# Crawl Response Observations Analyzer — Record Quality Audit + String Normalisation + Category Frequencies

> Crawl Response Observations Analyzer — Record Quality Audit + String Normalisation + Category Frequencies is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-22).

Runs three local analytical reports (record quality audit, string normalisation, and category frequencies) on up to 200 crawl response observation records containing status codes and response times.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-web-01-195?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-22
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/crawl-response-observations-analyzer-record-quality-audit-string-3bb553fc
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_qC0jFbGEHnyDGWC8Fvdt6

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 crawl-response-observations-analyzer-record-quality-audit-string-3bb553fc -d '<json body>'
```

Example prompt: Can you run a quality audit, string normalisation, and category frequency analysis on these crawl response records I have — I've got up to 50 rows with fields like row_id, site_group, date, status_code, and response_ms that I want checked and summarised?

## When to prefer this

Choose this endpoint when you need three simultaneous local analytical reports — quality audit, string normalisation, and category frequencies — on a batch of crawl response records without any external data lookup or prediction. Ideal for data pipeline validation, ETL preprocessing, and exploratory summarisation of web crawl outputs where cost efficiency ($0.01 for all three reports) and offline computation are priorities.

## Known failure modes

- Empty rows array or fewer than 1 row submitted — validation error
- More than 200 rows submitted — exceeds maximum batch size
- Missing required fields (row_id, site_group, date, status_code, response_ms) on any row — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- Numeric fields outside accepted range — schema rejection
- Payment not attached or insufficient — x402 payment required error

## How this service works

Crawl response observations — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies for supplied crawl response observations records (status_code, response_ms). 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

Three structured analytical reports returned together: (1) a record quality audit highlighting completeness, validity, and data issues per row; (2) a string normalisation report cleaning and standardising text fields; (3) category frequency counts for categorical fields such as site_group and status_code. All computed locally with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/crawl-response-observations-analyzer-record-quality-audit-string-3bb553fc/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)