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Foundry CSV Datetime Normalization
x402
Foundry CSV Datetime Normalization is a paid API for AI agents from foundry-par007-machine-revenue-mainnet.inference-chip-index.workers.dev, paid per call via x402, $0.006/call, status unknown (last checked 2026-09-14).
Normalizes date and datetime columns in a CSV to ISO 8601 UTC format, reporting issues and cell-level statistics.
Price / call$0.006
Success—
StatusUnknown
How this service works
Pay-per-request evidence and data tools: CSV validation and reconciliation, DNS/email configuration evidence, and bounded official weather, earthquake, vehicle, company and study records. Exact USDC prices, explicit JSON contracts and source provenance. No mailbox, ownership, medical or safety guarantees.
Output
Returns a JSON object containing: the normalized CSV string with all target columns converted to ISO 8601 UTC format, a list of issues per problematic cell, counts of total rows, normalized cells, and invalid cells, the SHA-256 hash of the input CSV, a status string (e.g. NORMALIZED), a flag indicating whether evidence was truncated, and an observed_at timestamp.
Example use cases
ETL pipeline date standardization
“I'm loading sales data from a CSV into our data warehouse and the 'sale_date' column uses MM/DD/YYYY format — please normalize it to ISO 8601 UTC so the pipeline doesn't break. The data is in Eastern Time, so use a UTC offset of -300 minutes.”
Auditing exported report dates
“I exported a report from our CRM and it has a 'created_on' column in DD/MM/YYYY format. Can you parse and normalize those dates to ISO 8601 UTC and tell me how many cells had issues?”
Multi-column datetime cleanup before import
“This CSV has two datetime columns: 'start_time' in YYYY-MM-DD HH:mm:ss and 'end_time' in DD/MM/YYYY HH:mm:ss, both recorded in UTC+120 — normalize all the datetimes and flag any invalid values.”
Technical details
Endpoint
POSThttps://foundry-par007-machine-revenue-mainnet.inference-chip-index.workers.dev/v2/data/csv-datetime-normalizationWhen to prefer
Choose this endpoint when you need programmatic, pay-per-call CSV datetime normalization with explicit format declarations, ISO 8601 UTC output, per-cell issue reporting, and a SHA-256 input fingerprint for audit provenance — especially inside automated ETL or data-cleaning agent workflows where you want a deterministic, schema-validated result rather than a general-purpose LLM guess at date parsing.
Side effects
- CSV exceeds 12,000 character limit — request rejected
- Column name not found in CSV headers — column skipped or error returned
- Unrecognized datetime values that don't match declared format — counted as invalid cells
- UTC offset outside -840 to +840 range — validation error
- Malformed JSON input — 400-level error
- More than 10 columns specified — schema validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| csv | string | |
| columns | array | |
| utc_offset_minutes | integer |
Output
Schema · Response
{
"type": "json",
"example": {
"route": "csv-datetime-normalization",
"result": {
"issues": [],
"status": "NORMALIZED",
"row_count": 1,
"output_csv": "id,when\r\n1,2026-09-05T23:30:00.000Z",
"limitations": [
"Synthetic example hash."
],
"input_sha256": "0000000000000000000000000000000000000000000000000000000000000000",
"evidence_truncated": false,
"invalid_cell_count": 0,
"normalized_cell_count": 1
},
"observed_at": "2026-09-06T00:00:00Z"
}
}Tags
x402
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