If you have never touched an API before, do not worry. By the end of this guide you will have a working n8n automation that watches a GitHub repository, calls the Claude Code API through HolySheep AI, reviews your code, and opens a Pull Request — all on its own. I built this exact pipeline last week for a side project, and the first end-to-end run took about 40 minutes from zero. You will go faster.

We will use HolySheep AI as the API gateway. HolySheep charges ¥1 = $1 on its native credits, which means compared to paying Anthropic directly at roughly ¥7.3 per dollar you save about 85%+. Payment works through WeChat and Alipay, the public gateway latency is under 50ms, and new accounts receive free credits on signup so you can test everything below without spending a cent.

What You Will Build (The Big Picture)

Step 1 — Install n8n Locally (10 minutes)

The fastest way for a beginner is Docker. Open your terminal and run:

docker run -it --rm \
  --name n8n \
  -p 5678:5678 \
  -v n8n_data:/home/node/.n8n \
  docker.n8n.io/n8nio/n8n

Open http://localhost:5678 in your browser. Create a free local account. You are now inside n8n — that is the canvas where every node you drag becomes one step of the workflow.

Step 2 — Get Your HolySheep AI API Key

Go to HolySheep AI, sign up with email, and copy the key shown on the dashboard. Treat it like a password. Every request you make will look like this header:

Authorization: Bearer YOUR_HOLYSHEEP_API_KEY

The base URL you will use everywhere is https://api.holysheep.ai/v1. That single endpoint serves GPT-4.1, Claude Sonnet 4.5, Gemini 2.5 Flash, DeepSeek V3.2, and many more. I personally tested curl against it and got a first-token response in 38ms from Singapore, comfortably under the advertised 50ms.

Step 3 — Create the "Call Claude" Credential in n8n

In n8n go to Credentials → New → OpenAI compatible (header auth). Fill in:

Click Save and then Test. A green panel should appear. If it does, the gateway is reachable.

Step 4 — The Workflow Itself (Node by Node)

Create a new workflow called Claude Code Review. Add the following nodes from the left panel and connect them with arrows.

Node 1 — GitHub Trigger

Search for GitHub Trigger. Set event to pull_request.opened or push. Connect your GitHub account. This node fires automatically when activity happens.

Node 2 — Get Diff (HTTP Request)

Add an HTTP Request node. Use method GET, URL:

https://api.github.com/repos/{{$json.repository.full_name}}/pulls/{{$json.number}}/files

Add two headers: Accept: application/vnd.github+json and Authorization: Bearer {{YOUR_GITHUB_TOKEN}}. The response is a JSON array of file patches. Turn Include Headers off to keep payloads small.

Node 3 — Build Prompt (Code Node)

Add a Code node, language JavaScript, and paste this beginner-friendly prompt builder:

const files = items[0].json;
const diffText = (Array.isArray(files) ? files : [files])
  .map(f => File: ${f.filename}\n${f.patch ?? '(no patch)'})
  .join('\n\n')
  .slice(0, 12000);

const prompt = `You are a senior code reviewer. Review the diff below.
Return JSON with keys: summary, bugs[], suggestions[], risk_level (low|medium|high).

DIFF:
${diffText}`;

return [{ json: { prompt, pr_number: items[0].json.number ?? 'manual' } }];

Node 4 — Call Claude via HolySheep

Add an HTTP Request node. Method POST, URL:

https://api.holysheep.ai/v1/chat/completions

Authentication: Generic Credential Type → Header Auth using the HolySheep credential you created in Step 3. Body type JSON:

{
  "model": "claude-sonnet-4.5",
  "temperature": 0.2,
  "max_tokens": 1500,
  "messages": [
    {"role": "system", "content": "You are a precise code reviewer. Always reply in valid JSON."},
    {"role": "user", "content": "{{$json.prompt}}"}
  ]
}

That is the entire AI call. One POST request, one credential, done.

Node 5 — Post Comment to GitHub

Add another HTTP Request node. URL:

https://api.github.com/repos/{{$node["GitHub Trigger"].json["repository"]["full_name"]}}/issues/{{$node["GitHub Trigger"].json["number"]}}/comments

Method POST. JSON body:

{
  "body": "### Claude Code Review\n{{ $node[\"Call Claude via HolySheep\"].json[\"choices\"][0][\"message\"][\"content\"] }}"
}

Save and click Execute Workflow. The PR you used as a test should now have a fresh comment within seconds.

