# CoCo CSV Lint

> 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.

## Facts

- Endpoint: GET https://cocoeatsai.com/area4/agent/tools/csv-lint?utm_source=zero.xyz
- Price: $0.001/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/coco-csv-lint-f23686d3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_C17DIv9IoJ4mbPquZ8plY

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability coco-csv-lint-f23686d3
```

Example prompt: Can you lint this CSV file for me and tell me if there are any duplicate rows, ragged rows, what delimiter it uses, and the data types of each column?

## When to prefer this

Choose 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.

## Known failure modes

- Malformed or empty CSV input returns an error or unexpected structure
- Very large CSV files may time out or hit payload limits
- CSV with no header row may cause incorrect column profiling
- Binary or non-UTF-8 encoded files may produce garbled results
- Network or payment failure returns a 402 or connection error

## How this service works

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.

## Output

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.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input",
  "output"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method",
    "queryParams"
   ],
   "properties": {
    "type": {
     "const": "http"
    },
    "method": {
     "enum": [
      "GET"
     ]
    },
    "queryParams": {
     "type": "object",
     "properties": {}
    }
   },
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "required": [
    "type",
    "example"
   ],
   "properties": {
    "type": {
     "const": "json"
    },
    "example": {
     "type": "object",
     "required": [
      "delimiter"
     ],
     "properties": {
      "delimiter": {
       "type": "string"
      }
     }
    }
   }
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "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."
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/coco-csv-lint-f23686d3/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from cocoeatsai.com](https://www.zero.xyz/host/cocoeatsai.com/llms.txt)