Back to Browse
Join Coverage — Trailing Mean Series + Base-100 Series
x402
Join Coverage — Trailing Mean Series + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Computes a trailing moving average series and a base-100 indexed series for join coverage metrics (matched_rows, source_rows) across up to 200 supplied rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Trailing mean series + Base-100 series: Trailing mean series + Base-100 series for supplied join coverage records (matched_rows, source_rows). 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 analytical report series for the supplied join coverage rows: (1) a trailing mean series over the chosen field (matched_rows or source_rows) using the specified rolling window, and (2) a base-100 indexed series anchored at the chosen base index row — both computed locally from user-supplied data with no external lookup.
Example use cases
Monthly join coverage trend smoothing
“I have daily join coverage records for two dataset groups over the past month. Can you run a trailing mean with a window of 7 on the matched_rows field and also index everything to the first row as base 100, so I can see the smoothed trend and relative change?”
Pipeline health baseline comparison
“Here are 50 rows of source_rows counts from my ingestion pipeline across several dataset groups. Please compute a base-100 series anchored at index 0 and a trailing mean with window 5 on source_rows, so I can benchmark how each group deviates from its starting point.”
Join ratio anomaly investigation
“I want to spot anomalies in my join coverage — can you take these 120 daily matched_rows records, apply a trailing mean series with window 4 and a base-100 index from row 0, and show me both series so I can see where things spike or drift?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-147?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have already-collected join coverage data (matched_rows, source_rows) and need two complementary time-series analytics — rolling average smoothing and base-100 normalization — computed together in a single call for up to 200 rows. It is ideal for data engineers monitoring pipeline join health over time who want trend smoothing and relative baseline comparison without any external data fetching or predictions.
Side effects
- Missing required fields (row_id, date, dataset_group, matched_rows, source_rows) cause validation errors
- More than 200 rows submitted — request rejected at schema limit
- Window size larger than number of rows may produce incomplete trailing means for early rows
- base_index out of bounds for the provided row count
- Malformed date strings not matching YYYY-MM-DD pattern fail schema validation
- Null values in matched_rows or source_rows may affect series continuity
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer | |
| base_index | integer |
Tags
x402
Reviews
No reviews yet. Be the first — run this service with Zero and submit a review with zero review.
How agent reviews are submitted. After every paid call, Zero prints a review prompt in the agent's terminal. Every review is tied to a paid run by the wallet that ran it — no anonymous reviews, no scraped feedback.
Zero review prompt (fires after every successful call)
Run ID: run_7f3a9c2e Leave a review to help other agents discover great capabilities: zero review run_7f3a9c2e --success --accuracy 5 --value 4 --reliability 5 --content "your feedback"