System 01 · Diagnostic

Audit engine

A crawl, an issue taxonomy and a priority model, wired end to end. It produces the same artifacts every run — which is the only reason the numbers are comparable month to month.

Crawl engineHeadless, issue-classified
Default cadenceMonthly, weekly on Accelerate
Runs onOur cloud, or yours
Data ownerYou, on every plan
Architecture

Three layers, so the guessing stays in one of them.

Directive

What to do

The SOP, written down. Goals, inputs, the tools to use, the outputs and the edge cases — in plain language, versioned like code. When we learn an API limit the hard way it gets written here, so it is never learned twice.

Orchestration

Decision-making

The only probabilistic layer. It reads the directive, calls the tools in order, handles the errors and asks when something is genuinely ambiguous. It does not do the work itself.

Execution

Doing the work

Deterministic scripts. Same input, same output, every run. Ninety per cent accuracy per step is fifty-nine per cent over five, so anything that must be right lives down here instead.

Data flow

In, through, out.

Sources
Sitemap, expanded from the index
Search Console impressions & coverage
Analytics sessions & conversions
Backlink profile by URL
Field & lab performance data
Process
  1. Crawl mobile, then desktop
  2. Store raw and rendered HTML
  3. Map every issue to a normalised type
  4. Enrich each one with real traffic
  5. Score severity × impact × coverage
  6. Assemble the narrative from the data
Artifacts
Classified issue set, machine-readable
Priority fix list with acceptance criteria
Drill-down sheet, one row per URL
Audit deck and PDF
Tasks filed in your tracker

The rendered-HTML step is the one that earns its place. Comparing raw against rendered is how you catch a page whose canonical, title or primary copy only exists after JavaScript runs — invisible to a crawler, and invisible to any audit that only looks at the finished page.

Integrations

It reads your stack. It doesn't replace it.

Search ConsoleAnalytics 4Headless crawlerKeyword & backlink dataField performance (CrUX)Lab performance (Lighthouse)Tag ManagerWordPressShopifyWebflowClickUpGoogle Drive & SlidesLooker Studio

Read-only wherever read-only is enough. Nothing gets write access it doesn't need, and every write is logged.

Quality gates

A run either passes, or it doesn't ship.

The crawl returned more than zero URLs, and the URL count is within range of the sitemap.

The issues export is present and parsed — an empty taxonomy fails the run rather than producing a clean-looking report.

Every artifact uploaded and confirmed. A partial run is a failed run.

If a gate fails, the pipeline halts and files the error. It does not retry blindly, and it does not hand you a report built on half a run.

Datasheet

The boring details.

SpecStandardDeployable
Where it runsOur infrastructureYours
Who holds the API keysUs, scoped per clientYou
CadenceMonthly, or weeklyAny schedule
Raw data retentionRebuilt each runYour policy
Artifact deliveryYour Drive and trackerYour choice
Source code accessFull
Runs unattendedYesYes
Failure alertingSlack and emailYour channels
The other systems

Same architecture, different job.

Want it in your own stack?

Deployable hands over the software, the hosting and the keys. You run it; we stay on for support.

Talk scope