# Sensor Calibration Record Quality Audit and Adjacent Row Changes

> Sensor Calibration Record Quality Audit and Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).

Audits sensor calibration records for quality issues and detects adjacent row changes across reference_value and sensor_value fields for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-20-011?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-30
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/sensor-calibration-record-quality-audit-and-adjacent-row-changes-8c2c49f1
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_z6t-9S3yJK7ucU26zBQuD

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 sensor-calibration-record-quality-audit-and-adjacent-row-changes-8c2c49f1 -d '<json body>'
```

Example prompt: Can you audit these sensor calibration records — I have up to 50 rows with row_id, station_group, date, reference_value, and sensor_value — and give me both a record quality audit and a report of adjacent row changes on the reference_value field?

## When to prefer this

Use this endpoint when you have sensor calibration data with reference and sensor value pairs and need both a record-level quality audit and adjacent row change detection in a single call. It is ideal for preprocessing calibration logs before statistical analysis, detecting step changes in time series sensor data, or validating data integrity before reporting. Best when you have up to 200 rows and need two complementary diagnostic reports at low cost without any external data lookups or live predictions.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, reference_value, sensor_value) — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (-1e12 to 1e12) — rejection
- Empty rows array — minimum items constraint violated
- Invalid field enum value (must be reference_value or sensor_value) — schema error

## How this service works

Sensor calibration — Record quality audit + Adjacent row changes: Record quality audit + Adjacent row changes for supplied sensor calibration records (reference_value, sensor_value). 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: (1) a record quality audit identifying data completeness issues, null values, format problems, and anomalies in the calibration rows; and (2) an adjacent row changes report highlighting where consecutive rows show value changes in the selected field (reference_value or sensor_value). Both reports are computed locally against the supplied data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/sensor-calibration-record-quality-audit-and-adjacent-row-changes-8c2c49f1/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)