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Experiment Run Timing — Record Quality Audit + String Normalisation + Numeric Interval Filter
x402
Experiment Run Timing — Record Quality Audit + String Normalisation + Numeric 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 2026-11-02).
Runs three local analytical reports on experiment run timing data: a record quality audit, string normalisation, and numeric interval filter for run_seconds or sample_count fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Experiment run timing — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter for supplied experiment run timing records (run_seconds, sample_count). 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 flagging missing, null, or malformed values; (2) a string normalisation report for fields like course_group; and (3) a numeric interval filter report identifying rows where the chosen numeric field (run_seconds or sample_count) falls inside or outside the specified minimum–maximum range. All reports are computed locally from the supplied data with no external lookups.
Example use cases
Pre-analysis data quality check
“I have 120 experiment run timing rows from our education study — can you audit them for quality issues, normalise the course_group strings, and filter out any run_seconds values outside the 5 to 600 range?”
Cleaning course group labels
“Our experiment dataset has inconsistent course_group strings across 80 rows. Can you run string normalisation on them alongside a quality audit, using run_seconds as the filter field with a minimum of 0 and maximum of 500?”
Validating sample counts before reporting
“Before I send this experiment data to the team, can you audit these 200 timing records for quality, normalise the strings, and filter sample_count values to only those between 1 and 1000?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-13-197?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to simultaneously quality-audit, normalise strings, and apply a numeric range filter to experiment run timing records (run_seconds, sample_count) in a single paid call. It is best when your dataset has up to 200 rows and you want all three reports bundled for $0.01 USDC rather than making separate calls. Prefer it over generic data cleaning tools when your data matches the experiment timing schema (course_group, date, run_seconds, sample_count).
Side effects
- Fewer than 1 row submitted — request rejected
- More than 200 rows submitted — exceeds row limit
- Invalid date format (not YYYY-MM-DD) — schema validation error
- Field enum value not 'run_seconds' or 'sample_count' — rejected
- Minimum greater than maximum — may produce empty interval filter results
- Missing required fields (row_id) — row rejected or error returned
- Payment not provided or insufficient USDC — 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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