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Build Result Imports — Calendar Date Check
x402
Build Result Imports — Calendar Date Check is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-14).
Validates calendar date fields in a CSV of build result import records, checking up to 1000 rows for date correctness and contract compliance.
Price / call$0.01
Success—
StatusUnknown
How this service works
Build result imports — Calendar date check: Calendar date check for Build result imports. Validate a declared CSV table contract, up to 1000 rows. Quoted cells supported; no external enrichment. Specialised preset in a shared 50-profile, 20-operation engine. 0.01 USDC includes one CSV calendar date check report.
Output
A calendar date check report covering up to 1000 rows of the submitted CSV, identifying which rows contain valid or invalid date values in the declared date columns, along with any contract violations such as out-of-range values or disallowed category entries.
Example use cases
CI pipeline date audit before ingestion
“Before I load this build results CSV into our data warehouse, can you validate the calendar dates in it? Here's the CSV with a comma delimiter — flag any rows where 'built_on' looks malformed or out of range.”
Build import QA for release report
“I need to QA our sprint build import file — it's a semicolon-delimited CSV with build IDs, dates, and repo names. Run a calendar date check on it and tell me which rows have bad date values.”
Validate allowed categories and dates together
“Check this build results CSV for valid calendar dates in the 'built_on' column, and only allow records tagged 'group-a' or 'group-b' as repository categories. Use comma as delimiter and flag anything that's wrong.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-builds-dates?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, cheap ($0.01 USDC) automated check specifically for calendar date fields in build result import CSVs, without requiring external data enrichment. It is ideal for pre-ingestion QA pipelines validating CI/CD build logs before loading into a data warehouse or analytics system, especially when the dataset is under 1000 rows and you want row-level date validation with category allow-listing.
Side effects
- CSV exceeds 100,000 character limit — request rejected
- More than 1000 rows submitted — validation truncated or rejected
- Invalid delimiter specified outside allowed enum values
- Cell content exceeds max_cell_length — parsing error
- Malformed CSV structure (unclosed quotes, inconsistent columns) — parse failure
- Minimum value greater than maximum value — configuration error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| csv | string | |
| maximum | number | |
| minimum | number | |
| delimiter | string | |
| max_cell_length | integer | |
| allowed_categories | array |
Tags
x402
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