CodeGate
A fully automated multi-agent AI code review system that triggers on every GitHub Pull Request, runs four specialist AI agents (Security, Quality, Testing, Docs) plus an Orchestrator AI, and delivers a PASS / WARN / BLOCK decision with inline PR comments in under 10 seconds — zero human intervention required.
5 (4 specialist + 1 orchestrator)
AI Agents
$0 /month (free API tiers)
Operating Cost
<10 seconds end-to-end
Review Time
5 (4 specialist + 1 orchestrator)
AI Agents
$0 /month (free API tiers)
Operating Cost
Overview
CodeGate is a fully automated, multi-agent AI code review pipeline built inside n8n. Every time a Pull Request is opened or updated on GitHub, CodeGate wakes up automatically, dispatches the diff to four specialist AI agents — Security, Quality, Testing, and Docs — then sends all four reports to a fifth Orchestrator AI that merges duplicate findings, sorts by severity, computes a PASS / WARN / BLOCK decision, and posts the result back to the PR with inline comments and a commit status check — all within 6–10 seconds, zero human intervention required.
Technical Architecture
The complete pipeline runs in under 10 seconds from GitHub webhook receipt to commit status posted — fast enough that the developer sees the result before they've finished reading the PR description they just wrote.
GitHub Webhook Trigger
PR opened / synchronize / reopened
Validate & Extract
Rejects drafts, bots, non-PR events
Process Diff
Filter noise, format diff, docs-only short-circuit
Build Agent Prompts
Creates 4 specialist items from one diff
AI Agent Reviews
Groq primary · Gemini fallback · runs 4×
AI Orchestrator
Merges findings · scores · writes summary
GitHub API Actions
PR comment · inline review · commit status · label
Slack Alert
Fires on BLOCK decisions only
4-Specialist Agent System
Security agent hunts for hardcoded secrets, injection flaws, and weak crypto. Quality agent checks logic errors and edge cases. Testing agent flags missing unit tests. Docs agent verifies docstrings and changelog entries. Each agent's system prompt explicitly forbids it from commenting outside its domain — eliminating duplicate findings before the Orchestrator even runs.
Dual-AI Failover Architecture
Groq (llama-3.3-70b-versatile) is the primary inference provider — fast, free, and capable. The n8n HTTP Request node is configured with `onError: continueErrorOutput`, which routes any Groq failure silently to Gemini 1.5 Flash. This means the pipeline has two independent AI providers and never returns an empty review.
GitHub API Integration
Four sequential GitHub REST API v3 calls complete the loop: POST /issues/{pr}/comments (summary), POST /pulls/{pr}/reviews (inline line comments), POST /statuses/{sha} (✅/❌ check that blocks or allows the merge button), and POST /issues/{pr}/labels (ai-reviewed / needs-changes / security-flag).
Decision & Scoring Logic
BLOCK: any critical finding, or 2+ high findings. WARN: 1 high finding, or 3+ medium findings. PASS: only low/info findings or none. Score (0–100) is AI-computed by the Orchestrator based on severity and count. BLOCK triggers a Slack incoming webhook alert to the team channel.
Performance Benchmarks
REVIEW TIME
<10 seconds
AI AGENTS
5 total
GITHUB API CALLS
4 per PR
OPERATING COST
$0 / month
Results & Impact
Zero-Cost CI Gate
Runs entirely on free API tiers (Groq + Gemini + n8n Cloud) — $0/month operating cost while delivering production-grade automated code review on every PR.
5-Agent Review Coverage
Security vulnerabilities, logic errors, missing tests, and outdated documentation are all flagged in a single sub-10-second pipeline run — four specialist perspectives plus one orchestrator.
Native GitHub Integration
PR summary comments, inline line-level code annotations, commit status checks (blocking merge on BLOCK), and automatic label assignment — all via the GitHub REST API.
“Code review in 10 seconds. Four specialists. Zero cost.”
Up next — JobGenieAI