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Interview Transcripts — Record Quality Audit + Two-Measure Correlation
x402
Interview Transcripts — Record Quality Audit + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).
Audits data quality and computes correlation between transcript_words and audio_minutes for up to 200 interview transcript records, producing two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Interview transcripts — Record quality audit + Two-measure correlation: Record quality audit + Two-measure correlation for supplied interview transcripts records (transcript_words, audio_minutes). 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) a record quality audit identifying missing values, out-of-range entries, formatting issues, and completeness stats across up to 200 rows; (2) a two-measure correlation report quantifying the statistical relationship between transcript_words and audio_minutes, including correlation coefficient and supporting statistics. No external lookups or predictions are made — all analysis uses local analytical engines on the supplied data.
Example use cases
Pre-analysis transcript data validation
“Before I run my research analysis, can you audit the quality of these 50 interview transcript records I collected — checking for missing values, bad dates, or weird entries — and also tell me how strongly the word count correlates with audio duration? Here are the rows with row IDs, channel groups, dates, transcript_words, and audio_minutes.”
Cross-channel transcription consistency check
“I have interview transcripts from two channel groups, group-a and group-b, across 30 sessions. Can you do a record quality audit and run a correlation between transcript_words and audio_minutes to see if the transcription quality differs or if word count tracks recording length consistently?”
Detecting anomalous transcripts in bulk
“I suspect some of my 150 interview transcripts have bad data — maybe recordings that are very long but have very few words, or missing fields. Can you audit the records for quality issues and compute the correlation between word count and audio minutes so I can spot the outliers?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-news-12-015?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular interview transcript data with word counts and audio durations and need both a data quality audit and a Pearson-style correlation between those two measures in a single $0.01 call. It is ideal for pre-processing pipelines, research data validation, or QA workflows where you want to detect bad records and measure transcript-audio alignment simultaneously without any external API calls or live predictions.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, transcript_words, audio_minutes, channel_group) causes row-level rejection
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Submitting fewer than 1 row returns a minimum items error
- Null values in both numeric measures may degrade correlation output quality
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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