# Proposal Preparation String Normalisation + Trailing Mean Series

> 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.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-writing-08-028?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/proposal-preparation-string-normalisation-trailing-mean-series-1d023407
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_wVsYY6StQap-MpsWLeAzn

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability proposal-preparation-string-normalisation-trailing-mean-series-1d023407 -d '<json body>'
```

Example prompt: Can you normalize the string fields and compute a trailing mean series with a window of 3 for my proposal preparation data — I have 4 rows with completed_sections values like 10, 20, 15, 30 for group-a and group-b across dates in October 2026, and I want the report for the completed_sections field?

## When to prefer this

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.

## Known failure modes

- 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

## 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.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "document_group",
     "date",
     "completed_sections",
     "planned_sections"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "document_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "planned_sections": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "completed_sections": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "document_group": "group-a",
     "planned_sections": 1,
     "completed_sections": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "document_group": "group-b",
     "planned_sections": 2,
     "completed_sections": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "document_group": "group-a",
     "planned_sections": 3,
     "completed_sections": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "document_group": "group-b",
     "planned_sections": 4,
     "completed_sections": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "completed_sections",
    "planned_sections"
   ],
   "type": "string",
   "default": "completed_sections"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/proposal-preparation-string-normalisation-trailing-mean-series-1d023407/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)