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Research Task Completion — String Normalisation + Secondary-Measure Weighted Mean
x402
Research Task Completion — String Normalisation + 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).
Normalises string fields and computes a secondary-measure weighted mean across up to 200 research task completion records (completed_tasks, assigned_tasks), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Research task completion — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied research task completion records (completed_tasks, assigned_tasks). 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) string-normalised versions of the input records (cleaning company_group and other string fields), and (2) a secondary-measure weighted mean calculated over the chosen field (completed_tasks or assigned_tasks) across all supplied rows, grouped by relevant dimensions such as company_group and date.
Example use cases
Weekly team task completion analysis
“Here are 50 rows of task data from our research teams across three company groups — can you normalise the group name strings and compute a weighted mean of completed_tasks for the week of 2026-10-01, and give me both summary reports?”
Cross-department assigned task weighting
“I need to understand how assigned_tasks are distributed across departments — run string normalisation and give me the secondary-measure weighted mean for assigned_tasks across all 120 rows of our Q4 research records.”
Data quality check with weighted aggregation
“Our research completion dataset for group-a has inconsistent string formatting — can you normalise it and then compute the weighted mean of completed_tasks across all 30 rows so I can compare performance between 2026-10-01 and 2026-10-30?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-22-034?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation of research task labels and a weighted mean of a secondary numeric measure (completed_tasks or assigned_tasks) in a single call on up to 200 rows. It is ideal for lightweight, local analytical processing of task completion datasets without any live lookup, prediction, or external data enrichment. Prefer this over generic analytics APIs when your data is already structured per the schema and you want two complementary reports (normalised records + weighted aggregate) for a flat per-call cost.
Side effects
- Input array is empty or exceeds 200 rows — request rejected
- date field does not match YYYY-MM-DD pattern — validation error
- completed_tasks or assigned_tasks outside numeric bounds — schema rejection
- field enum value not 'completed_tasks' or 'assigned_tasks' — invalid input
- All values for the selected measure are null — weighted mean cannot be computed
- Payment of 0.01 USDC not confirmed — 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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