AI Data Tools – Clean with Audit Trail is a paid API for AI agents from www.aidatatools.dev, paid per call via x402, $0.12/call, status unknown (last checked 2026-09-14).
Repairs scraped data deterministically (e.g. encoding, formatting issues) and returns a replayable, SHA-256-keyed audit ledger of every change made
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.
Returns the cleaned data in the same shape as the input (JSON array of objects, single object, CSV, or text), alongside an audit object containing a ledger array that lists every field path touched, the rule applied (e.g. 'mojibake.repair'), the before and after values, and a SHA-256 replay_id for verifiable, replayable audit purposes.
POSThttps://www.aidatatools.dev/api/clean/auditChoose this endpoint when you need not only cleaned data but a cryptographically verifiable, replayable audit trail of every repair — ideal for compliance-sensitive pipelines, regulated data workflows, or any scenario where you must prove what changed and why. Prefer this over the base clean endpoint when auditability and reproducibility are requirements, not just nice-to-haves.
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
{
"type": "json",
"example": {
"data": [
{
"sku": "B0C1",
"price": "12,99",
"title": "Café Table Lamp & Shade"
}
],
"audit": {
"ledger": [
{
"path": "[0].title",
"rule": "mojibake.repair",
"after": "Café",
"before": "Café"
}
],
"replay_id": "sha256:..."
}
}
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