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Implementation

We make the fixes, in your codebase or your CMS

An audit nobody acts on is an expensive PDF. We do the work, in your stack, as changes your team can review.

How the work lands

Wherever possible we work directly in your repository and deliver pull requests, scoped small enough to review properly. Your team keeps ownership and veto; nothing lands without your approval. For CMS-driven sites we work in the CMS and document every change we make.

We do not take over your site, we do not install an overlay, and we do not add a script tag that promises to fix things at runtime. Runtime patches are exactly the kind of client-side dependency that causes agent readiness problems in the first place.

What we typically change

At the cheap end: llms.txt, robots directives, security.txt, canonical hygiene, meta and Open Graph coverage, alt text. These are hours of work and they move the score immediately.

In the middle: structured data across templates, heading and landmark structure, form labelling and input types, navigation that uses real anchors, and search that an agent can drive by URL.

At the deep end: rendering architecture. If your content only exists after hydration, no amount of schema will help; the fix is server rendering or prerendering for the routes that matter. This is the most expensive work and the one with the largest score movement, which is why we scope it against your architecture rather than your page count.

Machine endpoints

Most sites score zero on machine endpoints today, because almost nobody publishes one. That makes it the cheapest available differentiation: an agents.json, a documented read-only API with an OpenAPI spec, or an MCP server exposing your catalogue or documentation.

This is genuinely new territory, and we would rather be honest that the standards are still moving than sell it as settled. We build to what is actually being consumed today, and we tell you which parts are a bet.

What you get

  • Reviewable pull requests, or documented CMS changes
  • Re-scan after each batch so movement is visible, not asserted
  • Structured data implemented across templates, not page by page
  • Rendering fixes for the routes that matter commercially
  • Optional: agents.json, OpenAPI spec, or an MCP server
  • Handover notes so your team can maintain it without us
Typical timeline
2–8 weeks, depending on architecture
Investment
Typically $4,000–$25,000

We scope against architecture, not page count. How we price

The rest of what we do

  • Agent readiness audit

    A full audit of what AI agents can and cannot do on your site

    A manual audit against the published 100-point rubric: what agents can fetch, parse, and act on, with captured evidence for every finding and a ranked fix list.

    Agent readiness audit

  • Monitoring

    Standards move. We tell you what broke, before a customer does

    Ongoing re-scanning against the evolving agent readiness rubric, with alerts when a deploy, a CDN setting, or a new standard breaks something.

    Monitoring