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The door: what an agent should know before it acts on a site

Quickstart: ask before you act

MCP, curl, Python, OpenAI Agents, Claude tool use, LangChain

The signed answer about any domain, laid out for a person

How each named agent behaves on sites, from verified requests

Capability registry

What sites declare agents can do, and what was verified

Verify a record

Check any answer or bundle on your own machine

Before you act

One signed answer, no key.

Read, cite, connect or transact: ask first, verify the receipt offline, keep it with the action.

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The door: scan free, have it fixed, keep it fixed

The checks behind the audit, one at a time

Is your business record right where agents look?

Compare two sites

Two domains, side by side, same measurement

What search and answer engines read from a video

Browser extension

The second vantage point: from your own address, after JavaScript

The record on your phone, with receipts

Your site

Measured as agents see it.

A free A–F audit with every defect named, no account. Fix it, then prove it held.

Developers

The door: the API by lane, the specs, SDKs, keys and quotas

Every endpoint, with a worked example from production

Resolve protocol

The signed answer: what it holds, how to verify it

SDKs: npm and PyPI

Typed clients, the offline verifier, conformance fixtures

The Ed25519 keys every answer is signed with

Every finding the measurement can raise, with its revision

Run the suite against your own implementation

Data

The door: census, conduct, proof and datasets, each with a denominator

Signed decisions, scans and crawler visits, counted

Proof and timestamps

How every record is sealed and anchored

CC BY 4.0 snapshots and the archive

SEO and AI tools, measured

The vendors that measure sites, measured by the same rules

Registry: media kits, llms.txt, entity graphs

Verified machine-readable profiles of real organisations

Learn

The door: guides, findings and the glossary, from measurements

The scan, stage by stage, and what each grade means

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Dated cases from real scans, with the bytes behind them

Every term the product uses, defined

Who sends each agent, what it reads, how to verify it

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Glossary · Linked data and entities

ContactPoint

Structured contact details associated with an entity and purpose.

What ContactPoint does not show

It improves routing only when telephone, language, area served, and contact type are maintained.

Where ContactPoint comes up on this site

llms.txt adoption rate: how many sites actually publish oneContactPoint near 92,000.
The state of AI visibility, September 2026: what 1,364 scans say a crawler actually receivesBuiltWith counts 354,358 sites declaring an Organization, 108,730 declaring a PostalAddress, 91,622 a ContactPoint, 55,182 an Offer, and 22,972 an OpeningHoursSpecification.

Related terms in Linked data and entities

The RDF and JSON-LD machinery behind structured data, and the schema.org types a business page actually needs.

IRI · URI · URL · Blank node · Literal · Datatype · Language tag · Predicate · Subject · Object · Named graph · Default graph · RDF dataset · Graph merge · Graph normalization · Canonical RDF · JSON-LD expansion · JSON-LD compaction · JSON-LD flattening · Remote context · Context poisoning · Vocabulary term · Schema type · Schema property · domainIncludes · rangeIncludes · Inverse property · ItemList · BreadcrumbList · WebPage · Article · NewsArticle · BlogPosting · Product · Offer · Service · Place · PostalAddress · GeoCoordinates · AggregateRating · Review · Author relationship · Publisher relationship · mainEntity

Questions about ContactPoint

What is ContactPoint?

Structured contact details associated with an entity and purpose.

What does ContactPoint not show or guarantee?

It improves routing only when telephone, language, area served, and contact type are maintained.

Which area of the glossary does ContactPoint belong to?

Linked data and entities: The RDF and JSON-LD machinery behind structured data, and the schema.org types a business page actually needs.

← GeoCoordinates · AggregateRating →

See it in the full glossary · 731 terms across 19 areas.