# Data Collection Completeness — Numeric Interval Filter + Secondary-Measure Weighted Mean

> Data Collection Completeness — Numeric Interval Filter + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).

Filters data collection completeness records by a numeric interval on one field and computes a secondary-measure weighted mean, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-education-22-132?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-collection-completeness-numeric-interval-filter-secondary-5ba92bc3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_zTHHiP-063g37JrAW7f00

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-numeric-interval-filter-secondary-5ba92bc3 -d '<json body>'
```

Example prompt: I have 150 rows of course data collection completeness records with observed and expected values for groups like 'group-a' and 'group-b' — can you filter the observed_values between 0 and 100 and compute a weighted mean report using expected_values as the secondary measure?

## When to prefer this

Choose this endpoint when you have up to 200 education or data collection completeness records and need both interval-based numeric filtering and a weighted mean statistic in a single low-cost call ($0.01 USDC for 2 reports). Prefer this over general-purpose analytics tools when working specifically with observed/expected value completeness pairs organized by course group and date.

## Known failure modes

- Missing required fields (row_id, observed_values, expected_values) causes validation error
- More than 200 rows submitted exceeds the maximum row limit
- Invalid date format (non YYYY-MM-DD) triggers pattern validation failure
- Null values in the weight/measure field may affect weighted mean calculation
- minimum greater than maximum produces an empty filtered result set
- Payment failure via x402 protocol prevents endpoint execution

## How this service works

Data collection completeness — Numeric interval filter + Secondary-measure weighted mean: Numeric interval filter + Secondary-measure weighted mean 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

Returns two analytical reports covering: (1) the subset of input rows whose selected field falls within the specified [minimum, maximum] interval, and (2) a secondary-measure weighted mean computed across those filtered records, all derived locally from the supplied data without external lookups.

## 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"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-collection-completeness-numeric-interval-filter-secondary-5ba92bc3/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)