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CSV Data Cleanup & Deduplication API
x402
CSV Data Cleanup & Deduplication API is a paid API for AI agents from well-016-datacleanup.rainmaker-wells.workers.dev, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-22).
Cleans and normalizes a CSV file by trimming whitespace, standardizing dates/emails/phones, applying case rules, and merging or flagging duplicate rows, returning cleaned CSV plus a JSON summary report.
Price / call$0.005
Success—
StatusUnknown
How this service works
Clean a CSV ($0.005 USDC): give an https url or inline csv (max 1 MB / 20k rows). Trims whitespace, optional case rules, dates to ISO 8601, lowercases emails, normalizes phone digits, merges or flags exact + fuzzy duplicate rows on key_columns. Returns cleaned CSV text + JSON report (rows in/out, dupes, columns changed). Deterministic, no AI. As is, no warranty. Nothing stored. Provided as is, with no warranty or guarantee of accuracy or fitness. Nothing is stored.
Output
Returns cleaned CSV text with all normalizations applied (whitespace trimmed, dates in ISO 8601, emails lowercased, phone digits normalized, duplicates merged or flagged), plus a JSON report containing row counts in and out, number of duplicates found, and a list of columns that were changed.
Example use cases
Contact list deduplication before CRM import
“I have a contacts CSV at https://example.com/contacts.csv — can you clean it up, normalize all phone numbers to digits only, lowercase emails, convert dates to ISO 8601 assuming month/day/year order, and merge any fuzzy duplicate rows that share the same 'email' and 'phone' columns?”
Standardize mixed-format sales data
“I've got inline CSV sales data with inconsistent date formats, mixed-case product names, and some duplicate rows. Can you clean it up — convert all dates to ISO 8601 treating ambiguous ones as day/month/year, apply title case to the 'product_name' column, and flag duplicates rather than merging them?”
Pre-import data quality check for a database
“Before I load this CSV into our database, can you trim all whitespace, normalize the emails to lowercase, convert phone numbers to e164 format, standardize dates using month/day/year, and give me a report on how many duplicates were found and what columns changed? The file is at https://example.com/leads.csv”
Technical details
Endpoint
POSThttps://well-016-datacleanup.rainmaker-wells.workers.dev/api/data-cleanup?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need deterministic, rule-based CSV cleaning without AI involvement — especially for normalizing dates, phones, emails, casing, and deduplicating rows with configurable fuzzy matching. It is ideal for pre-import ETL pipelines, contact list cleanup, and data quality checks on files up to 1 MB / 20k rows. Nothing is stored server-side, making it suitable for sensitive data. Prefer it over AI-based cleaning when reproducibility and low cost ($0.005 per call) are priorities.
Side effects
- CSV exceeds 1 MB or 20,000 rows — returns an error indicating size limit exceeded
- URL is not publicly accessible or not HTTPS — returns a fetch error
- Malformed CSV that cannot be parsed — returns a parse error
- fuzzy_threshold outside 0.5–1 range — may return a validation error
- Network timeout fetching remote URL — returns a timeout error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| csv | string | Inline CSV text instead of url (max 1 MB). |
| url | string | Public https URL of a CSV (max 1 MB). |
| fuzzy | boolean | Also match near-duplicates (default true). |
| dedupe | string | merge (default), flag, or none. |
| case_rules | object | Map column -> lower | upper | title. |
| date_order | string | mdy (default) or dmy for ambiguous dates. |
| has_header | boolean | First row is a header (default true). |
| key_columns | array | Columns used to detect duplicates (default all). |
| date_columns | array | Columns to convert to ISO 8601 (default auto). |
| phone_format | string | digits (default) or e164. |
| email_columns | array | Email columns (default auto). |
| phone_columns | array | Phone columns (default auto by header). |
| fuzzy_threshold | number | Similarity 0.5-1 (default 0.92). |
Output
Schema · Response
{
"type": "object",
"additionalProperties": true
}Tags
x402
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