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Code Review & Testing Automation

Use Internal agents with GitHub integration and event flows to review PRs, triage issues, and run checks in a sandbox.

Typical use: Auto-comment on new PRs, label GitHub issues, or run sandbox tests when pull_request.opened fires.


Engineering teams struggle with:

  • PR review bottlenecks - Developers wait days for reviews
  • Inconsistent code quality - Style and patterns vary across team
  • Missing tests - Test coverage gaps lead to production bugs
  • Manual issue triage - Hours spent categorizing and prioritizing
  • Documentation debt - Code changes without doc updates

The cost:

  • Slower deployment cycles
  • More bugs in production
  • Developer frustration
  • Technical debt accumulation

Auteryn code agents integrate with your GitHub workflow to automate reviews, generate tests, and maintain quality—without slowing down your team.

Automated PR Review

Review every PR for style, security, performance, and best practices. Instant feedback.

Test Generation

Generate unit tests, integration tests, and edge case coverage automatically.

Issue Triage

Categorize, label, and prioritize GitHub issues. Route to the right team.

Documentation Sync

Update docs automatically when code changes. Keep everything in sync.

Security Scanning

Detect vulnerabilities, secrets in code, and security anti-patterns.

Persistent Sandbox

Agent maintains full codebase context across sessions. No re-indexing.


  1. Connect GitHub

    Install the Auteryn GitHub App. Grant permissions for repos you want automated.

  2. Configure Review Rules

    Define what the agent should check: style, tests, security, performance, documentation.

  3. Activate on PRs

    Agent automatically reviews every new PR and posts feedback as comments.

  4. Generate Tests

    Agent identifies missing test coverage and generates tests for approval.


Create a GitHub event flow on pull_request.opened that connects a code-reviewer Internal agent. The agent reads the diff, posts review comments, and optionally runs sandbox checks.


The agent checks for:

  • Style consistency - Follows your team’s conventions
  • Best practices - Language-specific patterns
  • Security issues - SQL injection, XSS, secrets in code
  • Performance - Inefficient algorithms, memory leaks
  • Test coverage - Missing tests for new code
  • Documentation - Missing or outdated comments

Unlike simple test generators, Auteryn agents:

  • Understand your codebase architecture
  • Follow your testing patterns
  • Generate realistic test data
  • Cover edge cases and error paths
  • Maintain test consistency

The agent’s persistent sandbox means:

  • Full codebase indexed - Understands all dependencies
  • No re-indexing - Instant context on every PR
  • Cross-PR learning - Remembers patterns from previous reviews
  • Faster execution - No cold start delays

GitHub

Native GitHub App integration. Automatic PR reviews, issue triage, and more via event flows.

Jira / Confluence

Sync issues, update tickets, and track progress via the native Atlassian integration.

Slack

Get notified of reviews, approve tests, and interact with agent.

GitLab (via sandbox / MCP)

Review merge requests by calling the GitLab API/CLI from the sandbox or a Custom MCP adapter. No native connector.

Other CI (via sandbox / MCP)

Drive CircleCI, Jenkins, or GitHub Actions from the sandbox or Custom MCP with your credentials.

Custom Tools

Connect your internal tools via Custom MCP or webhooks.


Code automation scales with your team:

  • Free: $0/month — 1,000 credits
  • Pro: $29/month — 15,000 credits ($24/mo billed annually)
  • Business: $99/month — 60,000 pooled credits ($83/mo billed annually)
  • Enterprise: Custom pricing for large teams

Actual PR-review volume depends on diff size and how deeply each review runs. See Pricing for full plan limits and credit rates.


  1. Sign up free - No credit card required

  2. Install GitHub App - One-click installation

  3. Use code review template - Start with our pre-built skill

  4. Configure rules - Customize what the agent checks



  • What languages are supported? Python, JavaScript/TypeScript, Java, Go, Ruby, PHP, and 20+ more.
  • Can it review large PRs? Yes, the persistent sandbox handles codebases of any size.
  • How accurate are the reviews? Quality depends on the model tier and your review rules; you review and approve every suggestion.
  • Can I customize review rules? Absolutely. You control what the agent checks and how strict it is.
  • What if it suggests wrong changes? You review and approve all suggestions. The agent learns from your feedback.

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