# Process Handoffs — Numeric Row Ordering + Explicit Missing-Value Fill

> Process Handoffs — Numeric Row Ordering + Explicit Missing-Value Fill 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).

Sorts process handoff records by numeric value and fills missing handoff_count or wait_minutes values using zero, mean, or median imputation, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-operations-18-124?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/process-handoffs-numeric-row-ordering-explicit-missing-value-fill-830ef583
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_mgN_OnFM1RPVWyLhTTuSR

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 process-handoffs-numeric-row-ordering-explicit-missing-value-fill-830ef583 -d '<json body>'
```

Example prompt: I have up to 200 rows of process handoff records with team_group, date, handoff_count, and wait_minutes columns — can you sort them numerically and fill any missing handoff_count values using median imputation, then give me the two reports?

## When to prefer this

Choose this endpoint when you need deterministic, offline numeric ordering and missing-value imputation for process handoff records (handoff_count, wait_minutes) without any live data lookup, prediction, or external API calls. It is ideal for pre-processing up to 200 rows of team handoff data before loading into dashboards or audit reports, and when you need two structured reports in a single low-cost call ($0.01 USDC).

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Invalid date format (must match YYYY-MM-DD pattern)
- Missing required fields (row_id, team_group, date) on any row — validation error
- Unsupported fill method specified (must be zero, mean, or median)
- Invalid field name specified (must be handoff_count or wait_minutes)
- Payment not received or insufficient USDC balance — 402 response

## How this service works

Process handoffs — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied process handoffs records (handoff_count, wait_minutes). 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 two analytical reports covering the supplied process handoff records: one showing numerically ordered rows and one showing the specified field (handoff_count or wait_minutes) with missing values explicitly filled using the chosen method (zero, mean, or median). Reports are generated locally without external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/process-handoffs-numeric-row-ordering-explicit-missing-value-fill-830ef583/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)