Aater Observatory · Participation Standard v2.1.0

The open standard for measuring AI participation.

Published May 2026
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aater.ai Observatory

Every AI system that reads the web applies its own classification. It decides what to extract, what to attribute, and what to ignore. Most site owners never see this classification. Aater makes it visible, measurable, and improvable — against a single shared standard.

The uncomfortable reality

Most sites fail before the first gate. They are not blocked, not penalised — simply invisible. AI systems move past them without recording a signal. The content exists. The classification does not.

New to the classification vocabulary? Read the Participation Lexicon first →

Why a standard matters

robots.txt told crawlers where to go.
This tells AI what it can use.

robots.txt established the protocol for crawler access. It is a declaration, not a measurement. It tells AI systems what they may crawl — not whether the content they find is actually usable, citable, or trustworthy.

The Participation State Standard fills that gap. It classifies every domain on three measurable dimensions — reachability, legibility, and authority — and resolves them to a single participation state. The same classification. The same gates. Applied identically, every time.

Participation State Standard v2.1.0 · Patent Pending (IN 202621062543)

robots.txt
Declares crawl permission
Does not measure content usability
sitemap.xml
Declares URL structure
Does not measure semantic value
schema.org
Declares content type
Does not measure authority or density
Participation Standard
Measures AI usability end-to-end
Classification Pipeline

Three gates. One derivation.

Gates are evaluated in strict sequence. Failure at any gate terminates evaluation and resolves the participation state immediately. No gate can be compensated for by performance at another.

Unfamiliar with gate terminology? See precise definitions in the Lexicon →

Gate 1
Reachability
Can AI reach it?
What is measured
  • DNS resolution and HTTP response
  • robots.txt policy — per-agent intersection
  • Content delivery completeness
  • Empty shell detection (200 OK ≠ content)
Outcomes
PassGate 2 →
DegradedGate 2 (constrained) →
BlockedAbsent — stop
Pass →
Gate 2
Legibility
Can AI read what it finds?
What is measured
  • Heading structure — hierarchy and coherence
  • Named entity density — distinct, non-UI tokens
  • Specific claim surface — verifiable assertions
  • Semantic depth vs render gap estimate
Outcomes
StructuredGate 3 →
PresentCapturable or Gate 3 →
MarginalMarginal — stop
Pass →
Gate 3
Authority
Can AI trust and cite what it reads?
What is measured
  • Byline or author metadata presence
  • Schema.org markup — type and consistency
  • Publication and modification dates
  • Topical coherence — density-gated signal
Outcomes
StrongAuthoritative
ModerateEmerging
WeakCapturable
Derivation complete
Participation State resolved
Apply the standard

Submit domain for derivation.

The same three gates. Applied in sequence. No human judgement enters the derivation.

The Five States

What the derivation resolves to.

Every domain on the web occupies exactly one of these states at any given moment. States change as content and configuration change. Classification reruns confirm or update the position.

Absent
Marginal
Capturable
Emerging
Authoritative
AbsentIndex 0

Reachability failed. The content cannot be accessed — blocked, unreachable, or empty response. AI systems record no signal.

Fails Gate 1
MarginalIndex 1

Legibility failed. Reachable — but structurally insufficient. No heading hierarchy, no extractable claim surface.

Fails Gate 2
CapturableIndex 2

Readable. Not attributable. Extraction possible — citation confidence insufficient. AI systems will not treat this as a named source.

Fails Gate 3
EmergingIndex 3

All gates pass. Authority partial. Content is readable and structured — attribution building but not yet confirmed.

All gates pass
AuthoritativeIndex 4

All gates pass at full strength. Authorship, schema, and topical coherence confirmed. Positioned for extraction, citation, and attribution by AI systems.

All gates pass — strong authority

For precise definitions of each state and its structural meaning, see the Participation Lexicon →

Classification is not ranking.

Participation state is not a score. There is no weighted formula, no fuzzy weighting. Each gate either passes or fails. The derivation is deterministic — the same domain, the same signals, produces the same state every time.

Invisible failure is the norm.

Most sites that fail do not receive an error. They receive silence. AI systems move on without recording the visit. The site owner has no signal. This is the gap the standard exists to close.

State changes when you change.

Classification reflects current structural reality. Fix a robots.txt entry and reachability passes. Add authorship markup and authority improves. The standard measures the present, not history.

Apply the standard

Classification runs the same pipeline on every domain.

The three gates are applied in sequence. No domain receives special treatment. No human judgement enters the derivation. Enter your domain to see which gate your site passes and where the constraint sits.

Which gate your site fails (if any)
The specific signal that produced the outcome
Your participation state in the global distribution
Live Classification

Where does your domain stand?

Run a classification against the standard. See which gate your site fails — and why.

Enter your domain to see where your site fails this pipeline.

Versioning

A standard requires stability.

Every classification is tagged with the engine version that produced it. When the standard evolves, prior classifications remain interpretable. Agencies and publishers can cite a specific version with confidence that the classification is reproducible.

PSS v2.1.0CurrentParticipation state engine · Gate-based derivation
System behaviour

Participation states continuously shift as domains change structure, authority, and accessibility.

The observatory measures these transitions across the public web. Classification is not a snapshot. It is a continuous derivation — re-evaluated whenever structural signals change.

Beyond classification

Knowing your state is the beginning.

The audit tells you where you stand. Pulse shows what AI systems are actually doing on your site — which agents are visiting, at what frequency, and to what depth.