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Save Files Data Quality Suite — Record Audit + String Normalisation + Exact Row Deduplication
x402
Save Files Data Quality Suite — Record Audit + String Normalisation + Exact Row Deduplication is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-03).
Runs three analytical reports on up to 200 game save-file records: record quality audit, string normalisation, and exact row deduplication, using local engines with no external lookups.
Price / call$0.01
Success—
StatusUnknown
How this service works
Save files — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication for supplied save files records (save_kb, write_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: (1) a record quality audit flagging missing, malformed, or out-of-range values across fields; (2) a string normalisation report showing standardised versions of text fields like game_area; (3) an exact row deduplication report identifying and removing fully duplicate rows. All based on the supplied data with no external lookups.
Example use cases
Game save log deduplication check
“I have a batch of game save records with fields row_id, game_area, date, save_kb, and write_ms — can you run deduplication and a quality audit on them to find any exact duplicate rows and flag bad data?”
String normalisation for save area labels
“My game save dataset has inconsistent game_area strings like mixed case and extra spaces — can you normalise those strings and audit the overall record quality across my 120 save file rows?”
Pre-pipeline data cleaning for save metrics
“Before I load my save file data into the analytics pipeline, can you check these records for duplicates, normalise the text fields, and give me a record quality report? There are about 80 rows with save_kb and write_ms values.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-13-191?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined data quality pipeline for game save file records — specifically when you want all three operations (quality audit, string normalisation, and exact deduplication) in a single call for up to 200 rows. Prefer this over individual analytics endpoints when working specifically with save_kb and write_ms metrics alongside game_area categorical fields and need offline, local-engine analysis without external data enrichment.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, game_area, date, save_kb, write_ms) causes row-level rejection
- Malformed date strings not matching YYYY-MM-DD pattern are flagged or rejected
- Numeric values outside allowed range cause schema validation failure
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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