# Tutorial Completion Analytics — String Normalisation + Trailing Mean Series

> Tutorial Completion Analytics — String Normalisation + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).

Runs two local analytical reports on tutorial completion data: string normalisation and a trailing mean series, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-game-20-028?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-30
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/tutorial-completion-analytics-string-normalisation-trailing-mean-series-2fe01fbd
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_qxLUVtFRp00l3puNpxL2Q

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 tutorial-completion-analytics-string-normalisation-trailing-mean-series-2fe01fbd -d '<json body>'
```

Example prompt: Can you run both a string normalisation report and a trailing mean series (window size 3) on my tutorial completion data for the 'completions' field? Here are my records: game-area 'group-a' had 10 starts and 1 completion on 2026-10-01, and 'group-b' had 20 starts and 2 completions on 2026-10-02.

## When to prefer this

Choose this endpoint when you need both string normalisation and a rolling/trailing mean series computed together in a single low-cost call on tutorial completion data (starts and completions) segmented by game area and date. Ideal for e-learning or game analytics pipelines where you want local, offline computation without external API dependencies or prediction models, and your dataset is 200 rows or fewer.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected
- Invalid date format (non-YYYY-MM-DD) causes row-level validation failure
- Missing required fields (row_id, game_area, date, starts, completions) cause schema rejection
- Window size larger than number of rows may yield sparse or empty trailing mean output
- Null values in the selected numeric field may produce gaps in the trailing mean series

## How this service works

Tutorial completion — String normalisation + Trailing mean series: String normalisation + Trailing mean series for supplied tutorial completion records (starts, completions). 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 analytical reports in a single response: (1) a string-normalised view of the game_area labels across supplied rows, and (2) a trailing mean series computed over the selected numeric field ('starts' or 'completions') using the specified rolling window — all computed locally from the supplied data, no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/tutorial-completion-analytics-string-normalisation-trailing-mean-series-2fe01fbd/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)