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Frame Timing Record Quality Audit + String Normalisation + Secondary-Measure Weighted Mean
x402
Frame Timing Record Quality Audit + String Normalisation + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).
Audits quality, normalises strings, and computes a secondary-measure weighted mean for up to 200 frame timing records (frame_ms, draw_calls) in three independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Frame timing — Record quality audit + String normalisation + Secondary-measure weighted mean: Record quality audit + String normalisation + Secondary-measure weighted mean for supplied frame timing records (frame_ms, draw_calls). 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 covering: (1) a record quality audit flagging missing, out-of-range, or malformed values in the supplied frame timing rows; (2) string normalisation results for text fields such as game_area; and (3) a secondary-measure weighted mean of the chosen primary field (frame_ms or draw_calls) weighted by the other measure — all computed locally with no external lookups.
Example use cases
Game area string cleanup and quality check
“I have 150 frame timing records from our game build with messy game_area labels and some null values in frame_ms — can you run a record quality audit and string normalisation on all of them so I can see what's dirty before I import it into our database?”
Weighted mean frame time by draw call volume
“I want to compute a draw_calls-weighted average of frame_ms across my 80 frame timing rows — can you run the secondary-measure weighted mean report on this data and give me the result?”
Full three-report pipeline for performance regression
“We just finished a performance regression test and I have 200 rows of frame timing records with game_area, date, frame_ms, and draw_calls — please run all three reports: quality audit, string normalisation, and weighted mean using frame_ms, so I can identify bad records and get a clean aggregate summary.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-01-205?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three combined analytical reports — quality audit, string normalisation, and weighted mean — specifically for frame timing game performance data (frame_ms and draw_calls fields) in a single $0.01 call covering up to 200 rows. Prefer it over general analytics APIs when you want a bundled, low-cost batch analysis with no external data lookups or predictions.
Side effects
- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, game_area, date, frame_ms, draw_calls) in any row — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- field enum value not 'frame_ms' or 'draw_calls' — rejected
- All rows have null values for chosen field — weighted mean cannot be computed
- Numeric values outside allowed range — clamped or flagged in audit report
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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