# Feature Availability — String Normalisation + Daily Sum Series

> Feature Availability — 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 2026-10-20).

Runs two local analytical reports on feature availability data: string normalisation and daily sum series, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-10-027?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/feature-availability-string-normalisation-daily-sum-series-138e3f35
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_8LqWh7a1fTriqR995v3Pb

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 feature-availability-string-normalisation-daily-sum-series-138e3f35 -d '<json body>'
```

Example prompt: Can you run a string normalisation and daily sum series analysis on my feature availability records? I have rows for dataset groups 'group-a' and 'group-b' from 2026-10-01 to 2026-10-04, with populated_features and expected_features values, and I want the report on the populated_features field.

## When to prefer this

Choose this endpoint when you need both string normalisation and a daily sum series on feature availability records in a single low-cost call (up to 200 rows, $0.01 USDC). Ideal for lightweight, offline analytical pipelines that do not require live data lookups, predictions, or external enrichment. Prefer it over separate analytics services when you want two bundled reports computed locally on supplied data.

## Known failure modes

- Exceeds 200-row limit — request rejected, reduce batch size
- Invalid date format (not YYYY-MM-DD) — validation error
- Missing required fields (row_id, date, populated_features, expected_features) — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — validation error
- Invalid field enum value (must be 'populated_features' or 'expected_features') — rejected

## How this service works

Feature availability — String normalisation + Daily sum series: String normalisation + Daily sum series for supplied feature availability records (populated_features, expected_features). 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 independent analytical reports: (1) a string normalisation report on the feature availability records and (2) a daily sum series aggregating the selected numeric field (populated_features or expected_features) by date, computed locally without external lookups or live data.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/feature-availability-string-normalisation-daily-sum-series-138e3f35/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)