Clean workflow design. Connected our stack in one afternoon. Minor learning curve on variables.
+ AI quality exceeded expectations · Saved our team 10+ hours weekly
GPT analyzes PR diffs for bugs, security issues, and style with inline suggestions.
This automation starts when gitHub `pull_request` opened or synchronize webhook. It webhooks pull_request and openai pull_request, then severity tagged, blocks merge label `ai-review-failed` if critical found until human dismiss. AI handles generation and decision logic in the middle of the flow.
Read-only visualization of how data moves from trigger to final result.
GitHub `pull_request` opened or synchronize webhook
GitHub pull_request webhook sends unified diff to GPT-4o with repo coding guidelines from `.cursor/rules` or CONTRIBUTING.md, posts review comments on suspiciou
GitHub pull_request webhook sends unified diff to GPT-4o with repo coding guidelines from `.cursor/rules` or CONTRIBUTING.md, posts review comments on suspiciou
severity tagged, blocks merge label `ai-review-failed` if critical found until human dismiss.
Pull_request
Pull_request
Pull_request
Remove repetitive steps from AI Code Review so your team focuses on high-value work.
Connected apps sync data automatically instead of copy-paste between dashboards.
Standardized logic runs the same way every time, with retries on failure.
Events trigger immediate actions instead of waiting for someone to check a queue.
Automation runtime
Connect required apps via OAuth or API keys. Credentials are encrypted server-side. Dev test runs mock external actions when connections are missing.
Est. setup time: ~6 min
Webhook trigger
Activate this workflow to provision the trigger endpoint.
No runs yet. Install the template and run a test, or activate to receive webhook/schedule runs.
GitHub pull_request webhook sends unified diff to GPT-4o with repo coding guidelines from `.cursor/rules` or CONTRIBUTING.md, posts review comments on suspicious lines—null dereference, SQL injection, missing error handle—severity tagged, blocks merge label `ai-review-failed` if critical found until human dismiss.
Some steps run in preview until their integrations go live.
GitHub App, fetch diff, load CONTRIBUTING guidelines, OpenAI, review comments API.
Repo CONTRIBUTING and eslint config summary in prompt context.
Critical high medium low; critical blocks merge label.
Line-level comments on diff hunks not generic PR comment only.
First week human tracks false positive rate; tune prompt.
| Variable | Type | Default | Required |
|---|---|---|---|
| Business Name | text | Your Business | Yes |
| Notification Email | — | Yes | |
| Timezone | select | — | Yes |
| Brand Voice | select | Professional | No |
| GitHub Repository | text | No |
You are a senior code reviewer. Analyze diffs for bugs, security vulnerabilities, and style violations per repo guidelines. Comment only on changed lines with severity. No nitpicks unless repeated pattern.
Secret pattern scan runs before sending to LLM; abort if found.
Skip or chunk review if >500 lines changed.
Human dismiss adds pattern to ignore list file.
Enterprise OpenAI no-retention endpoint recommended.
Our team can adapt this template to your exact workflow, apps, and brand requirements.
49 total reviews
Clean workflow design. Connected our stack in one afternoon. Minor learning curve on variables.
+ AI quality exceeded expectations · Saved our team 10+ hours weekly
After two weeks live, AI Code Review has become core to our daily ops. Verified install — runs without babysitting.
+ Support team helped customize quickly · Setup was straightforward
AI Code Review replaced a manual process that took 2 hours daily. ROI was clear within the first month.
+ Scales well as we grow · Integrations worked on first try
GitHub pull_request webhook sends unified diff to GPT-4o with repo coding guidelines from `.cursor/rules` or CONTRIBUTING.md, posts review comments on suspicious lines—null dereference, SQL injection, missing error handle—severity tagged, blocks merge label `ai-review-failed` if critical found until human dismiss.
Activate AI Code Review with default variables and run a sandbox test.
Scenario: New user installs template and validates output in under 15 minutes.
Connect live apps, map business rules, enable monitoring alerts.
Scenario: Team deploys to workspace after QA sign-off on test runs.
Version 1.2.0 — Improved reliability and Slack notifications for AI Code Review.
Current version: 1.2.0
Pull Request Review Summary — orchestrates GitHub, Slack, Jira, Linear to automate this workflow with field mapping, notifications, and audit logging.
Announce deployments to Slack with changelog snippet and rollback instructions.
Generate CHANGELOG entries from merged PRs grouped by conventional commit type.
Post structured PR review checklists and label PRs based on diff analysis.
Post structured PR review checklists and label PRs based on diff analysis.
Generate CHANGELOG entries from merged PRs grouped by conventional commit type.
Announce deployments to Slack with changelog snippet and rollback instructions.
Canva Asset Approval Flow — orchestrates LinkedIn, X, Instagram, Buffer to automate this workflow with field mapping, notifications, and audit logging.
Consolidate tasks from Slack, email, and voice into prioritized Google Tasks and Asana.
Pull Request Review Summary — orchestrates GitHub, Slack, Jira, Linear to automate this workflow with field mapping, notifications, and audit logging.
Inbox Priority Briefing — orchestrates Gmail, OpenAI, Google Calendar, Slack to automate this workflow with field mapping, notifications, and audit logging.