# Proposal Preparation Data Cleaner — Exact Row Deduplication + IQR Outlier Flags

> Proposal Preparation Data Cleaner — Exact Row Deduplication + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).

Deduplicates exact rows and flags IQR-based outliers in proposal preparation records (completed_sections, planned_sections) for up to 200 rows, producing 2 independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-writing-08-049?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-25
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/proposal-preparation-data-cleaner-exact-row-deduplication-iqr-outlier-bb6b5035
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_8fwpNcpZHLbQWwnlW_xfy

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-cleaner-exact-row-deduplication-iqr-outlier-bb6b5035 -d '<json body>'
```

Example prompt: Can you deduplicate and flag IQR outliers in my proposal preparation data? I have rows with row_id, document_group, date, completed_sections, and planned_sections — up to 200 rows — and I want 2 reports checking the completed_sections field.

## When to prefer this

Choose this endpoint when you need fast, local (no external lookup) data quality analysis on proposal preparation records specifically containing completed_sections and planned_sections fields. It is ideal for pre-analysis data cleaning pipelines where you want both exact deduplication and statistical outlier detection in a single cheap call ($0.01 USDC). Prefer this over generic data tools when your data fits the proposal tracking schema and you need two simultaneous report types without sending data to an ML or prediction service.

## Known failure modes

- Fewer than 1 row submitted — request rejected
- More than 200 rows submitted — exceeds batch limit
- Invalid date format (non-YYYY-MM-DD) — schema validation error
- Missing required fields (row_id, document_group, date, completed_sections, planned_sections) — validation failure
- Invalid field enum value (not completed_sections or planned_sections) — schema rejection
- All rows unique — deduplication report returns empty duplicate set
- Insufficient data spread for IQR calculation (too few rows or zero variance) — outlier report may return no flags

## How this service works

Proposal preparation — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags 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 independent analytical reports: (1) an exact row deduplication report identifying which rows are exact duplicates, and (2) an IQR-based outlier flagging report identifying rows where the selected numeric field (completed_sections or planned_sections) falls outside the interquartile range bounds.

## 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/proposal-preparation-data-cleaner-exact-row-deduplication-iqr-outlier-bb6b5035/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)