AgenticWeb CensusCheck your site
EN

Domain suffix · September 2026

Are .edu.in sites ready for AI agents?

.edu.in scores 19.4%, 14.9% below the web overall (34.3%).

Poor19.4%

AWCS

What “AWCS” measures and how

Measured on 100 pages, 96.2% of which carried the agentic category, with a confidence margin of ±5.30.

= −0.4
AWCS over the last 2 months

19.8%19.4%

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 not-applicable result 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=100 · coverage 96.2% · margin ±5.30 pp.

40% of the score
Read on its full scale

Poor14.0%

Read: 2 months, no significant change= +4.8 pp
Stable

What Stable measures

Lighthouse's Cumulative Layout Shift audit, counted per page: a page passes when Lighthouse rates its layout shift as good. The denominator is the pages the audit scored. It matters to an agent that works the page the way a person does, by taking a screenshot and clicking where it saw a button: if the page has moved in between, it clicks something else.

n=100 · coverage 96.2% · margin ±5.30 pp.

25% of the score
Stable on its full scale

Fair55.0%

Stable: 2 months, down▼ −8.3 pp
Guide

What Guide measures

The pages that pass the llms-txt audit: they serve a file 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 score uses, because a broken file does not guide an agent.

n=104 · coverage 100.0% · margin ±5.20 pp.

20% of the score
Guide on its full scale

Very poor3.0%

Guide: 2 months, no significant change= +1.3 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 WebMCP audits measure how good those tools are, not whether they exist.

n=100 · coverage 96.2% · margin ±5.30 pp.

15% of the score
Act on its full scale

Very poor1.0%

Act: 2 months, no significant change= +1.0 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. It is gradual rather than a yes or no, because turning away one agent is not the same as turning away all of them. A site with no robots.txt blocks nobody, so it counts as fully reachable, and that is what was measured. This is the only figure that multiplies the score 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: a blanket Disallow under User-agent: * is not counted, because the corpus-wide measurement cannot see it either, so both are measured the same way.

n=104 · coverage 100.0% · margin ±5.20 pp.

multiplies the rest
Reachable on its full scale

Excellent96.4%

Reachable: 2 months, no significant change= −3.2 pp
All sites
All sites: 34.3%
34.3%
.edu.in
.edu.in: 19.4%
19.4%
0%25%50%75%100%
.edu.in against the web overall, on the full scale.

Every other figure this month

7.7%
Sites with an AI crawler policy

Sites with an AI crawler policy

Sample
n=104
Coverage
100.0%
96.4%
Agents that can reach the site

Agents that can reach the site

Sample
n=104
Coverage
100.0%
14.0%
Pages an agent can parse

Pages an agent can parse

Sample
n=100
Coverage
96.2%
58.0%
Sites serving an llms.txt

Sites serving an llms.txt

Sample
n=104
Coverage
100.0%
55.0%
Pages that hold still

Pages that hold still

Sample
n=100
Coverage
96.2%
3.0%
Sites with a valid llms.txt

Sites with a valid llms.txt

Sample
n=104
Coverage
100.0%
1
Sites exposing tools

Sites exposing tools

Sample
n=100
Coverage
96.2%

How this was measured