# Agentics Structured Data Extractor

> Agentics Structured Data Extractor is a paid API for AI agents from x402rail.net, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-15).

Extracts structured JSON data from raw text, markdown, or HTML according to a caller-supplied JSON Schema

## Facts

- Endpoint: POST https://x402rail.net/v1/extract
- Price: $0.05/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/agentics-structured-data-extractor-e55c4717
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_mFUlVsOYSMAEjHDt9lmYS

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability agentics-structured-data-extractor-e55c4717 -d '<json body>'
```

Example prompt: Extract the title, revenue in USD, and fiscal quarter from this text as structured JSON: 'Acme Corp posted $1.25M in revenue for Q2-2026 in their quarterly report.' — use a schema with title (string), revenueUsd (number), and fiscalQuarter (string).

## When to prefer this

Choose this endpoint when you need to reliably extract typed, schema-conforming structured data from unstructured or semi-structured text (markdown, HTML, raw prose) in a single call. It is especially well-suited for correctness-critical agent workflows where the output shape must match a predefined contract. Prefer it over general LLM prompting when you want schema enforcement, token usage visibility, and a pay-per-call pricing model via x402.

## Known failure modes

- 413 returned if content exceeds the character limit from GET /v1/policy before any payment is settled
- 422 returned if content contains plaintext PII or secrets detected by screening
- Malformed or overly vague JSON Schema may yield incomplete or incorrect extraction
- Missing required 'schema' or 'content' fields returns a 400-level error
- Payment failure or insufficient USDC balance prevents call completion

## How this service works

Correctness-critical services for autonomous AI agents

## Output

A JSON object with a 'data' field containing the extracted values conforming to the caller-supplied schema, plus the model name used and token usage (input/output counts).

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "schema": {
   "type": "object",
   "description": "JSON Schema describing the desired output object. The extractor returns data conforming to this shape; richer property descriptions yield better extraction.",
   "additionalProperties": true
  },
  "content": {
   "type": "string",
   "description": "Raw text, markdown, or HTML to extract from. Capped at the published limit (GET /v1/policy -> limits.extract.maxContentChars); oversized input returns 413 before settlement. Must not contain plaintext PII/secrets (screened, rejected with 422 before the model sees it)."
  },
  "instructions": {
   "type": "string",
   "description": "Optional extra natural-language guidance to steer the extraction (e.g. disambiguation rules)."
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "data": {
   "title": "Quarterly Report",
   "revenueUsd": 1250000,
   "fiscalQuarter": "Q2-2026"
  },
  "model": "claude-sonnet-4-5",
  "tokenUsage": {
   "input": 812,
   "output": 64
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/agentics-structured-data-extractor-e55c4717/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from x402rail.net](https://www.zero.xyz/host/x402rail.net/llms.txt)