Methodology version 1.0

How the AI Readiness Score works

Five observable website pillars add up to 100 points. The formula is deterministic, the evidence is public, and every point can be recomputed without asking a model for an opinion.

PillarWeightPrimary question
Search access20 pointsCan answer-engine crawlers fetch, index, and quote the page?
Server-delivered content25 pointsDoes useful page content exist in the fetched HTML before client-side rendering?
Extractable structure20 pointsCan a parser segment the page into meaningful, quotable sections?
Entity clarity20 pointsDo metadata, structured data, and visible copy agree on who the organization is?
Site discovery15 pointsCan a crawler move from the homepage to the rest of the useful site?

Search access

Can answer-engine crawlers fetch, index, and quote the page?

20 points
Scoring signalPoints
Secure final URL4
No noindex or nosnippet directive6
OAI-SearchBot allowed4
Claude-SearchBot allowed3
PerplexityBot allowed3

Server-delivered content

Does useful page content exist in the fetched HTML before client-side rendering?

25 points
Scoring signalPoints
Visible text volume10
Content inside main or article landmarks5
Text-to-markup density5
Useful text early in the document3
Scripts do not dominate the response2

Extractable structure

Can a parser segment the page into meaningful, quotable sections?

20 points
Scoring signalPoints
One clear H14
Usable heading sequence4
Semantic page landmarks4
Lists or tables3
Descriptive internal links3
Image alternative-text coverage2

Entity clarity

Do metadata, structured data, and visible copy agree on who the organization is?

20 points
Scoring signalPoints
Useful title and meta description6
Self-consistent canonical URL3
Open Graph title and description2
Organization and WebSite schema4
Entity schema field completeness3
Schema name appears in visible copy2

Site discovery

Can a crawler move from the homepage to the rest of the useful site?

15 points
Scoring signalPoints
Working XML sitemap5
Internal-link depth4
Links to company, product, resources, and contact pages3
Breadcrumbs2
Curated llms.txt1

Hard caps

A page cannot earn a high readiness score when an answer engine cannot index it or the useful copy is absent from the fetched HTML. These conditions cap the total at 40, even if other checks pass.

Noindex

The page tells search systems not to index it.

OAI-SearchBot blocked

The robots policy blocks OpenAI's documented search crawler.

Thin server response

The fetched HTML contains fewer than 50 visible words.

Search bots and training bots are different

The rank uses answer-engine access signals. Policies for GPTBot, ClaudeBot, and Google-Extended are recorded for transparency but add zero points. A company can restrict model training without losing leaderboard points.

Benchmark process

  1. 1. Define the cohort. Capture the public AWS Partner Finder directory with partner names, listed websites, paths, recognition counts, and locations.
  2. 2. Fetch public evidence. Request the listed website, robots.txt, sitemap.xml, and llms.txt with timeouts and retries.
  3. 3. Apply the formula. Parse the raw response and assign points from the rulebook above.
  4. 4. Publish the measurement date. Keep unreachable sites visible but unranked so a network failure never becomes a zero.

Scope and limitations

This score measures public website machine-readiness at one point in time. It does not measure AWS standing, partner tier quality, security posture, service delivery, customer outcomes, domain authority, brand reputation, or the quality of a partner's AWS work. Dynamic pages, geofencing, bot defenses, and temporary outages can affect a fetch. Partners can rerun a public audit after making changes.

AWS Partner Finder snapshot: August 21, 2026. Prospectory is not sponsored or endorsed by Amazon Web Services.