# Proposal Preparation Data Quality & Correlation Analysis

> Proposal Preparation Data Quality & Correlation Analysis 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 three independent analytical reports on proposal preparation records: a record quality audit, string normalisation, and two-measure correlation between completed_sections and planned_sections.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-writing-08-204?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-data-quality-correlation-analysis-2c2b2f4d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap__pjRgEztp-cbfWDBe-Cxw

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-data-quality-correlation-analysis-2c2b2f4d -d '<json body>'
```

Example prompt: Can you audit the quality of my proposal preparation data, normalise the strings, and check the correlation between planned and completed sections? I have rows for document groups like 'group-a' and 'group-b' with dates in October 2026 and section counts — up to 50 rows total.

## When to prefer this

Choose this endpoint when you need a combined quality audit, string normalisation, and correlation analysis on proposal preparation records (with completed_sections and planned_sections fields) in a single call at low cost ($0.01 USDC). It is ideal for pre-reporting data hygiene checks on batches of up to 200 proposal rows. Prefer it over general-purpose analytics tools when your data conforms to the proposal preparation schema and you want three bundled reports without external data dependencies.

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, date, completed_sections, planned_sections) cause rejection
- Dates not matching YYYY-MM-DD pattern fail schema validation
- Null values in both numeric fields across all rows may produce degenerate correlation results
- Empty rows array (minItems:1 not met) returns a schema error

## How this service works

Proposal preparation — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation for supplied proposal preparation records (completed_sections, planned_sections). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Three independent analytical reports: (1) a record quality audit highlighting missing values, type issues, and anomalies across all rows; (2) a string normalisation report standardising document_group and other string fields; (3) a two-measure correlation report quantifying the statistical relationship between completed_sections and planned_sections across the supplied rows. All reports are generated from the supplied data only — no external lookups or predictions.

## 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/proposal-preparation-data-quality-correlation-analysis-2c2b2f4d/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)