# Research Task Completion — Adjacent Row Changes + Explicit Missing-Value Fill

> Research Task Completion — Adjacent Row Changes + 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 2026-10-22).

Analyzes research task completion records (completed_tasks, assigned_tasks) by detecting adjacent row changes and filling missing values explicitly, producing two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-22-162?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-22
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/research-task-completion-adjacent-row-changes-explicit-missing-value-1d0dcfa6
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_pSFrR9pP10H8mtNZRAwAU

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 research-task-completion-adjacent-row-changes-explicit-missing-value-1d0dcfa6 -d '<json body>'
```

Example prompt: I have 4 rows of daily research task data for two company groups — can you run adjacent row change detection and fill any missing completed_tasks values using the median method? The rows are: 2026-10-01 row-1 group-a assigned=1 completed=10, 2026-10-02 row-2 group-b assigned=2 completed=20, 2026-10-03 row-3 group-a assigned=3 completed=null, 2026-10-04 row-4 group-b assigned=4 completed=30.

## When to prefer this

Choose this endpoint when you need both adjacent row change detection and missing-value imputation on task completion records in a single API call at low cost ($0.01 USDC for both reports). It is ideal for research operations teams that track completed_tasks and assigned_tasks per company group over time and need lightweight, offline data cleaning without live lookups or external data sources. Prefer it over general-purpose data tools when your dataset fits within 200 rows and you want two bundled analytical outputs.

## Known failure modes

- More than 200 rows submitted — request rejected due to maxItems constraint
- Invalid date format (not YYYY-MM-DD) — schema validation error
- Missing required fields (row_id, company_group, date) — row rejected
- Fill method not one of zero/mean/median — enum validation failure
- Field not one of completed_tasks/assigned_tasks — enum validation failure
- Empty rows array (minItems=1 violated) — request rejected

## How this service works

Research task completion — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + Explicit missing-value fill for supplied research task completion records (completed_tasks, assigned_tasks). 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

Two independent analytical reports: (1) an adjacent row changes report identifying where completed_tasks or assigned_tasks values shifted between consecutive rows, and (2) an explicit missing-value fill report showing which null entries were imputed and what values were used (zero, mean, or median), covering up to 200 input rows.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/research-task-completion-adjacent-row-changes-explicit-missing-value-1d0dcfa6/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)