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Tutorial Completion Data Quality Suite — Record Audit, String Normalisation & Adjacent Row Changes
x402
Tutorial Completion Data Quality Suite — Record Audit, String Normalisation & Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-01).
Runs three data-quality reports (record quality audit, string normalisation, and adjacent row change detection) on up to 200 tutorial completion records containing starts and completions metrics.
Price / call$0.01
Success—
StatusUnknown
How this service works
Tutorial completion — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied tutorial completion records (starts, completions). 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 independent analytical reports: (1) a record quality audit flagging issues such as nulls, out-of-range values, or malformed rows; (2) a string normalisation report identifying and correcting inconsistencies in text fields like game_area; and (3) an adjacent row change report highlighting significant shifts between consecutive rows in the chosen numeric field (starts or completions). All reports are generated locally from the supplied data with no external lookups.
Example use cases
Game tutorial data quality check
“I've got tutorial completion records for my game across two areas with dates from October 2026 — can you run all three quality reports (record audit, string normalisation, adjacent row changes) on them and check the 'completions' field?”
Pre-analysis string normalisation audit
“Before I run my analysis, can you check my tutorial starts and completions dataset for string inconsistencies in the game_area column and also flag any quality issues in the records? I have about 50 rows.”
Detecting sudden drops in tutorial starts
“I want to know if there are any sudden changes between adjacent rows in my tutorial starts data — can you run the adjacent row change detection report on my 200-row game tutorial completion dataset?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-20-200?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tutorial completion records (with starts/completions counts per game area and date) and need three bundled data-quality reports in a single call at low cost. It is ideal for pre-analysis data hygiene on small-to-medium datasets (up to 200 rows) where you want string normalisation, record auditing, and row-change detection without setting up a local pipeline. Not suitable for real-time monitoring, prediction, or datasets exceeding 200 rows.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, game_area, date, starts, completions) in any row causes validation failure
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- Invalid field enum value (not 'starts' or 'completions') causes an error
- Empty rows array (minItems: 1 not met) returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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