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Policy Revision Tracking — String Normalisation + Secondary-Measure Weighted Mean
x402
Policy Revision Tracking — String Normalisation + Secondary-Measure Weighted Mean 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).
Applies string normalisation and secondary-measure weighted mean analytics to policy revision tracking records (revised_sections, total_sections) in up to 200 rows, returning 2 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Policy revision tracking — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied policy revision tracking records (revised_sections, total_sections). 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 independent analytical reports per call: (1) string-normalised representation of the selected field values across all input rows, and (2) a secondary-measure weighted mean computed using the paired numeric fields (revised_sections, total_sections), segmented by document_group and date as applicable. All computation is local with no external lookups.
Example use cases
Compliance team revision coverage check
“I have 50 rows of policy document data for Q4 — each row has a document group, a date, revised_sections, and total_sections. Can you normalise the revised_sections strings and compute a weighted mean against total_sections so I can see which groups have the highest revision coverage?”
Policy audit across multiple document groups
“We're auditing 120 policy records across 8 document groups from January through March. Please run string normalisation and the secondary-measure weighted mean on the total_sections field across all rows and give me both reports.”
Monthly policy change summary for legal team
“I've got 80 rows of monthly policy revision tracking data — row IDs, dates, document groups, revised_sections counts, and total_sections. Can you apply string normalisation and calculate a weighted mean for revised_sections so I can share a clean summary with the legal team?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-writing-11-034?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and weighted mean analytics on policy revision tracking data in a single cheap call ($0.01 USDC for 2 reports). Ideal for compliance, legal, or document management workflows where you have up to 200 structured rows with section counts and need clean statistical summaries without any external data lookups or predictions.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, revised_sections, total_sections) causes row rejection
- Dates not matching YYYY-MM-DD pattern fail schema validation
- Null values in both numeric fields may produce undefined weighted mean results
- Invalid field enum value (not 'revised_sections' or 'total_sections') causes request failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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