# CSV type profiler

- Human page: https://happytails.ai/en/data-tools/csv-type-profiler/
- Markdown: https://happytails.ai/en/data-tools/csv-type-profiler.md
- Structured JSON: https://happytails.ai/agents/en/data-tools/csv-type-profiler/index.json
- Visibility: public

## Tool capabilities

| Property | Value |
| --- | --- |
| Tool ID | `csv-type-profiler` |
| Category | data-tools |
| Implementation | Registered implementation. Registration alone is not a production-quality guarantee. |
| Browser execution | Automatic updates after valid input or file selection. |
| Browser processing | Browser; see tool notes for network behavior. |
| HTTP API | Not callable through HTTP. |
| Browser-agent interface | run_current_tool |

### Implementation notes

Runs locally on your device. CSV requires unique nonempty headers. Up to 1,000,000 characters, 10,000 data records and 100,000 cells across inputs, with 100 columns. Quoted multiline cells are supported. Each JSON settings field is limited to 100,000 characters. Output files are bounded to 4,000,000 characters. Diagnostic reports contain at most 500 findings and disclose the omitted count. Infer the dominant nonempty type per column and locate exceptions. Ties are mixed; leading-zero codes remain text. Dates use YYYY-MM-DD and booleans use lowercase true/false. Inference describes this sample, not every possible future value.

### Inputs and settings

Text input: CSV data.

Example or placeholder shown in the interface (not a validated fixture):

```text
code,amount
001,10
002,11
003,oops
```

Paste CSV data with unique column headers. Quoted multiline cells are supported. Results update as you type. Up to 1,000,000 characters.

| Setting | Meaning | Control type | Default | Constraints |
| --- | --- | --- | --- | --- |
| `separator` | Input CSV separator | select | "," | Allowed: ,, ;, 	 |

### Browser-agent workflow

1. Open the human page in a browser that supports WebMCP.
2. Discover the interface exposed by that page; use its actual schema.
3. Select files on the page first when the tool requires files.
4. Call `run_current_tool` with valid input and settings.
5. Inspect the returned result or error and the displayed output. Retrieve files from the displayed download links.

Calls do not automatically copy or download results. Browser permissions still apply. Interface availability alone is not proof of successful execution.

### Planning specification

Leading-zero codes stay text. The most frequent nonempty observed type wins; tied types are mixed. The result describes this sample, not a permanent database schema. Up to 1,000,000 characters, 10,000 data records, 100 columns and 100,000 cells across the sources. Files for multi-source tools are limited to 4,000,000 bytes total. Reports retain at most 500 diagnostic findings and state any omitted count. CSV and JSON outputs are limited to 4,000,000 characters.

This describes intended requirements. Use the implementation notes, interface schema and observed output to determine current support.

### Complete machine-readable capability record

```json
{
  "id": "csv-type-profiler",
  "category": "data-tools",
  "built": true,
  "requirements": "Leading-zero codes stay text. The most frequent nonempty observed type wins; tied types are mixed. The result describes this sample, not a permanent database schema. Up to 1,000,000 characters, 10,000 data records, 100 columns and 100,000 cells across the sources. Files for multi-source tools are limited to 4,000,000 bytes total. Reports retain at most 500 diagnostic findings and state any omitted count. CSV and JSON outputs are limited to 4,000,000 characters.",
  "implementation": {
    "fields": [
      {
        "key": "separator",
        "label": "Input CSV separator",
        "value": ",",
        "type": "select",
        "values": [
          ",",
          ";",
          "\t"
        ]
      }
    ],
    "live": true,
    "presentation": "metrics",
    "note": "Runs locally on your device. CSV requires unique nonempty headers. Up to 1,000,000 characters, 10,000 data records and 100,000 cells across inputs, with 100 columns. Quoted multiline cells are supported. Each JSON settings field is limited to 100,000 characters. Output files are bounded to 4,000,000 characters. Diagnostic reports contain at most 500 findings and disclose the omitted count. Infer the dominant nonempty type per column and locate exceptions. Ties are mixed; leading-zero codes remain text. Dates use YYYY-MM-DD and booleans use lowercase true/false. Inference describes this sample, not every possible future value.",
    "experience": {
      "automatic": true,
      "single": false,
      "inputMaxLength": 1000000,
      "inputMode": "text",
      "label": "CSV data",
      "placeholder": "code,amount\n001,10\n002,11\n003,oops",
      "help": "Paste CSV data with unique column headers. Quoted multiline cells are supported. Results update as you type. Up to 1,000,000 characters.",
      "action": null
    },
    "mode": "automatic",
    "interactive": false
  },
  "execution": "Browser interface",
  "api": null,
  "browser_agent": {
    "supported": true,
    "name": "run_current_tool",
    "discovery": "WebMCP on the human page in a supporting browser",
    "verification": "See audit/API-AUDIT.md; availability is not verification"
  }
}
```

## Page guide

Find the dominant type of each CSV column and locate the records that do not fit.

How can we improve this tool?

Report a problem or share an idea.

Please leave out private information. Your message and the tool name go to our team via PostHog.

### How to use CSV type profiler

1. Paste a CSV with unique column names.
2. Review inferred types, empty counts and the record numbers of exceptions.
3. Download the JSON report for your cleanup workflow.

## Useful next steps

- [Data dictionary generator](https://happytails.ai/en/data-tools/data-dictionary-generator/) ([Markdown](https://happytails.ai/en/data-tools/data-dictionary-generator.md))

- [CSV schema validator](https://happytails.ai/en/data-tools/csv-schema-validator/) ([Markdown](https://happytails.ai/en/data-tools/csv-schema-validator.md))

## Prepare the source

Paste a CSV with unique column names.

### Choose the matching rules

Review inferred types, empty counts and the record numbers of exceptions.

### Review and keep the result

Download the JSON report for your cleanup workflow. Leading-zero codes stay text. The most frequent nonempty observed type wins; tied types are mixed. The result describes this sample, not a permanent database schema.