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CSV Schema Infer Lite
x402
CSV Schema Infer Lite is a paid API for AI agents from api.delx.ai, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-15).
Infers column names and data type hints from a CSV text sample, returning a deterministic JSON schema report.
Price / call$0.001
Success—
StatusUnknown
How this service works
Infer column names and sample dtypes from CSV text. Call when quick schema report before loading tables. Returns columns with dtype hints as deterministic JSON for $0.001 USDC via x402 on Base. First-party local math only—no RPC, live market feed, API keys, storage, or mediagen. Advisory only; the caller owns capital, risk, and production controls.
Output
A deterministic JSON object listing each column name found in the CSV along with inferred data type hints (e.g. integer, float, string, date), derived purely from the provided CSV text sample using local computation.
Example use cases
Pre-ETL schema preview
“Here's a CSV sample I'm about to load into Postgres — can you quickly infer the column names and dtypes so I know what table schema to create? 'product_id,name,price,stock\n101,Widget A,9.99,250\n102,Widget B,14.50,80'”
Data pipeline validation
“Before my pipeline ingests this CSV, can you tell me the inferred column names and data types so I can catch any type mismatches early? 'date,region,revenue,units\n2024-01-01,West,15200.50,320\n2024-01-02,East,8900.00,190'”
Ad-hoc CSV structure check
“I just got a CSV export from a vendor and I'm not sure what the columns represent — can you infer the schema from this sample? 'ts,user_id,event_type,value\n1700000000,u123,click,1\n1700000001,u456,purchase,49.99'”
Technical details
Endpoint
POSThttps://api.delx.ai/api/v1/x402/csv-schema-inferWhen to prefer
Use this endpoint when you need a fast, cheap ($0.001 USDC), serverless schema preview of CSV text before loading it into a database or pipeline — no API key required, no storage, no external dependencies. Prefer it over full ETL tools when you only need column names and dtype hints from a sample, not full data loading or transformation.
Side effects
- Malformed or empty CSV input returns an error or empty schema
- CSV with no header row may produce incorrect or unnamed column inferences
- Very short samples with one row may yield ambiguous dtype inference
- Non-standard delimiters or encodings may cause parsing failures
- Extremely large CSV text payloads may be rejected or truncated
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| csv | string | CSV text sample |
Output
Schema · Response
{
"type": "json",
"example": {
"schema": "delx/util-csv-schema-infer/v1",
"columns": [
{
"name": "a",
"dtype_hint": "number"
},
{
"name": "b",
"dtype_hint": "string"
}
]
}
}Tags
x402
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