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Cache Telemetry — Base-100 Series + Date by Category Pivot
x402
Cache Telemetry — Base-100 Series + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-22).
Generates two analytical reports from supplied cache telemetry data: a Base-100 indexed time series and a date-by-category pivot table, for up to 200 rows of hit/miss count data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Cache telemetry — Base-100 series + Date by category pivot: Base-100 series + Date by category pivot for supplied cache telemetry records (hit_count, miss_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 returned together: (1) a Base-100 normalized time series for the selected field (hit_count or miss_count), anchored at the specified base_index row, showing relative change across all rows; and (2) a date-by-category pivot table grouping the selected metric by date and component. Results are derived entirely from the supplied data with no external lookups.
Example use cases
Cache efficiency trend analysis
“I've got 90 days of cache telemetry for three microservices — can you index the hit_count data to a Base-100 series starting from row 0 and also give me a pivot of hit counts by date and component so I can see which service degraded over time?”
Cache miss spike investigation
“Something spiked our cache miss_count last week. Can you take these 120 rows of daily telemetry across our CDN components and produce a Base-100 series plus a date-by-category pivot on miss_count, using row 0 as the baseline?”
Multi-component cache benchmarking
“We're benchmarking two cache backends — group-a and group-b — over 60 days. Run a Base-100 indexed series and a date-by-component pivot on the hit_count field from these records so we can compare their relative performance trajectories.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-software-06-167?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have structured cache telemetry rows (hit/miss counts by component and date) and need both a relative-indexed time series and a cross-tabulated pivot in a single low-cost call. Ideal for software teams analyzing cache efficiency trends without standing up local analytics infrastructure. Not suitable for live cache monitoring, prediction, or datasets exceeding 200 rows.
Side effects
- Missing required fields (row_id, component, date, hit_count, miss_count) cause validation errors
- More than 200 rows submitted exceeds the maxItems limit and will be rejected
- Invalid date format (not YYYY-MM-DD) will fail pattern validation
- base_index pointing to a row with a zero or null value may cause division errors in Base-100 normalization
- Payment failure (insufficient USDC balance) prevents processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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