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AI Data Tools - Scraped Data Cleaner
x402
AI Data Tools - Scraped Data Cleaner is a paid API for AI agents from www.aidatatools.dev, paid per call via x402, $0.04/call, status unknown (last checked 2026-09-13).
Deterministically repairs and normalizes scraped data (JSON objects, arrays, CSV, or raw text) and returns the same data shape, cleaned.
Price / call$0.04
Success—
StatusUnknown
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 the same data shape as the input (JSON array of objects, single object, CSV string, or raw text) with fields repaired: normalized prices, corrected special characters, standardized encodings, and fixed formatting inconsistencies — a drop-in replacement for the original scraped data.
Example use cases
E-commerce catalog scrape repair
“I scraped 500 product listings and the prices are formatted like '12,99' or '$12.99 USD' mixed together, and some titles have encoding artifacts like '&' — clean all of them up and give me back the same JSON array with corrected fields.”
Scraped real estate data normalization
“My scraper pulled property listings but the square footage, prices, and address fields are a mess with inconsistent formats and junk characters. Can you repair the data and return it as the same JSON objects, cleaned up?”
CSV pipeline data fix before database load
“I have a CSV string from a scraping job that has broken special characters, inconsistent date formats, and some fields with stray HTML tags — please clean it up deterministically and return a fixed CSV so I can load it into the database.”
Technical details
Endpoint
POSThttps://www.aidatatools.dev/api/cleanWhen to prefer
Choose this endpoint when you have scraped data with deterministic, rule-based repair needs — malformed prices, encoding issues, special character corruption, or inconsistent formatting — and you need the exact same data shape returned. Prefer it over ML-based enrichment tools when reproducibility and determinism are critical, and over validation-only endpoints when you need the data actually fixed, not just flagged. It accepts JSON objects, arrays, CSV, and raw text, making it versatile for scraping pipelines.
Side effects
- Unrecognizable input format that cannot be parsed — likely returns an error or unparseable response
- Input body missing required 'type', 'method', or 'bodyType' fields — returns 400-level validation error
- Extremely large payloads may time out or be rejected
- Ambiguous data where the 'correct' value is unclear may be repaired inconsistently
- Non-UTF-8 or binary content not representable as JSON/text may fail to parse
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"sku": "B0C1",
"price": "12,99",
"title": "Café Table Lamp & Shade"
}
}Tags
x402
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