How Our AI SEO Audit Agent Actually Works

We built an AI agent that runs a full SEO audit on any e-commerce site. Crawl every page, pull Search Console data, cross-reference, and produce a prioritised report. All in one session.

This is how it works under the hood.

Three data sources, one agent

The SEO audit agent connects three things:

1. Crawl data. The agent crawls the site programmatically. Every page. Extracts title tags, meta descriptions, H1s, image alt attributes, canonical tags, internal links, page speed metrics, and schema markup. For a 300-page site, this takes 2-3 minutes.

2. Google Search Console API. Real performance data. Which pages get impressions. Which keywords drive clicks. Which pages have high impressions but low CTR (meaning the title/description needs work). Which pages have dropped in position over the last 90 days.

3. Claude Code. The AI layer that analyses both datasets together. This is where it gets interesting. The agent doesn't just list problems. It cross-references crawl issues against actual search performance.

A page with a duplicate title tag that gets zero impressions is low priority. A page with a duplicate title tag that gets 2,000 impressions per month and a 1.2% CTR is urgent. The agent knows the difference.

What the agent produces

The output is a structured report with five sections:

Critical issues. Problems that are actively costing traffic right now. Keyword cannibalisation between high-impression pages. Missing schema on top-performing products. Broken canonical tags causing indexing problems.

High impact fixes. Issues that would produce measurable results within 4-6 weeks. Duplicate meta titles on indexed pages. Missing alt text on product images in categories where image search drives traffic.

Content opportunities. Keywords where the site has impressions but no dedicated page. Related keywords that existing pages could target with minor content updates.

Technical debt. Slower-burn items. Page speed improvements. Internal link structure. Orphaned pages with no internal links pointing to them.

Monitoring plan. Which metrics to track weekly. Which pages to re-check in 30 days. Specific Search Console queries to watch.

Why this beats traditional SEO audits

Traditional SEO audits have two problems.

Coverage. A human auditor reviews a sample of pages. Maybe 20-50. They miss things. Our agent crawls every page. Every image. Every meta tag.

Context. Screaming Frog can crawl your site and list every issue. But it can't tell you which issues matter. It doesn't know that your "gold vermeil earrings" page gets 3,000 impressions a month and deserves a better title tag. The AI agent connects crawl data to business impact.

The result is an audit that takes minutes instead of days and prioritises by revenue impact rather than alphabetical order.

See what we found on a real DTC audit or the before/after results.