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Request Latency String Normalisation and Keyed Dataset Comparison
x402
Request Latency String Normalisation and Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Normalises strings and compares two keyed datasets of request latency records (latency_ms, request_count) across up to 200 rows, producing 2 analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Request latency — String normalisation + Keyed dataset comparison: String normalisation + Keyed dataset comparison for supplied request latency records (latency_ms, request_count). 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 analytical reports: (1) a string normalisation report that standardises component and other string fields across the supplied rows, and (2) a keyed dataset comparison report that matches rows by key across the two supplied datasets and highlights differences in latency_ms and request_count values. No external lookups or predictions are made; all analysis is performed locally on the supplied data.
Example use cases
Pre/post deployment latency regression check
“I just deployed a new version of our API — here are the latency records from before and after the deploy, each with a component name, date, latency_ms, and request_count. Normalise the component strings and compare the two datasets row by row so I can see where latency got worse.”
A/B test component latency comparison
“I have latency measurements for two groups — group-a and group-b — collected over the past four days. Can you normalise the component labels and run a keyed comparison between the two datasets to tell me which group has higher latency and request counts?”
Staging vs production latency audit
“Here are request latency records from our staging environment and our production environment, up to 200 rows each. Normalise the component names and compare the two datasets so I can see where staging and production latency_ms values diverge.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-software-03-036?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and keyed dataset comparison on request latency data in a single low-cost call. It is ideal for comparing two snapshots of API or service latency metrics — such as before/after a deployment, A/B test groups, or staging vs production — where you want normalised component labels and a structured diff of latency_ms and request_count values across up to 200 rows. It does not perform live lookups, predictions, or external actions, making it suitable for offline or batch analytical workflows.
Side effects
- Missing required fields (row_id, component, date, latency_ms, request_count) causes validation error
- Exceeding 200 rows in either dataset results in rejection
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Null or out-of-range numeric values for latency_ms or request_count may be flagged
- Empty primary rows array causes error (minItems: 1)
- Payment of 0.01 USDC not included causes 402 rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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