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Tutorial Completion Record Quality Audit and String Normalisation
x402
Tutorial Completion Record Quality Audit and String Normalisation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Runs two independent analytical reports on supplied tutorial completion records — a record quality audit and string normalisation — for up to 200 rows, using local engines with no external lookups.
Price / call$0.01
Success—
StatusUnknown
How this service works
Tutorial completion — Record quality audit + String normalisation: Record quality audit + String normalisation for supplied tutorial completion records (starts, completions). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Two independent analytical reports: (1) a record quality audit identifying issues such as missing values, out-of-range numbers, duplicate row IDs, or malformed dates across the supplied rows; and (2) a string normalisation report showing cleaned and standardised versions of string fields like game_area. No external data sources are used — analysis is performed locally on the supplied rows only.
Example use cases
Pre-analysis data quality check
“Before I run my funnel analysis, can you audit these 150 tutorial completion rows for data quality issues and normalise the game_area labels? The rows have row_id, date, game_area, starts, and completions fields.”
Cleaning inconsistent game area labels
“My tutorial tracking dataset has messy game_area strings — things like 'Group A', 'group-a', and 'GROUP A' mixed together. Can you normalise them and flag any record quality problems across these 80 rows?”
Weekly tutorial data validation
“I've exported this week's tutorial starts and completions data — about 60 rows — can you run a record quality audit and string normalisation report so I can spot any bad data before sending it to the dashboard?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-20-001?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw tutorial completion records (starts, completions by game area and date) that need pre-analysis data hygiene — specifically a quality audit and string normalisation — in a single low-cost call. It is ideal for batch offline validation of up to 200 rows without needing live data lookups, predictions, or external enrichment. Prefer it over general-purpose data cleaning tools when your data model matches the game/tutorial engagement schema (row_id, game_area, date, starts, completions).
Side effects
- Rows array is empty or missing — returns validation error
- More than 200 rows supplied — rejected with maxItems error
- row_id field missing or blank — schema validation failure
- date field does not match YYYY-MM-DD pattern — rejected
- starts or completions values outside allowed numeric range — schema rejection
- Malformed JSON payload — parse error returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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