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Redirect Observations Analyzer — Record Quality Audit, String Normalisation & Trailing Mean Series
x402
Redirect Observations Analyzer — 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 redirect observation data containing redirect counts and final HTTP status codes, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Redirect observations — Record quality audit + String normalisation + Trailing mean series: Record quality audit + String normalisation + Trailing mean series for supplied redirect observations records (redirect_count, final_status_code). 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 derived from the submitted redirect observation rows: (1) a record quality audit flagging data issues, (2) a string normalisation report for text fields, and (3) a trailing mean series computed over the specified numeric field (redirect_count or final_status_code) using the given window size. All computed locally with no external lookups.
Example use cases
Web redirect quality audit for site groups
“I have a dataset of redirect observations with redirect counts and final HTTP status codes across different site groups. Can you audit the record quality, normalise the strings, and give me a trailing mean series with a window of 5 for redirect_count?”
Rolling average on HTTP status code trends
“Can you compute a trailing mean series with window size 4 on the final_status_code field from my redirect tracking records? I also want a quality audit and string normalisation report on the same data.”
Data cleaning for redirect monitoring pipeline
“I need to clean up my redirect monitoring data before feeding it into our dashboard — can you run a string normalisation and record quality audit on my 150-row dataset of redirect observations grouped by site?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-web-14-199?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined data-quality, normalisation, and rolling-average analysis on redirect observation records in a single low-cost call. It is ideal for web analytics pipelines where redirect_count and final_status_code data needs auditing and smoothing before further processing, and when you want all three reports for a flat fee rather than calling separate services.
Side effects
- Submission of more than 200 rows results in rejection
- Missing required fields (row_id, site_group, date, redirect_count, final_status_code) cause validation errors
- Invalid date format (not YYYY-MM-DD) rejected by schema
- Window size outside 2–200 range is rejected
- Numeric values outside allowed range cause schema validation failure
- Empty rows array not accepted (minimum 1 row required)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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