE 1

Automatically catch hardcoded API keys and security antipatterns in every pull request.

USE CASE 2

Enforce consistent input validation and error handling across new endpoints without manual review.

USE CASE 3

Define team coding standards once in text files and have them checked automatically on all future changes.

USE CASE 4

Reduce time spent on repetitive code review feedback by flagging common issues with suggested fixes.

Tech stack

TypeScriptGitHub ActionsLarge Language ModelsVS CodeJetBrains IDEs

Getting it running

Difficulty · moderate Time to first run · 30min

Requires LLM API key (OpenAI, etc.) and GitHub Actions workflow configuration.

Use freely for any purpose including commercial. Keep the notice and disclose changes to the patent grant.

In plain English

Continue is a tool that brings automated AI code review directly into your software development workflow, specifically by running checks on every pull request as part of your continuous integration pipeline. The core idea is that you write review criteria in simple text files stored in your repository, and Continue uses AI agents to evaluate whether new code meets those criteria, flagging issues automatically without a human reviewer needing to look at every pull request first. The way it works is straightforward: you create markdown files in a folder called .continue/checks/ inside your project. Each file describes a check, such as "make sure no API keys are hardcoded" or "confirm all new endpoints validate input." When a pull request is opened, Continue runs these checks as GitHub status checks, the same kind of green or red indicators you already see from automated tests. If a check fails, Continue not only marks it red but also suggests a concrete code diff to fix the problem. This is useful for development teams who want consistent code quality standards enforced automatically. Instead of relying on human reviewers to catch the same recurring issues, security antipatterns, missing error handling, style violations, you encode those rules once and the AI enforces them on every future change. Because the checks are just text files in version control, the whole team can contribute to and audit them like any other code. The project includes a command-line tool called the Continue CLI, installable via a shell script or npm, as well as extensions for code editors including VS Code and JetBrains IDEs. The stack is TypeScript, and the system integrates with large language models to power the actual review logic.

Copy-paste prompts

Prompt 1
How do I set up Continue to automatically check for hardcoded secrets in my pull requests?
Prompt 2
Show me how to write a custom check file in .continue/checks/ that validates all new API endpoints require input validation.
Prompt 3
How do I integrate Continue into my GitHub Actions workflow so it runs on every PR?
Prompt 4
Can you help me create a Continue check that flags missing error handling in async functions?
Prompt 5
How do I install the Continue CLI and use it locally before pushing to GitHub?
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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.