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Peer Feedback Daily Sum Series + Two-Measure Correlation
x402
Peer Feedback Daily Sum Series + 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).
Computes a daily sum time series and a two-measure correlation (review_count vs actioned_comments) from supplied peer feedback records, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Peer feedback — Daily sum series + Two-measure correlation: Daily sum series + Two-measure correlation for supplied peer feedback records (review_count, actioned_comments). 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 analytical reports: (1) a daily sum series showing the aggregated total of the selected field (review_count or actioned_comments) grouped by date across up to 200 input rows, and (2) a Pearson or similar correlation coefficient and supporting statistics measuring the linear relationship between review_count and actioned_comments in the supplied data.
Example use cases
Course group engagement trend analysis
“I've collected peer feedback data for two course groups over October — can you aggregate the review_count into a daily sum series and also tell me how strongly review_count correlates with actioned_comments across all the rows?”
Instructor feedback quality audit
“I have 150 rows of peer feedback records with dates, course groups, review counts, and actioned comment numbers. Can you compute the daily totals for actioned_comments and run a correlation between review_count and actioned_comments so I can see if more reviews lead to more actioned feedback?”
Weekly reporting on peer review activity
“Generate a daily sum series for our peer review counts and a two-measure correlation between review_count and actioned_comments using this dataset of 80 feedback records — I need both reports for our weekly education analytics summary.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-23-141?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you already have peer feedback data on hand (up to 200 rows) and need both a daily aggregation time series and a bivariate correlation between review_count and actioned_comments in a single low-cost call. It is ideal for education analytics pipelines, course group reporting, or instructor dashboards where no external data lookup or prediction is needed — just fast, local statistical computation on your supplied dataset.
Side effects
- Input array exceeds 200 rows — request is rejected or truncated
- Missing required fields (row_id, date, review_count, actioned_comments) cause validation errors
- Malformed date strings not matching YYYY-MM-DD pattern cause parsing failures
- Null values in both numeric measures may reduce correlation sample size or return NaN
- Insufficient variation in data may produce undefined or near-zero correlation
- Payment not supplied or insufficient USDC causes 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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