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Task Throughput Data Quality & Analytics — Audit, Normalisation, Interval Filter
x402
Task Throughput Data Quality & Analytics — Audit, Normalisation, Interval Filter is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Runs three analytical reports on task throughput records: record quality audit, string normalisation, and numeric interval filtering for tasks_started/tasks_completed data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Task throughput — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter for supplied task throughput records (tasks_started, tasks_completed). 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
Returns three independent analytical reports: (1) a record quality audit flagging data issues such as missing or malformed fields, (2) a string normalisation report on team_group and other string fields, and (3) a numeric interval filter report identifying rows where the selected field (tasks_started or tasks_completed) falls within or outside the specified minimum/maximum range. Up to 200 rows processed per call.
Example use cases
Sprint data cleanup before reporting
“I have 150 rows of daily task throughput data from multiple team groups and I need you to audit them for quality issues, normalise the team_group strings, and filter out any rows where tasks_completed is below 0 or above 200 before I build my sprint report.”
Validate exported ops data
“Can you check this batch of operations task records for data quality problems, clean up the team_group names, and filter tasks_started to only keep values between 1 and 100? There are about 80 rows with date, row_id, team_group, tasks_started, and tasks_completed.”
Flag anomalous task counts in team logs
“I've got daily logs from our teams — around 60 rows — and I want to run a record quality audit, normalise any inconsistent team_group strings, and filter so I only see rows where tasks_completed is between 5 and 300. Can you do all three checks at once?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-operations-02-197?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to simultaneously audit data quality, normalise strings, and apply a numeric range filter to task throughput records in a single low-cost call. It is best suited for batches up to 200 rows of operational task data (tasks_started/tasks_completed) where no live data lookup, prediction, or external enrichment is needed — purely local analytical processing of supplied data.
Side effects
- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, date, tasks_started, tasks_completed) — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Minimum greater than maximum threshold — undefined filter behaviour
- Numeric values outside allowed bounds (±1,000,000,000,000) — schema rejection
- Empty rows array — minItems constraint violation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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