Very poor0.0%

AWCS

What the AWCS is, and how it is measured

The figures the index is made of, with their own series: a technology whose index is flat can still have moved on one dimension.

= −10.7
AWCS over 2 months

10.7%0.0%

Read

What Read measures

Lighthouse builds the accessibility tree an agent would traverse and scores the page pass or fail. The denominator is only the pages the audit could evaluate: a notApplicable or an error is excluded rather than counted as a failure, and the fraction that could be evaluated is published beside it as the coverage.

n=1 · coverage 100.0% · margin ±53.00 pp.

53% of the score
Read on its full scale

Very poor0.0%

Read: 2 months, no significant change= −20.0 pp
Guide

What Guide measures

The llms-txt audit passing: a file is served AND Lighthouse considers it valid. The denominator is every sampled page, so this is a fraction of the whole web and not of the sites that have a file. This is the figure the index uses, because a broken file does not guide an agent.

n=1 · coverage 100.0% · margin ±53.00 pp.

27% of the score
Guide on its full scale

Very poor0.0%

Guide: 2 months, no significant change= 0.0 pp
Act

What Act measures

A count, not a percentage: how many sampled sites register WebMCP tools that an agent can call. It is the audit that defines the Act dimension — the other two WebMCP audits measure how good those tools are, not whether they exist.

n=1 · coverage 100.0% · margin ±53.00 pp.

20% of the score
Act on its full scale

Very poor0.0%

Act: 2 months, no significant change= 0.0 pp
Reachable

What Reachable measures

Read from the robots.txt of the sampled sites: of the AI agents we track, how many are NOT disallowed. Gradual and not a yes or no — turning away one agent out of seventeen is not the same as turning away all of them. A site with no robots.txt blocks nobody, so it counts as fully reachable: that is a measurement, not a gap. This is the only figure that MULTIPLIES the index instead of adding to it, because it is a precondition: if an agent cannot fetch the page, nothing else about the page matters. One caveat we would rather state than hide: a blanket Disallow under User-agent: * is not counted, because the corpus-wide measurement cannot see it either, and we would rather be consistent than clever.

n=1 · coverage 100.0% · margin ±53.00 pp.

multiplies the rest
Reachable on its full scale

Excellent100.0%

Reachable: 3 months, no significant change= 0.0 pp

Measured, and not part of the index

These are signals, not scores. They are kept apart on purpose: mixed in with the dimensions, a low one reads as a bad grade for something the index never counted.

50.0%
Google's category score

Google's category score

Sample
n=1
Coverage
100.0%

The score Lighthouse gives the agentic-browsing category, read from the report as published. We republish it as a declared reference and never as a figure of ours: it includes cumulative-layout-shift — a rendering metric — at half the weight, and its weights are conditional and undocumented. A number whose calculation we do not control is not a number we cite as our own.

Google's category score: 2 months, no significant change= +6.2
0.0%
Sites with an AI crawler policy

Sites with an AI crawler policy

Sample
n=1
Coverage
100.0%

Not a Lighthouse audit: it is read from the robots.txt of the sampled sites, checking whether the file names any of the AI crawlers we track. It measures HAVING AN EXPLICIT POLICY and not permitting: blocking AI crawlers is a legitimate decision, and penalising it would be a value judgement dressed up as a measurement. What is a sign of maturity is having decided.

Sites with an AI crawler policy: 3 months, no significant change= 0.0 pp
0.0%
Sites serving an llms.txt

Sites serving an llms.txt

Sample
n=1
Coverage
100.0%

The same llms-txt audit as the figure below, read differently: this one counts SOMETHING being served at /llms.txt, valid or not. Read that literally, because the distance between the two figures is large and it is the interesting part: of the pages that serve something, fewer than two in five serve a file that parses. Our reading — and we cannot verify it without fetching those files ourselves, which we do not do — is that a good share of the rest are soft 404s: a server answering 200 with an HTML error page. So the figure to cite is the valid one below, and this one is best read as an upper bound. Pages whose audit errored are excluded from both, and the coverage says how many that was.

Sites serving an llms.txt: 2 months, no significant change= −40.0 pp

Against the rest of Recruitment & staffing

The 7 technologies in this category with a published index, and the web overall for scale. Workable is the highlighted bar.

Recruitee
Recruitee: 53.3%
53.3%
Paylocity
Paylocity: 26.7%
26.7%
All sites
All sites: 19.9%
19.9%
WP Job Openings
WP Job Openings: 13.3%
13.3%
BambooHR
BambooHR: 0.0%
0.0%
Paradox
Paradox: 0.0%
0.0%
SmartRecruiters
SmartRecruiters: 0.0%
0.0%
Workable
Workable: 0.0%
0.0%
00.250.500.751.0
Every Recruitment & staffing technology the census can publish, against the web overall (19.9%). The scale is always 0–1.

What else we measure here

50.0%
Google's category score

Google's category score

Sample
n=1
Coverage
100.0%
0.0%
Sites with an AI crawler policy

Sites with an AI crawler policy

Sample
n=1
Coverage
100.0%
100.0%
Agents that can reach the site

Agents that can reach the site

Sample
n=1
Coverage
100.0%
0.0%
Pages an agent can parse

Pages an agent can parse

Sample
n=1
Coverage
100.0%
0.0%
Sites serving an llms.txt

Sites serving an llms.txt

Sample
n=1
Coverage
100.0%
0.0%
Sites with a valid llms.txt

Sites with a valid llms.txt

Sample
n=1
Coverage
100.0%
0
Sites exposing tools

Sites exposing tools

Sample
n=1
Coverage
100.0%

How this was measured