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GOFIBER Data Check - Tabular Data Validation and Comparison Service
x402
GOFIBER Data Check - Tabular Data Validation and Comparison Service is a paid API for AI agents from gofiber.hr, paid per call via x402, $0.1/call, status unknown (last checked 2026-10-22).
Validates, checks, and optionally compares structured tabular data (CSV or row arrays) for schema errors, duplicate groups, empty fields, and numeric sum accuracy.
Price / call$0.1
Success—
StatusUnknown
How this service works
GOFIBER d.o.o. iz Petrinje izvodi elektroinstalacije, strukturno mrežno kabliranje, videonadzor i WAGO PLC automatizaciju u Sisačko-moslavačkoj županiji i šire. Brza ponuda.
Output
Returns a job ID, status (FULFILLED or pending), a result object containing: total rows checked, schema errors list, duplicate groups, empty fields list, amount field sums with validity flags and invalid row indices, overall verified boolean, and a scope disclaimer. Also provides status_url and result_url for async polling.
Example use cases
Pre-import data integrity check
“I have a CSV file of customer transactions I'm about to import into our database. Can you validate it for empty fields, schema errors, and duplicate entries, treating 'transaction_id' as the key and 'total' as an amount field?”
Financial record comparison audit
“I need to compare two sets of invoice records to find discrepancies — the left set is our internal ledger and the right is what the supplier sent. Match them by 'invoice_id' and compare 'amount' as an exact decimal field.”
Batch data quality scan
“Can you run a data quality check on these 50 rows I'm about to process? I want to know which rows have missing fields, any schema violations if I define 'price' as number and 'sku' as string, and whether there are any duplicates.”
Technical details
Endpoint
POSThttps://gofiber.hr/x402/services/data-check?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need deterministic, offline validation of structured tabular data — particularly for schema conformance, duplicate detection, empty field identification, and exact decimal comparison of amount columns. It is well-suited for pre-import data audits, financial reconciliation between two record sets, and batch data quality checks. It does NOT validate against external records or databases — all checks are internal and deterministic.
Side effects
- Invalid JSON input or malformed CSV returns a schema validation error
- Missing required compare fields (left, right, key) when using compare mode causes rejection
- Exceeding maxItems (1000 rows) or maxProperties (50) limits results in rejection
- Providing neither csv nor rows in a dataset object causes a oneOf validation failure
- Non-numeric values in amount_fields cause them to be flagged as invalid rows rather than causing a hard failure
- Network timeout if the job takes longer than expected; use status_url to poll
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| csv | string | |
| rows | array | |
| schema | object | |
| compare | object | Two record sets compared by key; left is the reference. amount_fields are compared as exact decimals, other fields as exact text. |
| sum_fields | array |
Output
Schema · Response
{
"type": "json",
"example": {
"job_id": "3f2a9c8e7b6d5a4f3e2d1c0b9a8f7e6d5c4b3a2f1e0d9c8b7a6f5e4d3c2b1a09",
"result": {
"scope": "Deterministic checks of supplied data, not validation against external records.",
"totals": {
"amount": {
"complete": true,
"invalid_rows": [],
"sum_valid_values": "5"
}
},
"verified": true,
"empty_fields": [],
"rows_checked": 2,
"schema_errors": [],
"duplicate_groups": []
},
"status": "FULFILLED",
"result_url": "https://gofiber.hr/x402/jobs/3f2a9c8e7b6d5a4f3e2d1c0b9a8f7e6d5c4b3a2f1e0d9c8b7a6f5e4d3c2b1a09/result",
"status_url": "https://gofiber.hr/x402/jobs/3f2a9c8e7b6d5a4f3e2d1c0b9a8f7e6d5c4b3a2f1e0d9c8b7a6f5e4d3c2b1a09"
}
}Tags
x402
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