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ClinKAgent PDF Question Answering
x402
ClinKAgent PDF Question Answering is a paid API for AI agents from clinkagent.com, paid per call via x402, $0.05/call, status unknown (last checked 2026-10-02).
Answers a plain-language question about any public PDF by returning a cited answer with verbatim supporting quotes and page numbers, or 'not_found' if the answer isn't present.
Price / call$0.05
Success—
StatusUnknown
How this service works
Ask a question about any public PDF and get a cited answer - pass a PDF URL and a plain-language question; returns the answer, confidence, verbatim supporting quotes with page numbers, or not_found. PDF question answering, document QA, read a filing/paper/manual/contract for me, extract a fact from a PDF. Text-based PDFs up to 25MB (no OCR). Full text instead: /pdf/text $0.01.
Output
Returns the answer to the question derived from the PDF content, a confidence level, one or more verbatim supporting quotes with their page numbers, or a 'not_found' response if the document does not contain information relevant to the question. Works only on text-based PDFs up to 25MB (no OCR support).
Example use cases
Extract clause from legal contract
“I have a lease agreement at https://example.com/lease.pdf — can you find what it says about early termination penalties and give me the exact quote with the page number?”
Look up stat in research paper
“Check this academic paper at https://arxiv.org/pdf/2301.00001.pdf and tell me what sample size they used in the main study — quote the relevant sentence and tell me where it appears.”
Answer question from government filing
“Pull up this FDA guidance document at https://fda.gov/files/guidance.pdf and tell me what it says about the required labeling format for dietary supplements, with a cited quote.”
Technical details
Endpoint
POSThttps://clinkagent.com/pdf/answer?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a specific question answered from a public PDF with cited evidence (quotes + page numbers), rather than extracting the full text. It is more cost-effective and targeted than full-text extraction when you only need one or a few facts. Prefer it for SEC filings, research papers, contracts, manuals, and policy documents where cited, verifiable answers matter. Use the sibling /pdf/text endpoint instead when you need the complete document text.
Side effects
- PDF is scanned/image-based and cannot be read without OCR — returns not_found or error
- PDF URL is not publicly accessible or requires authentication
- PDF exceeds 25MB file size limit
- Question is fewer than 3 or more than 500 characters
- Answer genuinely not present in the document — returns not_found
- PDF is malformed or not a valid PDF file
- Network timeout fetching the remote PDF
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| url | string | Public http(s) URL of a PDF file |
| question | string | 3-500 char plain-language question about the document |
Output
Schema · Response
{
"type": "json",
"example": {
"answer": "...",
"citations": [
{
"page": 3,
"quote": "..."
}
],
"not_found": false,
"confidence": "high"
}
}Tags
x402
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