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Feature Availability Analytics — Trailing Mean Series + Keyed Dataset Comparison
x402
Feature Availability Analytics — Trailing Mean Series + 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 2026-10-20).
Computes a trailing mean time series and a keyed dataset comparison for feature availability records (populated_features vs expected_features) across up to 200 rows in two independent reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feature availability — Trailing mean series + Keyed dataset comparison: Trailing mean series + Keyed dataset comparison for supplied feature availability records (populated_features, expected_features). 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
Returns two independent analytical reports: (1) a trailing mean time series over the selected field (populated_features or expected_features) across the provided rows, and (2) a keyed dataset comparison between the primary rows and the secondary 'other' dataset — both computed locally without any external lookups, for up to 200 input rows.
Example use cases
Feature fill rate trend analysis
“I have daily records of how many features are populated vs expected across two dataset groups over the past month. Can you compute a trailing mean of populated_features and show me a keyed comparison between the two groups so I can see where fill rates are dropping?”
Data pipeline quality monitoring
“My ETL pipeline produces daily feature counts per group — can you run both a trailing mean series and a keyed dataset comparison on this week's populated_features and expected_features data so I can spot any anomalies in completeness?”
Comparing two feature dataset snapshots
“I have two different snapshots of feature availability records for the same date range — one from our production pipeline and one from staging. Can you run a keyed dataset comparison on expected_features so I can see where the two differ?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-10-153?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two complementary analytical views — trailing mean trends and keyed cross-dataset comparison — on feature availability records in a single low-cost call ($0.01 USDC for both reports). Ideal for data quality monitoring, feature store audits, or ETL pipeline validation where you have up to 200 dated records with populated vs expected feature counts grouped by dataset. Prefer this over single-report endpoints when you need both time-series smoothing and cross-dataset diff in one request.
Side effects
- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, date, dataset_group, populated_features, expected_features) — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Null values in both populated_features and expected_features may reduce analytical output quality
- Payment not included or insufficient — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array | |
| window | integer |
Tags
x402
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