# Data Collection Completeness — Numeric Interval Filter + Daily Sum Series

> Data Collection Completeness — Numeric Interval Filter + 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 2026-10-25).

Filters data collection completeness records by a numeric interval and computes a daily sum time series, delivering two independent analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-education-22-125?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-25
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-collection-completeness-numeric-interval-filter-daily-sum-series-85f4c16e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_NvYW4hY1bvPzVKZdb1tD9

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-daily-sum-series-85f4c16e -d '<json body>'
```

Example prompt: Run a numeric interval filter on my data collection completeness records keeping observed_values between 0 and 100, then compute the daily sum series — I have 4 rows across course groups group-a and group-b from October 2026.

## When to prefer this

Choose this endpoint when you need two simultaneous analytical operations — numeric range filtering and daily sum aggregation — on data collection completeness records with observed/expected value pairs, and want both delivered in a single low-cost call ($0.01 USDC). It is purely local computation with no external data lookups, making it deterministic and fast. Best suited for education or monitoring contexts where you have up to 200 timestamped rows tagged by course group and want to understand both which records fall within a numeric band and how daily totals trend over time.

## Known failure modes

- Rows array empty or missing — returns validation error
- date field does not match YYYY-MM-DD pattern — schema validation failure
- observed_values or expected_values outside allowed numeric range (±1 trillion) — rejected
- More than 200 rows submitted — request rejected at maxItems limit
- minimum greater than maximum — may return empty filter results or error
- Payment not provided or insufficient (requires 0.01 USDC via x402) — 402 Payment Required

## How this service works

Data collection completeness — Numeric interval filter + Daily sum series: Numeric interval filter + 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: (1) a numeric interval filter report showing which rows fall within the specified min/max range for the chosen field, and (2) a daily sum series aggregating values by date — both computed locally on the supplied completeness data without any 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-daily-sum-series-85f4c16e/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)