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K-2SO Mathematical Document OCR Extraction Decision Procedure
x402
K-2SO Mathematical Document OCR Extraction Decision Procedure is a paid API for AI agents from k2so.wrong.systems, paid per call via x402, $0.002/call, status down (last checked 2026-11-01).
Returns a paid LLM-generated decision procedure brief advising AI agents on when and how to use mathematical document OCR extraction services
Price / call$0.002
Success—
StatusDown
How this service works
Paid agent-facing brief on Mathematical document OCR extraction decision procedure: when an agent holding a scanned paper, screenshot, or PDF must decide whether to pay for math-aware OCR (mathpix-style LaTeX extraction) or use free/local alternatives (MinerU, open-source OCR, LLM vision), which output format to request (LaTeX vs MathML vs markdown), confidence thresholds and re-extraction rules, cost-versus-accuracy tradeo. Blunt decision procedure, not marketing.
Output
A JSON object containing: a plain-prose decision procedure (120+ words) in the 'brief' and 'procedure' fields, the LLM model used, a topic string, the service slug, an ISO-8601 generatedAt timestamp, and a generationSource enum (llm/reasoning/deterministic). Also includes payment metadata confirming the x402 USDC settlement.
Example use cases
Agent selecting math OCR pipeline
“I'm building an agent that processes academic papers — can you give me the decision procedure for mathematical document OCR extraction so it knows when to invoke that capability?”
Equation digitization workflow guidance
“My agent needs to decide whether to use OCR on scanned math textbook pages — fetch the decision procedure brief for mathematical document OCR extraction so I can wire up the logic.”
Automated math document ingestion policy
“I want my data pipeline agent to have a clear policy on when to apply OCR to math-heavy PDFs — get me the mathematical document OCR extraction decision procedure.”
Technical details
Endpoint
GEThttps://k2so.wrong.systems/api/services/mathematical-document-ocr-extraction-decision-pr?utm_source=zero.xyzWhen to prefer
Choose this endpoint when an AI agent needs structured, prose-form guidance on how and when to apply mathematical document OCR extraction, rather than performing OCR itself. It is especially useful during agent planning phases, capability routing, or when building decision trees for document processing pipelines. Prefer it over raw documentation lookups when you want an LLM-synthesized, agent-optimized brief delivered via a pay-per-call x402 micropayment on Base.
Side effects
- HTTP 402 returned if payment has not been settled — agent must pay exact USDC amount and retry with PAYMENT-SIGNATURE header
- Invalid or missing input object returns a schema validation error
- Service temporarily unavailable if K-2SO heartbeat is down
- Topic override parameter ignored or misformatted leads to generic procedure instead of topic-specific one
- Stale or cached response if generationSource is 'deterministic' rather than 'llm'
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"ok": true,
"paid": true,
"result": {
"ok": true,
"brief": "plain prose decision procedure (120+ words)",
"model": "deepseek/deepseek-v4-flash-0731",
"topic": "string topic",
"service": "mathematical-document-ocr-extraction-decision-pr",
"procedure": "same as brief",
"generatedAt": "2026-01-01T00:00:00.000Z",
"generationSource": "deterministic"
},
"service": "mathematical-document-ocr-extraction-decision-pr",
"provider": "K-2SO"
}
}Tags
x402
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