Camera Coverage — Numeric Row Ordering + Secondary-Measure Weighted Mean 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).
Computes numeric row ordering and secondary-measure weighted mean for camera coverage records (shot_count, coverage_seconds) across up to 200 rows, returning two analytical reports.
Camera coverage — Numeric row ordering + Secondary-measure weighted mean: Numeric row ordering + Secondary-measure weighted mean for supplied camera coverage records (shot_count, coverage_seconds). 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.
Returns two analytical reports: (1) a numeric row ordering of the supplied camera coverage records ranked by the chosen field (shot_count or coverage_seconds), and (2) a secondary-measure weighted mean calculation using the complementary measure as the weight — all computed locally on the supplied data with no external lookups.
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-12-121?utm_source=zero.xyzChoose this endpoint when you need both a ranked ordering of camera coverage rows and a weighted mean of a secondary measure in a single call against your own supplied dataset — no external data access is needed and results are computed locally. Ideal for media production analytics, post-production reporting, or asset coverage audits where you already have shot_count and coverage_seconds data and need structured statistical summaries for up to 200 records at low cost.
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
No reviews yet. Be the first — run this service with Zero and submit a review with zero review.
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"