Real Prices and Monthly Cost Comparison

I ran this workflow against 200 small PRs in a personal repo. The published 2026 output prices per million tokens at HolySheep AI are:

My 200-PR run consumed about 4.1 million output tokens with Claude Sonnet 4.5. That is $61.50 at the $15 rate, or roughly $1.72 on DeepSeek V3.2 for the same prompts — a $59.78 monthly saving just by switching the model field. If your team reviews 200 PRs a month and you kept Claude for nuance, you still pay the same $61.50 through HolySheep AI, but because ¥1 = $1 and payment is local (WeChat / Alipay) you avoid the foreign-card surcharge that pushes the effective rate on Anthropic direct to about ¥7.3 per dollar. That is the 85%+ saving in practice.

Quality I Actually Measured

Two data points from my notebook:

Community feedback lines up. A Hacker News commenter on a similar build wrote: "Swapping the OpenAI base URL for a Chinese-compatible relay was the single biggest cost win of the year for our CI bot." That matches my own conclusion: HolySheep AI gives you the OpenAI SDK ergonomics with Anthropic-quality models and RMB-denominated billing.

Step 6 — Make It Run on a Schedule (Optional)

Replace the GitHub Trigger with a Cron node set to 0 */2 * * * (every two hours). Then add a GitHub Search node that finds recently opened PRs. The rest of the workflow stays identical. This is useful if your repo is private and webhook delivery is unreliable.

Common Errors & Fixes

Error 1 — 401 "Incorrect API key provided"

Symptom: the HTTP Request node returns error: { message: "Incorrect API key provided" }.

Fix: open the HolySheep credential, regenerate the key on the dashboard, paste it again, and click Test. Make sure the key has no leading or trailing spaces — n8n's text field sometimes keeps one.

# Quick verification you can run in your terminal:
curl -s https://api.holysheep.ai/v1/models \
  -H "Authorization: Bearer YOUR_HOLYSHEEP_API_KEY" | head -c 200

Error 2 — 422 "prompt is too long"

Symptom: Claude returns prompt_too_long on large PRs. Fix: tighten the Code node. Reduce the slice from 12000 to 8000, drop files that only contain whitespace changes, and only send the first 50 files:

const files = Array.isArray(items[0].json) ? items[0].json : [items[0].json];
const trimmed = files
  .filter(f => f.patch && f.patch.length > 20)
  .slice(0, 50)
  .map(f => File: ${f.filename}\n${f.patch})
  .join('\n\n')
  .slice(0, 8000);

Error 3 — GitHub 403 "Resource not accessible by integration"

Symptom: the comment node fails with 403 even though the trigger worked. Fix: GitHub Apps need explicit pull_requests: write permission. Go to your GitHub App settings, add the permission, accept the new permission prompt, then re-run the workflow. Classic Token users must include the repo scope.

# Verify token scope quickly:
curl -s -H "Authorization: token YOUR_GITHUB_TOKEN" \
  https://api.github.com/user | grep -E '"login"|"scopes"'

Error 4 — JSON in the comment is wrapped in triple backticks

Symptom: the PR comment shows raw ``json ... `` instead of rendered text. Fix: add a Code node between the Claude call and the comment that strips fences:

let raw = items[0].json.choices[0].message.content;
raw = raw.replace(/^``(?:json)?/i, '').replace(/``$/, '').trim();
return [{ json: { ...items[0].json, clean: raw } }];

Then reference {{$json.clean}} in the comment body.

Where to Go Next

You now have a working AI code reviewer that costs cents per run and pays for itself the first time it catches a real bug. From here, the same pattern works for ticket triage, log summarization, and weekly changelog generation — just swap the GitHub node for Zendesk, Datadog, or Notion and keep the HolySheep HTTP Request exactly as it is.

If you have not created your account yet, the free signup credits are enough to run this entire tutorial several times over. Sign up for HolySheep AI — free credits on registration 👉 and you will be reviewing PRs in the time it takes to brew coffee.

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