--- title: "How an SEO agent works | SEO Skill" description: "An interactive guide to SEO agents. See the evidence an agent works from, the loop it runs, how approval works, and how to measure a change honestly." canonical: "https://seoskill.dev/blog/seo-agent" language: "en" --- # How an SEO agent works An interactive guide. Six small models you can play with, from the evidence an agent can see to the measurement that closes the loop. An SEO agent is an AI agent doing SEO work with real evidence. You ask a question in plain language. It pulls what it needs from a crawl of your site, Search Console, your analytics, and live search results, then finds problems and opportunities, proposes changes, and measures what shipped. This guide shows how that works without assuming you use a terminal. Each section explains one idea, gives you one small model to play with, and says what it means. Most demos use example data from a made-up outdoor gear store, so the numbers hold still while you poke them. Section three is the exception: it replays a real audit of a live site. ## What an SEO agent can see An agent is only as good as the evidence it can reach. Four sources cover most SEO questions, and they answer different things. A crawl reads your pages the way a search engine would. Search Console says what people searched and clicked. Analytics says what visitors did after arriving. Live results say who ranks today. None of them can answer for another, which is the first thing worth feeling for yourself. Interactive demo: one question, "Why did clicks fall on the pricing page this month?", answered from four separate evidence sources. The crawl shows the page is technically fine. Search Console shows clicks fell while impressions held, so the page lost position, not demand. Analytics shows visitor behavior is unchanged, so the drop is in arrivals. Live results show a competitor page now ranks above it. Disconnecting a source removes the claims that depend on it, because one source cannot prove another's facts. This is why "is my SEO good" has no one-source answer. The crawl can be clean while the demand quietly moves to a competitor. Keeping the sources separate is what makes the answer checkable later, when you want to know whether a fix worked. ## An SEO agent works in a loop A chatbot answers and stops. An agent keeps going, and SEO work has a natural shape for it to follow: find something worth acting on, inspect the evidence, propose a change, verify it went live, and measure what happened. The trigger differs. Sometimes it is a problem, like pages that broke in a release. Sometimes it is an opportunity, like search demand with no page answering it. The stages do not change. Interactive demo: the five stages drawn as a closed circuit that an orange line travels around while it plays. Find (a crawl flags broken canonical tags, or Search Console shows unanswered demand), inspect the evidence, propose a change a human can judge, verify the live result after the deploy, and measure equal windows of final data either side of the change. The measurement feeds the next find. That return edge is what makes it a loop rather than a checklist. The last stage is the one people skip, and it is the one that makes the loop worth running. What you measure this month decides what is worth finding next month. ## Watch one investigation Here is the loop run for real. On 10 August 2026 an agent audited [ilo.so](https://ilo.so/), an X analytics site I run, picked what to build from the query evidence, and the work shipped the same day. Press play and keep an eye on the right panel. The question at every step is the same. What can the agent point to? Interactive demo: a step-through of the real audit that ran against ilo.so on 10 August 2026. The owner asks what is worth building. The agent reads 180 days of final Search Console evidence and finds measured demand around X analytics: the follower-count page already earns clicks ("x follower count", 376 impressions at position 5.0), the profile-analytics page earns impressions at positions 11 to 24 with almost no clicks, and no page ranks posts by engagement. It proposes a top-posts ranking tool and expanded tool pages, backed by guides for the impression questions people already search. Two pull requests merge the same day. A post-deploy crawl verifies 115 of 115 pages return 200 and are indexable. The recorded baseline (10,881 clicks and 228,237 impressions for the 28 final days to 7 August) claims nothing about results, because final data cannot yet reflect the changes. The comparison is scheduled for 10 September, and the result gets published either way. Notice what never happens. The agent does not claim the new pages will rank, and it does not mark the job done when the pull requests merge. The baseline records that the new URLs have no search data yet, because none can exist. The check is scheduled for 10 September, and the result becomes a public case study either way. Pointing at evidence, step after step, is what separates an SEO agent from a chatbot with opinions about SEO. ## Evidence changes the answer Data about your site is rarely complete. Search Console finalizes days late. Exports stop at row limits. Crawls go stale while you are busy shipping. A trustworthy agent does not paper over any of this. It changes its wording. Interactive demo: the same click question shown in five data states. Complete data earns a direct claim: clicks fell 61% starting the day after a template release. Partial data earns a caveat, since the last week is still settling. A capped export makes the agent say that rows past the limit are unknown rather than zero. Missing data turns the answer into a request to connect Search Console. A stale export makes the agent ask for fresh data before blaming the release. The state of the evidence changes the wording, not just the numbers. The wording is the tell. A tool that returns the same confident sentence in all five of those states is filling in a template, not reading your data. ## You decide what ships An agent that publishes whatever it likes is a liability. The workable shape is a queue. The agent proposes changes with the evidence attached, and you approve, narrow, or skip each one. Interactive demo: a queue of four proposed changes with Inspect, Narrow, Approve, and Skip actions. Adding missing meta descriptions and fixing dead product pages carry crawl and Search Console evidence. A broad 12-title rewrite can be narrowed to the 3 pages that are actually losing clicks. A keyword-stuffed homepage headline rewrite carries no evidence at all, and skipping it is the point. The agent acts on the approved list only, so nothing ships without a human decision. The queue only works if you use all four buttons. Narrowing a broad change and skipping an unevidenced one are the decisions that keep the site yours. (The keyword headline was in the queue on purpose. Every SEO tool has one of those ideas. You are allowed to say no.) ## Measure the change The loop ends with a comparison: clicks before the change against clicks after. Two rules keep it honest. The windows on either side must be the same length, and the newest days must stay out of the comparison, because search data is not final for several days. Interactive demo: 84 days of example daily clicks with a real step change at day 42. A slider moves the comparison date. The before and after windows stay 21 days each, and the newest 3 days are excluded because Search Console data is not final yet. With the windows around the real change the observed difference is about +30%. Move the date away from the change and the observed difference shrinks, which is the point: the windows show an observed movement, not proof of what caused it. One thing the demo cannot show is causation. The windows show an observed movement. Rankings also move for reasons that have nothing to do with you, which is why the loop verifies the change went live and reports the result either way, up or down. ## Jobs an SEO agent can do The same loop covers most of the SEO work a site needs: - Diagnose a site that lost traffic, and say which evidence supports each suspected cause. - Find queries with real demand and no page answering them. - Improve an existing page against the queries it already earns. - Watch for technical regressions after releases. - Investigate local search results for a place, kept separate from national rankings. - Check how ready pages are for AI search, as observations rather than promises. - Measure a shipped change with equal windows of final data. The [reports guide](https://seoskill.dev/docs/reports) lists every report behind those jobs, and what each one can and cannot prove. ## Try it on your own site Everything in this guide runs locally from one command. Install it, sign in to Search Console during setup, and the first report on your own site is a few minutes away. Install the SEO CLI globally. ``` npm i -g seo ``` Run setup after installation. ``` seo start ``` The [getting started guide](https://seoskill.dev/docs/getting-started) walks through setup, and the [skill page](https://seoskill.dev/docs/skill) covers giving your own agent the same reports through Claude, Codex, and other tools. SEO has always been evidence work. An agent just never gets bored of checking.