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Texture Streaming Data Analyzer — Quality Audit, String Normalization & Grouped Summary
x402
Texture Streaming Data Analyzer — Quality Audit, String Normalization & Grouped Summary is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).
Runs three local analytical reports on texture streaming records: a record quality audit, string normalization of game_area labels, and a grouped numeric summary of loaded_mb or stream_ms metrics — for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Texture streaming — Record quality audit + String normalisation + Grouped numeric summary: Record quality audit + String normalisation + Grouped numeric summary for supplied texture streaming records (loaded_mb, stream_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
Returns three reports: (1) a record quality audit flagging missing, null, or malformed values per row; (2) normalized/standardized game_area string labels; and (3) a grouped numeric summary (count, sum, mean, min, max, etc.) of the selected field (loaded_mb or stream_ms) aggregated by game_area — all computed locally with no external calls.
Example use cases
Game area streaming data quality check
“I've got 50 texture streaming log rows with game_area, loaded_mb, and stream_ms fields — can you audit them for data quality issues like missing or out-of-range values and also normalize the area name strings?”
Grouped loaded_mb stats by game zone
“Take these 80 texture streaming records and give me a grouped numeric summary of loaded_mb broken down by game_area so I can see which zones are consuming the most texture data.”
Validate and clean streaming records before pipeline
“Before I push this batch of 150 texture streaming rows into our pipeline, can you run a record quality audit and string normalization on the game_area labels so I catch any problems first?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-09-194?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 texture streaming records (with loaded_mb and stream_ms measurements) and need all three of: a record quality audit, string normalization of category labels, and a grouped numeric summary — bundled in one $0.01 call. Prefer this over single-report endpoints when you need all three analyses simultaneously without making separate API calls. Not suitable for live data lookup, prediction, or datasets exceeding 200 rows.
Side effects
- More than 200 rows submitted — request rejected with row count limit error
- Missing required fields (row_id, date, game_area) in one or more rows — validation error returned
- Invalid date format not matching YYYY-MM-DD pattern — schema validation failure
- Field selector not one of 'loaded_mb' or 'stream_ms' — enum validation error
- Empty rows array (minItems: 1 violated) — request rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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