The repair loop

From finding to fix, in one place.

Most AI visibility tools stop at the diagnosis. SurfaceGX closes the gap with a four-step loop that ends with a deployed, verified fix rather than a slide deck.

01 · scan
Read every surface
02 · diagnose
Root-cause diagnosis
03 · repair
Developer-ready artifact
04 · confirm
Re-scan to verify
Most tools stop after step 02.
Read across the surfaces that answer for you:
ChatGPT Claude Gemini Perplexity Google AI Overviews
Step 01

Scan: Read every surface

Before anything can be fixed, every machine-readable layer needs to be read. The scan step covers fetchability, crawler access, canonicals, robots.txt and sitemap configuration, discovery files (llms.txt), and structured data, across owned pages and third-party retrieval surfaces.

Surface Audit · M.01

What runs

  • Fetchability and render checks per URL
  • Crawler access: GPTBot, ClaudeBot, OAI-SearchBot, Google-Extended
  • Canonical, robots.txt, and sitemap integrity
  • Discovery file presence (llms.txt, ai.txt)
  • Structured data and schema coverage
Crawler Observatory · M.06

Also running

  • Classifies AI bots from your server logs
  • Shows which priority pages GPTBot, ClaudeBot, and others actually requested
  • Surfaces crawl gaps between what you expect and what engines fetch
Step 02

Diagnose: Find the root cause

A score drop tells you nothing. Diagnosis separates retrieval failures (the engine never fetched the right page) from interpretation failures (it fetched and misread), then links each finding to a specific fix. This is where most tools stop.

Engine Diagnosis · M.02

What runs

  • Asks each engine what it retrieved from your pages
  • Separates retrieval failures from interpretation failures
  • Identifies which assets visibility-critical pages depend on
  • Pinpoints which engines can and can't reach your content
Hallucination Risk Engine · M.05

Also running

  • Pressure-tests regulated claims against engine outputs
  • Flags risky statements before they become citations
  • Surfaces safer language with supporting evidence
Step 03

Repair: Developer-ready artifacts

Every finding ships as something deployable: a Fix Card, a robots.txt change, a schema/JSON-LD patch, an llms.txt file, a content brief, or a GitHub pull request against your actual repo. Engineers merge it instead of translating it.

Content Repair · M.03

Interpretation gap fixes

  • Writer-ready briefs for each interpretation failure
  • Each brief cites the specific engine that misread the content
  • Answer-first snippets tuned per surface (voice, chat, AI Overviews)
Engineering Handoff · M.04

Infrastructure fixes

  • Fix Cards with the exact code change required
  • Brand manifests and crawler discovery files
  • Schema/JSON-LD patches scoped to failing pages
  • GitHub PRs opened against your repos for engineers to merge
Step 04

Confirm: Re-scan to verify the fix landed

Shipping the fix is not the end. SurfaceGX re-runs the scan against the same pages after repairs are merged, confirming the finding is resolved and the score has moved. Repairs are kept accountable.

Progress & Reporting · M.07

What runs

  • Re-scan confirms deployed fixes resolved the finding
  • Trends score movement over time
  • Keeps repairs accountable with before/after evidence
  • Packages results for stakeholder reporting
The loop

Then it starts again

  • AI engines re-crawl on their own schedules
  • New content means new surfaces to read
  • SurfaceGX monitors continuously so fixes don't regress
Under the hood

The full repair stack

Six diagnostic engines and a reporting layer feed the loop. Most teams never think about them; they just merge the fixes. For the technical buyer who wants the depth, here's what's running.

ScanM.01

Surface Audit

Scores fetchability, crawler access, canonicals, robots/sitemap, and discovery files across every owned and retrieval surface.

UnderstandM.02

Engine Diagnosis

Asks each engine what it retrieved, separating retrieval failures from interpretation failures.

FixM.03

Content Repair

Turns interpretation gaps into writer-ready briefs, each citing the engine that misread you.

ShipM.04

Engineering Handoff

Ships Fix Cards, manifests, and GitHub PRs against your repos. Engineers merge them instead of translating them.

ComplyM.05

Hallucination Risk Engine

Pressure-tests regulated claims, flags risky statements, and surfaces safer language with evidence.

ObserveM.06

Crawler Observatory

Classifies AI bots from your logs and shows which priority pages GPTBot, ClaudeBot, and others actually requested.

TrackM.07

Progress & Reporting

Trends score movement, keeps repairs accountable, and packages results for stakeholders.

Want the deep version?

Definitions, evidence ledger, and the full methodology live in the docs.

Read the docs →

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