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Proposal Preparation String Normalisation + Trailing Mean Series
x402
Proposal Preparation String Normalisation + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Runs string normalisation and trailing mean series analysis on proposal preparation records (completed_sections, planned_sections) for up to 200 rows, returning 2 analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Proposal preparation — String normalisation + Trailing mean series: String normalisation + Trailing mean series for supplied proposal preparation records (completed_sections, planned_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
Returns 2 analytical reports: (1) a string normalisation report on the proposal preparation records and (2) a trailing mean series report computed over the specified field (completed_sections or planned_sections) with the given window size, covering up to 200 input rows. No external data or predictions are included.
Example use cases
Proposal completion trend smoothing
“I have weekly proposal data for two document groups over the last 8 weeks with completed_sections and planned_sections counts — can you run a trailing mean series with a window of 4 on the completed_sections field to smooth out the weekly noise and normalize the string labels?”
Grant proposal progress reporting
“We track grant proposal writing progress daily with rows showing document_group, date, planned_sections, and completed_sections. Can you run string normalisation and a trailing mean with window size 5 on our 50 rows so we can see a clean rolling average of completed_sections?”
Multi-group proposal pipeline analytics
“I'm managing proposals across 3 document groups and have 120 rows of daily data. Please normalize the string fields and compute a trailing mean series with a window of 7 for the planned_sections field so I can compare trends across groups.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-writing-08-028?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and a trailing mean (rolling average) series computed together on proposal preparation data (completed_sections and planned_sections fields) for up to 200 rows in a single low-cost call. Prefer it over general analytics platforms when working specifically with proposal/document tracking records and needing two bundled local reports without external API calls or predictions.
Side effects
- Fewer than 1 row provided — request rejected (minItems: 1)
- More than 200 rows submitted — request rejected (maxItems: 200)
- Invalid date format (must match YYYY-MM-DD pattern) — validation error
- Window size outside 2–200 range — validation error
- Field value not in enum ['completed_sections','planned_sections'] — validation error
- Null numeric values may be handled gracefully but could affect trailing mean calculations
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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