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Time Entries String Normalisation
x402
Time Entries String Normalisation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-12).
Normalises string fields in time entry records (project name, date format) for up to 200 rows of typed time-tracking data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time entries - String normalisation: String normalisation for Time entries. Up to 200 supplied typed records. Local numeric and data-quality processing; no external enrichment or forecasting. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded string normalisation deliverable.
Output
Returns normalised versions of the submitted time entry records with cleaned and standardised string fields (project names, dates) and corrected data quality issues, preserving row_id references for downstream matching.
Example use cases
Timesheet import data cleanup
“Before I import this week's timesheet export into our billing system, can you normalise all the string fields across these 50 time entry rows? Project names are inconsistent and some dates look off.”
Freelancer invoice reconciliation
“I've got 120 time entry records from my contractors with messy project name strings and inconsistent date formatting — can you clean and normalise all of them so I can reconcile against invoices?”
Automated reporting pipeline prep
“I need to standardise the project and date strings in these 30 time entries before they feed into our weekly reporting pipeline — please normalise them for me.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-analytics-time-entries-normalise?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 time entry records with inconsistent or dirty string fields (project names, dates) and need lightweight local normalisation without external enrichment. Ideal for pre-processing timesheet exports before loading into billing or reporting systems. Not suitable for forecasting, enrichment with external data, or datasets exceeding 200 rows.
Side effects
- Rows array empty or missing — validation error returned
- row_id missing or blank on any record — schema violation
- date field not matching YYYY-MM-DD pattern — rejected record
- More than 200 rows submitted — request rejected with max items error
- hours or billable_hours out of numeric bounds — rejected
- Malformed JSON body — 400 bad request
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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