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Survey Participation — String Normalisation + Keyed Dataset Comparison
x402
Survey Participation — String Normalisation + Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-04).
Normalises strings and compares two keyed survey participation datasets (respondents and invitations) across up to 200 rows, producing two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Survey participation — String normalisation + Keyed dataset comparison: String normalisation + Keyed dataset comparison for supplied survey participation records (respondents, invitations). 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
Two analytical reports: (1) a string normalisation report covering the supplied survey participation rows, and (2) a keyed dataset comparison report identifying differences between the two supplied datasets by row ID, covering respondents and invitations fields across up to 200 rows. No external lookups or predictions are made; all analysis uses local engines.
Example use cases
Reconcile survey response counts between data exports
“We pulled survey participation records from two different exports — both have the same row IDs and course groups but some respondent and invitation counts differ. Can you normalise the strings and run a keyed comparison across all rows to show me exactly which records changed?”
Audit course group name consistency across datasets
“I have two batches of survey data for our education programme — the course group labels might be inconsistently capitalised or formatted. Can you normalise the string fields in both datasets and flag any keyed differences in respondents or invitations?”
Validate survey data before merging two sources
“Before we merge our survey participation tables, I want to verify that both sources agree on respondents and invitation counts for each row ID and date. Can you normalise the strings and compare the two datasets to produce a discrepancy report?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-10-036?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have two sets of survey participation records (with respondents and invitations counts keyed by row ID, course group, and date) and need both string normalisation and a structured keyed comparison in a single low-cost call. It is ideal for education analytics pipelines that need to reconcile or audit two exports of survey data without requiring external lookups or live data sources. At $0.01 USDC for two reports on up to 200 rows, it is cost-effective for routine data quality checks.
Side effects
- Input arrays exceed 200 rows — request will be rejected or truncated
- Missing required fields (row_id, course_group, date, respondents, invitations) cause validation errors
- Date strings not matching YYYY-MM-DD pattern will fail schema validation
- Numeric values outside the allowed range (±1,000,000,000,000) will be rejected
- Empty rows array (minItems:1 not satisfied) returns an error
- Mismatched row_id keys between the two datasets may result in unmatched rows in comparison report
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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