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Facilities Usage String Normalisation and Keyed Dataset Comparison
x402
Facilities Usage String Normalisation and Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Normalises strings and compares two facilities usage datasets (occupied_seats, available_seats) by key, returning 2 analytical reports for up to 200 rows each.
Price / call$0.01
Success—
StatusUnknown
How this service works
Facilities usage — String normalisation + Keyed dataset comparison: String normalisation + Keyed dataset comparison for supplied facilities usage records (occupied_seats, available_seats). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns 2 analytical reports: (1) a string normalisation report standardising team_group and other string fields across the supplied rows, and (2) a keyed dataset comparison report identifying row-level differences in occupied_seats and available_seats between the two supplied arrays, matched by row_id. No external data is fetched; all analysis is performed locally on the supplied records.
Example use cases
Reconciling two weekly occupancy reports
“I've got two weekly facilities reports for October with row IDs, team groups, dates, occupied seats, and available seats — one from the booking system and one from the facilities team. Can you normalize the team names and compare them row-by-row to show me where the seat counts differ?”
Auditing seat utilization across team groups
“Can you take these two sets of facilities usage records — up to 200 rows each, with occupied and available seat counts per team group and date — normalize any inconsistent group name formatting, and give me a keyed comparison showing which rows have mismatched numbers?”
Validating data consistency before dashboard merge
“Before I merge these two occupancy data exports into our dashboard, can you run a string normalization and keyed comparison on them? Each dataset has row_id, team_group, date, occupied_seats, and available_seats fields, and I need to catch any discrepancies between the two sources.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-operations-12-036?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have two facilities usage datasets (with occupied_seats and available_seats) that you need to both clean (string normalisation of team/group names) and reconcile (keyed row-by-row comparison) in a single low-cost call. It is ideal for up to 200 rows per dataset where no live data lookup, prediction, or external action is needed — purely local analytical processing on supplied data at $0.01 per call.
Side effects
- Input arrays exceed 200 rows — request will be rejected or truncated
- Missing required fields (row_id, team_group, date, occupied_seats, available_seats) cause row-level errors
- Date strings not matching YYYY-MM-DD pattern fail schema validation
- Numeric values outside allowed range cause validation errors
- Empty input array (minItems:1 not met) returns error
- Mismatched row_ids between the two arrays result in unmatched rows in comparison report
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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