# Data Quality Gate

> Data Quality Gate is a paid API for AI agents from www.aidatatools.dev, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-14).

Analyzes a JSON dataset and returns a deterministic quality verdict (RELIABLE / USABLE_WITH_CLEANING / UNRELIABLE) with metrics on completeness, nulls, type consistency, duplicates, outliers, and cardinality.

## Facts

- Endpoint: POST https://www.aidatatools.dev/api
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-quality-gate-25bd677a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_VPnAFrFrZKf4AwfWiW0VU

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 data-quality-gate-25bd677a -d '<json body>'
```

Example prompt: Run a data quality check on this JSON dataset and tell me whether it's reliable, usable with cleaning, or unreliable — I need to know about any nulls, duplicates, outliers, and type inconsistencies before I load it into my pipeline.

## When to prefer this

Choose this endpoint when you need a fast, deterministic, traceable data quality verdict on a JSON dataset with no probabilistic or LLM-based variability — ideal for CI/CD data pipelines, pre-model training checks, and vendor data audits where reproducibility and exact metrics matter. Prefer it over LLM-based data review when you need identical outputs for identical inputs and auditable fact-based metrics rather than narrative summaries.

## Known failure modes

- Invalid or malformed JSON payload returns a parsing error
- Empty dataset or zero-row input may return an error or trivial verdict
- Extremely large datasets may time out or exceed payload size limits
- Missing required fields in the JSON body result in a 400-level error

## How this service works

Deterministic post-scrape data cleaner and quality gate for AI agents. Three tiers over one engine, no LLM anywhere: the same input always produces byte-identical output.

**CLEAN** (`POST /api/clean`, $0.04) - post the raw output of a scrape, get the REPAIRED data back as the response body: residual HTML stripped, mojibake decoded ("Café" -> "Café"), invisible characters removed, non-breaking spaces normalised, values trimmed, across nested objects and arrays. It repairs how data was ENCODED and never what it SAYS: a negative price or a failed extraction ("captcha", "access denied") is reported, never rewritten or deleted. Call it after every extraction run - a verdict is cached per source, but dirt is produced fresh by every run.

**CLEAN + AUDIT** (`POST /api/clean/audit`, $0.12) - identical repaired data plus a complete, replayable, reversible ledger of every transformation, with a replay_id and input/output SHA-256. Applying the ledger in reverse reconstructs the input byte for byte.

**VERDICT** (`POST /api`, $0.01) - score + exact facts + a RELIABLE / USABLE_WITH_CLEANING / UNRELIABLE judgement, for deciding whether to trust a source at all. Facts-only signals (price_divergence, text_cleanliness, a robust MAD cross-check) report alongside without moving the score.

What is repaired automatically, what needs an explicit opt-in, and what is only ever reported is published in full at `GET /api/clean` - machine-readable, and auditable before you pay. Paid via x402: no account, no API key, no signup.

## Output

Returns a deterministic quality verdict — one of RELIABLE, USABLE_WITH_CLEANING, or UNRELIABLE — along with exact metrics: completeness percentage, null counts per field, type consistency flags, impossible value detections, duplicate row counts, outlier identifications, and cardinality statistics per column. Results are fully reproducible: identical input always produces identical output.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method",
    "bodyType",
    "body"
   ],
   "properties": {
    "body": {
     "type": "array",
     "items": {
      "type": "object"
     },
     "description": "The scraped data to process. A JSON array of objects, a single object, a CSV string or raw text are all accepted -- the endpoint detects the shape and gives the same shape back."
    },
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "POST",
      "PUT",
      "PATCH"
     ],
     "type": "string"
    },
    "bodyType": {
     "enum": [
      "json",
      "form-data",
      "text"
     ],
     "type": "string"
    }
   },
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object"
    }
   }
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "score": 83.75,
  "checks": [
   {
    "name": "text_cleanliness",
    "detail": "2 of 30 values carry mojibake",
    "status": "warn"
   }
  ],
  "verdict": "RELIABLE"
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-quality-gate-25bd677a/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from www.aidatatools.dev](https://www.zero.xyz/host/www.aidatatools.dev/llms.txt)