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SignalHarness PDF Extract
x402
SignalHarness PDF Extract is a paid API for AI agents from signalharness.ai, paid per call via x402, $0.03/call, status unknown (last checked 2026-09-14).
Extracts text, markdown, and metadata from a publicly accessible PDF URL, returning full content with SHA-256 integrity hash.
Price / call$0.03
Success—
StatusUnknown
How this service works
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Output
Returns a JSON object with: extracted plain text, markdown-formatted content, SHA-256 hash of the content, HTTP status, PDF metadata object, warnings array, byte count, page count, source URL, and content type. Also includes a receipt with payment details, latency, execution ID, and service version for auditability.
Example use cases
Research paper content extraction
“There's a research paper at https://arxiv.org/pdf/2301.00001.pdf — can you pull out all the text and let me know how many pages it has?”
Contract review text parsing
“I need to read through this contract PDF at https://docs.example.com/contract-2024.pdf — extract all the text so I can review the clauses.”
Invoice data extraction pipeline
“Can you grab the text from this invoice PDF at https://billing.company.com/invoice-12345.pdf, including any metadata, so I can pull out the amounts and dates?”
Technical details
Endpoint
POSThttps://signalharness.ai/api/agent/services/pdf_extract/invokeWhen to prefer
Choose this endpoint when you need to extract structured text and markdown from a publicly accessible PDF via HTTPS URL, especially when you also need integrity verification via SHA-256 hash, page count, and metadata. It is well-suited for agent pipelines that process documents programmatically at $0.03 per call with on-chain payment receipts for auditability. Prefer this over generic web scrapers when the target is specifically a PDF and you need reliable markdown output alongside raw text.
Side effects
- URL does not start with https:// — rejected by schema validation
- PDF URL is not publicly accessible or returns 4xx/5xx — extraction fails
- URL points to a non-PDF content type — may produce empty or error result
- PDF is password-protected or encrypted — text extraction returns empty
- URL exceeds 2048 character limit — rejected by schema validation
- Network timeout fetching large PDF files
- Malformed or corrupted PDF — warnings array populated, partial or no text returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| url | string |
Output
Schema · Response
{
"type": "json",
"example": {
"replay": false,
"result": {
"text": "Example caller-supplied content.",
"sha256": "0000000000000000000000000000000000000000000000000000000000000000",
"status": "OK",
"markdown": "# Example\n\nNormalized caller-supplied content.",
"metadata": {},
"warnings": [
"Verify the caller-supplied data before relying on this result."
],
"byteCount": 0,
"pageCount": 0,
"sourceUrl": "example00",
"contentType": "Example caller-supplied content."
},
"status": "succeeded",
"receipt": {
"asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
"usage": [],
"status": "succeeded",
"network": "eip155:8453",
"artifacts": [],
"endedAtMs": 0,
"latencyMs": 0,
"paymentId": "example-payment",
"receiptId": "example-receipt",
"requestId": "example-request",
"serviceId": "pdf_extract",
"executionId": "example-execution",
"startedAtMs": 0,
"amountAtomic": "30000",
"resultSha256": "563ead3b476aff911a258fa0d6937c9de7505bfcc8ab75ea252c66056e60f7d6",
"serviceVersion": "1.0.0",
"settlementReference": "0x0000000000000000000000000000000000000000000000000000000000000000"
},
"artifacts": [],
"requestId": "example-request",
"executionId": "example-execution"
}
}Tags
x402
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