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Tree Canopy Observations — Record Quality Audit + Exact Row Deduplication + Category Frequencies
x402
Tree Canopy Observations — Record Quality Audit + Exact Row Deduplication + Category Frequencies is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Runs three local analytical reports on tree canopy observation records: a record quality audit, exact row deduplication, and category frequency analysis — all in one call for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Tree canopy observations — Record quality audit + Exact row deduplication + Category frequencies: Record quality audit + Exact row deduplication + Category frequencies for supplied tree canopy observations records (canopy_m2, plot_m2). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three independent analytical reports returned together: (1) a record quality audit highlighting missing, null, or out-of-range values in canopy_m2, plot_m2, date, and other fields; (2) an exact row deduplication report identifying identical rows; (3) a category frequency report showing how often each station_group value appears across the dataset.
Example use cases
Pre-analysis data quality check
“Before I run my canopy coverage analysis, can you audit this dataset of 150 tree canopy observations for record quality issues, flag any exact duplicate rows, and tell me how many records fall into each station group?”
Urban forestry station reporting
“I've got canopy measurement records from three station groups collected over October — can you check the data quality, remove any duplicate entries, and give me a frequency breakdown by station group for all 80 rows?”
Dataset validation for regulatory submission
“I need to clean up this tree canopy dataset before submitting it — please run a quality audit, exact deduplication, and category frequency report on these 200 rows with canopy_m2 and plot_m2 values.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-17-212?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tree canopy observation data (canopy_m2, plot_m2, station_group) and need all three of: a data quality audit, exact deduplication, and category frequency counts in a single cost-efficient call. Ideal for preprocessing forestry or environmental monitoring datasets before statistical analysis or regulatory reporting. Not suitable if you need live data lookup, predictive modeling, or reports beyond 200 rows.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, station_group, date, canopy_m2, plot_m2) causes rejection
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Payment not included or insufficient USDC causes 402 response
- Empty rows array (minItems:1 violated) returns error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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