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Localization Coverage — Record Quality Audit + String Normalisation + Trailing Mean Series
x402
Localization Coverage — Record Quality Audit + String Normalisation + Trailing Mean Series 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).
Runs three analytical reports (record quality audit, string normalisation, and trailing mean series) on localization coverage data (source_strings, translated_strings) for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Localization coverage — Record quality audit + String normalisation + Trailing mean series: Record quality audit + String normalisation + Trailing mean series for supplied localization coverage records (source_strings, translated_strings). 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 missing, null, or malformed fields; (2) a string normalisation report standardising the source_strings and translated_strings values; and (3) a trailing mean series computing a rolling average over the specified window for the selected field — all computed locally with no external lookups.
Example use cases
Game UI localisation progress audit
“I have 50 rows of localization coverage records for my game, each with a date, game area, source string count, and translated string count. Can you run a record quality audit, string normalisation, and a trailing mean series with window 5 on the translated_strings field to see how translation progress is trending?”
Detect dirty data in translation records
“We have a batch of localization records across three game areas — 'cutscenes', 'menus', and 'tutorials' — and I suspect some rows have null or inconsistent string counts. Run the quality audit and string normalisation reports on these 120 rows so I can find and fix the bad data.”
Rolling average of source strings by date
“Can you compute a trailing mean series with a window of 4 for source_strings across my 80 localization coverage rows dated between 2026-09-01 and 2026-11-30? I want to see the smoothed trend alongside the quality audit for those records.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-18-199?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need all three analytical operations — quality audit, string normalisation, and trailing mean computation — applied together to localization coverage data in a single call at low cost ($0.01 USDC). It is ideal for game localisation pipelines where you want to validate data integrity, clean string counts, and compute rolling averages in one batch without any external API calls or live data dependencies.
Side effects
- Exceeding 200 rows causes the request to be rejected
- Invalid date format (not YYYY-MM-DD) triggers a validation error
- Missing required fields (row_id, source_strings, translated_strings) cause record-level audit failures
- Window size outside 2–200 range is rejected
- Non-numeric source_strings or translated_strings values may cause normalisation errors
- Payment not included or insufficient USDC triggers a 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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