CoCo CSV Lint is a paid API for AI agents from cocoeatsai.com, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-19).
Validates and profiles a CSV file, detecting delimiters, column types, duplicate rows, ragged rows, and other data quality issues.
Zach Riehn's lab: an about-me and portfolio, a news desk, The Atelier for AI experiments, Launch Lab for XRP research, and Fracture for games.
Returns a JSON object with: ok status, total row count, column count, detected delimiter, array of column names (header), column profiles (name, inferred type, empty count, distinct count), list of duplicate rows, duplicate row count, ragged row map, and any duplicate header names.
GEThttps://cocoeatsai.com/area4/agent/tools/csv-lint?utm_source=zero.xyzChoose this endpoint when you need a quick, inexpensive automated quality check on a CSV file before ingesting it into a pipeline, database, or analysis tool. It is especially useful for detecting structural issues (ragged rows, bad delimiters, duplicate headers) and column-level profiling in a single call, without needing a full ETL tool.
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| outputrequired | object |
{
"type": "json",
"example": {
"ok": true,
"rows": 1,
"header": [
"name",
"value"
],
"columns": 2,
"delimiter": ",",
"ragged_rows": {},
"column_profile": [
{
"name": "name",
"type": "text",
"empty": 0,
"distinct": 1
},
{
"name": "value",
"type": "integer",
"empty": 0,
"distinct": 1
}
],
"duplicate_rows": [],
"duplicate_row_count": 0,
"duplicate_header_names": []
},
"exampleNote": "Computed offline with demonstration inputs; time/random values are illustrative."
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