# Inventory Administration String Normalisation and Keyed Dataset Comparison

> Inventory Administration String Normalisation and Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).

Normalizes strings and performs keyed dataset comparison on inventory administration records tracking count sessions and discrepancy counts across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-operations-21-036?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-29
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/inventory-administration-string-normalisation-and-keyed-dataset-c1d6a2f3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_AdvDC6H_7tlDyWR8T89jF

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 inventory-administration-string-normalisation-and-keyed-dataset-c1d6a2f3 -d '<json body>'
```

Example prompt: Compare these two sets of inventory session records — one from our current system and one from the audit — and normalize the team group names, then tell me where count_sessions or discrepancy_count values differ between matching row IDs.

## When to prefer this

Choose this endpoint when you need to reconcile two sets of inventory administration records locally — specifically when you need both string normalization of categorical fields like team_group AND keyed row-level comparison of numeric metrics (count_sessions, discrepancy_count) in a single cheap call. Ideal for audit workflows, data quality checks, and operational reporting where no external lookups or predictions are needed and datasets are under 200 rows.

## Known failure modes

- Missing required fields (row_id, team_group, date, count_sessions, discrepancy_count) causes validation failure
- Exceeding 200 rows per dataset returns an error
- Invalid date format (not YYYY-MM-DD) causes rejection
- Empty rows array triggers minimum-items validation error
- Malformed JSON body returns a 400-level error

## How this service works

Inventory administration — String normalisation + Keyed dataset comparison: String normalisation + Keyed dataset comparison for supplied inventory administration records (count_sessions, discrepancy_count). 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: one covering string normalization results for team_group and string fields, and one covering keyed dataset comparison between the two supplied row arrays, highlighting differences in count_sessions and discrepancy_count values per row_id. No external data is fetched; all analysis is performed locally on submitted data.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/inventory-administration-string-normalisation-and-keyed-dataset-c1d6a2f3/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)