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Quant Agent Shop Structured Extraction
x402
Quant Agent Shop Structured Extraction is a paid API for AI agents from quantagentshop.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Extracts structured JSON fields from text, web pages, or PDFs according to a caller-supplied JSON Schema, with one automatic repair attempt if validation fails.
Price / call$0.01
Success—
StatusUnknown
How this service works
Structured extraction. Send text (up to 20,000 characters; 20 KB of UTF-8 is read) or a public page or PDF URL, plus a JSON Schema (up to 8,000 characters, no pattern keywords, $ref only inside it); returns JSON checked against your schema, after one repair attempt if needed. Use to pull fields from invoices, listings, filings or emails. Not for free-form summaries (use /v1/summarize). Typical response 3 to 10 s. Failed calls are not charged.
Output
A JSON object matching the caller-supplied JSON Schema, containing the fields extracted from the provided text or URL. If the initial extraction fails schema validation, one automatic repair attempt is made. If the call fails entirely, no charge is applied. Typical response time is 3–10 seconds.
Example use cases
Invoice field extraction for accounting
“Pull the vendor name, invoice date, invoice number, line items with quantities and prices, subtotal, tax, and total amount from this invoice PDF at https://mybusiness.com/invoices/march2024.pdf and give it back as structured JSON.”
Job listing data structuring
“Extract the job title, company name, location, salary range, required skills, and application deadline from this job posting text and return them as a JSON object: 'Senior Backend Engineer at Stripe, San Francisco or Remote. $180k–$230k. Skills: Go, Kubernetes, PostgreSQL. Apply by April 30, 2024.'”
SEC filing key metrics parsing
“From this 10-K filing page at https://www.sec.gov/Archives/edgar/data/320193/000032019324000006/aapl-20231230.htm, extract the company name, fiscal year end date, total revenue, net income, and total assets as structured JSON.”
Technical details
Endpoint
POSThttps://quantagentshop.com/v1/extract?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to extract specific, schema-defined fields from text, HTML pages, or PDFs and want the output validated against a JSON Schema automatically. Prefer it over generic LLM extraction when you need guaranteed schema compliance and a deterministic structure. Not appropriate for free-form summaries (use /v1/summarize instead) or when the source document requires authentication or is behind a paywall.
Side effects
- Schema exceeds 8,000 characters or 16 nesting levels — request rejected
- Text input exceeds 20,000 characters — truncated or rejected
- URL is not publicly accessible or returns non-200 — extraction fails
- JSON Schema uses disallowed keywords (pattern, patternProperties) — rejected
- Extracted content does not match schema after one repair attempt — error returned
- PDF is encrypted or requires authentication — extraction fails
- Ambiguous or missing fields in source content — fields may be null or omitted
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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