# Tree Canopy Observations — Record Quality Audit + String Normalisation + Base-100 Series

> Tree Canopy Observations — Record Quality Audit + String Normalisation + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).

Runs three analytical reports on tree canopy observation records: a record quality audit, string normalisation, and a base-100 indexed time series — all computed locally without external lookups.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-17-201?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/tree-canopy-observations-record-quality-audit-string-normalisation-05d83336
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_qXltSCJUYQ-wN392u6gVT

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 tree-canopy-observations-record-quality-audit-string-normalisation-05d83336 -d '<json body>'
```

Example prompt: Can you run a record quality audit, string normalisation, and base-100 index series on my tree canopy observations? I have up to 50 rows with fields row_id, station_group, date, canopy_m2, and plot_m2 — index on canopy_m2 starting from row 0.

## When to prefer this

Choose this endpoint when you have tree canopy observation records (canopy_m2, plot_m2) and need all three of: a data quality audit, string normalisation of categorical labels, and a base-100 time series — in a single call at low cost. It is ideal for pre-analysis data cleaning pipelines where the dataset is up to 200 rows and no external data enrichment or prediction is needed.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, date, canopy_m2, plot_m2) cause row-level errors
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- base_index out of range (>= number of rows) causes index computation error
- Payment not included or insufficient USDC causes 402 rejection
- All null values in the selected field may produce an empty or degenerate base-100 series

## How this service works

Tree canopy observations — Record quality audit + String normalisation + Base-100 series: Record quality audit + String normalisation + Base-100 series for supplied tree canopy observations records (canopy_m2, plot_m2). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Returns three reports for the supplied canopy observation rows: (1) a record quality audit flagging missing, null, or malformed values; (2) a string normalisation report for the station_group field; and (3) a base-100 indexed numeric series for the chosen field (canopy_m2 or plot_m2) anchored at the specified base row index.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "station_group",
     "date",
     "canopy_m2",
     "plot_m2"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "plot_m2": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "canopy_m2": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "station_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "plot_m2": 1,
     "canopy_m2": 10,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "plot_m2": 2,
     "canopy_m2": 20,
     "station_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "plot_m2": 3,
     "canopy_m2": 15,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "plot_m2": 4,
     "canopy_m2": 30,
     "station_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "canopy_m2",
    "plot_m2"
   ],
   "type": "string",
   "default": "canopy_m2"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/tree-canopy-observations-record-quality-audit-string-normalisation-05d83336/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)