# Data Collection Completeness — String Normalisation + Daily Sum Series

> Data Collection Completeness — String Normalisation + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-06).

Runs string normalisation and daily sum series analysis on up to 200 data collection completeness records (observed_values, expected_values), returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-education-22-027?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-06
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-collection-completeness-string-normalisation-daily-sum-series-b70ed539
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_A09goIAlqHPcLJgoxPrpM

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 data-collection-completeness-string-normalisation-daily-sum-series-b70ed539 -d '<json body>'
```

Example prompt: Can you run string normalisation and a daily sum series on my data collection completeness records for course groups — I have about 40 rows with observed_values and expected_values by date, and I want both reports on the observed_values field?

## When to prefer this

Choose this endpoint when you need both string normalisation and daily sum series analytics in a single low-cost call on data collection completeness records (observed vs expected values) segmented by course group and date, with no need for live data lookup or external predictions. Ideal for education or monitoring pipelines that batch up to 200 rows and want two complementary reports for $0.01.

## Known failure modes

- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, date, observed_values, expected_values) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Numeric values outside ±1,000,000,000,000 range rejected
- Empty rows array returns an error
- Payment of 0.01 USDC not completed blocks the response

## How this service works

Data collection completeness — String normalisation + Daily sum series: String normalisation + Daily sum series for supplied data collection completeness records (observed_values, expected_values). 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 per call: (1) a string normalisation report processing the string fields in the supplied rows, and (2) a daily sum series report aggregating the selected numeric field (observed_values or expected_values) by date — both computed locally without external lookups or predictions, covering up to 200 input rows.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-collection-completeness-string-normalisation-daily-sum-series-b70ed539/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)