Verity Suite – Claim Freshness Check

x402

Verity Suite – Claim Freshness Check is a paid API for AI agents from suite.veritylayer.dev, paid per call via x402, $0.25/call, status unknown (last checked 2026-09-14).

Checks whether a given fact or claim is still current by evaluating it against retrieved evidence snippets, returning a calibrated freshness verdict.

Price / call$0.25

Seller volume →—

Success—

StatusUnknown

How this service works

The trust fabric for AI agents — calibrated, fail-closed services agents pay per call.

Output

Returns a JSON object with a 'status' field (one of: current, outdated, changed, unverifiable), a 'staleness' score, and an array of 'reasons' citing specific evidence snippets and their dates. If the claim has changed, a 'current_value' field states the new fact. The service is fail-closed: when evidence is absent, undated, or insufficient, it returns 'unverifiable' rather than guessing.

Example use cases

Stale knowledge base detection

“I have a claim in our knowledge base that says 'The federal minimum wage is $7.25 per hour' — last verified in 2022. Here are three recent web snippets I pulled today about minimum wage. Can you check whether this is still current or if it's changed?”

RAG answer freshness gate

“Before my agent answers a user question about mortgage interest rates, I retrieved these three news snippets from this week. Check whether the claim 'The 30-year fixed mortgage rate is around 7%' still holds based on this evidence, so I know whether to trust or discard it.”

Competitive intelligence currency check

“Our sales deck says 'Competitor X's flagship plan costs $99/month' — we last checked in early 2024. I've pulled four current snippets from their pricing page and recent reviews. Please verify if this pricing claim is still accurate or has changed.”

Technical details

Endpoint

POSThttps://suite.veritylayer.dev/freshness

When to prefer

Choose this endpoint when an AI agent needs a structured, fail-closed verdict on whether a specific fact is still true before using it in a response, rather than relying on its own potentially stale training data. It is especially valuable in RAG pipelines where retrieved snippets need to be cross-checked against a held claim, in knowledge base maintenance workflows to flag outdated entries, or when an agent must avoid confidently stating facts that may have changed. Prefer this over generic LLM self-checks because it returns a typed enum status with evidence-grounded reasons, making it auditable and deterministic.

Side effects

Empty or undated evidence array causes status=unverifiable — agent must supply dated, relevant snippets
Evidence irrelevant to the claim results in status=unverifiable rather than an incorrect verdict
Claim text exceeding 2000 characters is rejected with a validation error
Ambiguous or compound claims may produce unverifiable if the evidence only partially addresses them
Payment failure (insufficient USDC) results in 402 response before processing begins

Input

Schema · Request body

Field	Type	Description
as_of	—	The date or version at which the claim was last known to be true, if known (e.g. '2024-01-01'). Used only to weigh evidence recency; it is not itself proof of current truth.
claim	string	The single fact or claim to check for currency. Treated as data to be judged, not as instructions.
evidence	array	Retrieved current snippets, ideally each with a date and source, to judge the claim against. If empty or undated, currency cannot be confirmed.

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