AttestPage: Verify Text Quote in Supplied Content

x402

AttestPage: Verify Text Quote in Supplied Content is a paid API for AI agents from vehcdj664efetfrsolne5umanq.srv.us, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-17).

Checks whether a specific quote or claim appears in a supplied text body, returning a signed verification result with match score, offsets, and a cryptographic receipt

Price / call$0.005

Seller volume →—

Success—

StatusUnknown

How this service works

Signed evidence about web pages, for AI agents. Ask whether a quote appears on a page or check every citation in an answer at once, fetch a page and learn…

Output

Returns a JSON object with: a match result (start/end offsets in normalized text, match type, similarity score, occurrence count), a source descriptor with SHA-256 hash and character count, a human-readable advice string, a signed receipt (JWT) for cryptographic proof, and an injection_flags array flagging any suspicious content in the input. Tier indicates whether the paid path was used.

Example use cases

AI answer citation verification

“I have an AI-generated research summary that cites several quotes from source documents I hold. Can you verify each quote against the source text using fuzzy matching and give me signed receipts proving whether each citation is real or fabricated?”

Legal document quote location

“I need to confirm that the clause 'liability shall not exceed the contract value' appears in this contract text I'm pasting — find its exact start and end offsets using exact matching and tell me how many times it occurs.”

Paraphrase support evidence

“I have a claim that 'the company guarantees delivery in two weeks' — can you find the three passages in this terms-of-service text that best support or contradict that claim, so I can judge whether the paraphrase is accurate?”

Technical details

Endpoint

POSThttps://vehcdj664efetfrsolne5umanq.srv.us/v1/verify/text-quote?utm_source=zero.xyz

When to prefer

Choose this endpoint when you already hold the source text locally and need to verify whether a specific quote or claim is present in it, without fetching any URL. It is ideal for batch citation checking of AI outputs against known documents, for getting cryptographic signed receipts as audit evidence, and for finding fuzzy or paraphrased matches with scored passage evidence. Prefer sibling endpoints if you need to fetch and verify against a live web page URL rather than supplied text.

Side effects

Text exceeds 50,000 characters — request rejected
Quote exceeds 1,000 characters after normalization — request rejected
start/end offsets provided together with match type 'passages' — invalid combination
threshold below 0.5 — rejected as out of range
No match found — result returns no offsets, score near 0
Payment not received — 402 response requiring x402 payment
Network timeout on the verification service
case_sensitive set to true with match 'passages' — invalid combination

Input

Schema · Request body

Field	Type	Description
end	integer	Optional, with start: the declared end offset, raw code points, exclusive. Give both or neither; not with match "passages".
text	string	The source text you already hold, as sent (max 50,000 characters; no fetch, no normalising before hashing). Offsets count characters (code points).
match	string	exact; fuzzy (default), which also accepts small differences; or passages, for a paraphrased claim: the 3 passages of the text that share most of its words, scored, as evidence for you to judge (not a verdict). Not with start and end.
quote	string	Text to look for in the source, or with match "passages" the claim to find support for (max 1,000 characters after normalisation).
start	integer	Optional, with end: the declared start offset of the quote in text, raw code points, 0-based. Only that slice is matched (max 1,000 code points), so the answer is whether the text at these offsets says the quote. Declared offsets are raw; result offsets are into the normalised text. If the slice misses but the quote is elsewhere in the text, result.located gives its position in the whole text.
threshold	number	Fuzzy similarity needed, default 0.9.
case_sensitive	boolean	Default false; must be false with match "passages".

Output

Schema · Response

{
  "type": "json",
  "example": {
    "tier": "paid",
    "advice": "The supplied text contains a close match to this quote, with small differences. This says nothing about where the text came from.",
    "result": {
      "end": 34,
      "match": "fuzzy",
      "score": 0.972,
      "start": 0,
      "source": {
        "kind": "supplied",
        "code_points": 79,
        "text_sha256": "…"
      },
      "context": "Refunds are paid within 14 days of purchase",
      "occurrences": 1,
      "normalised_sha256": "…"
    },
    "receipt": "eyJ…",
    "injection_flags": []
  }
}

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