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Physics Scenes — Record Quality Audit + String Normalisation + Date by Category Pivot
x402
Physics Scenes — Record Quality Audit + String Normalisation + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-04).
Runs three analytical reports on physics scene records (body_count, step_ms): a record quality audit, string normalisation, and a date-by-category pivot, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Physics scenes — Record quality audit + String normalisation + Date by category pivot: Record quality audit + String normalisation + Date by category pivot for supplied physics scenes records (body_count, step_ms). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three independent analytical reports delivered together: (1) a record quality audit flagging data issues such as nulls or out-of-range values, (2) string normalisation output for the game_area and other string fields, and (3) a date-by-category pivot table summarising the selected numeric field (body_count or step_ms) grouped by date and game area.
Example use cases
Game physics dataset quality check
“I have a batch of physics scene records from our game with body_count and step_ms values across different game areas — can you run a record quality audit on them to flag any issues, normalise the game_area strings, and pivot the data by date and category?”
Step timing analysis by game area
“Run the three analytical reports on my physics simulation logs — quality audit, string normalisation, and date pivot — focusing on the step_ms field. I have about 120 rows with game_area, date, and step_ms columns.”
Pre-pipeline data validation for physics engine
“Before I load this physics scene dataset into our pipeline, can you audit the record quality, normalise the string fields, and give me a date-by-category pivot for the body_count metric? There are around 80 rows in total.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-08-206?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have physics scene simulation records with body_count and step_ms fields and need all three of a data quality audit, string normalisation, and date-by-category pivot in a single low-cost call. It is ideal for batch offline analysis of up to 200 rows with no need for live data lookup or external prediction.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, game_area, date, body_count, step_ms) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Numeric values outside allowed range cause validation failure
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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