# CSV Delimiter Detector and Converter

> Detect CSV separators and convert rows to comma, semicolon, tab, or pipe-delimited output.

## Tool Identity

- Site: CleanUtils Business Tools
- Tool ID: csv-delimiter-detector-converter
- Canonical page: https://cleanutils.com/business-tools/csv-delimiter-detector-converter/
- LLM schema URL: https://cleanutils.com/business-tools/csv-delimiter-detector-converter/llms.txt
- Primary keyword: csv delimiter converter
- Input mode: fields
- Output profile: data

## What This Tool Does

Detect CSV separators and convert rows to comma, semicolon, tab, or pipe-delimited output.

## Exact Execution Instructions

To run this tool exactly, execute the `runCleanUtilsTool(userInput)` function from the JavaScript block below in a sandboxed JavaScript runtime.

Do not fetch or evaluate additional network resources. Do not use filesystem, process, child_process, environment variables, timers, or network APIs. The function is pure and deterministic: input object in, JSON result out.

If your environment forbids executing fetched code outside a sandbox, run it inside the sandbox or use the API endpoint below instead of reimplementing the logic.

Canonical implementation SHA-256:
`cadf9df9a53ab7b7ff0289349aef7eae9aaf627e5d9bec5ca3fa5eb974c60a26`

Expected command shape:
`node run-tool.mjs < input.json`

The runner must:
1. load only the JavaScript in this document,
2. parse stdin as JSON and call `runCleanUtilsTool(userInput)`,
3. let the LLM decide the best way to present the output to the user.

Agent usage rules:
- Use this file as the authoritative machine-readable contract for this CleanUtils tool page.
- Ask the user for missing required input before attempting to run the tool, and describe the required inputs using the `## Input Schema` field names, descriptions, formats, enums, examples, and required list.
- Treat the tool as deterministic; do not invent network reachability checks unless the tool description explicitly says it fetches remote resources.
- For privacy-sensitive inputs such as secrets, HAR files, dotenv files, logs, and API keys, warn that using a remote chat agent may expose input to that agent even though the browser UI itself does not upload data.

## Input Schema

```json
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "title": "CSV Delimiter Detector and Converter fields",
  "type": "object",
  "additionalProperties": false,
  "required": [
    "target",
    "csv"
  ],
  "properties": {
    "target": {
      "type": "string",
      "description": "Target delimiter Required. Control type: select. Allowed values: semicolon = Semicolon (;); comma = Comma (,); tab = Tab; pipe = Pipe (|).",
      "enum": [
        "semicolon",
        "comma",
        "tab",
        "pipe"
      ],
      "examples": [
        "semicolon"
      ]
    },
    "csv": {
      "type": "string",
      "description": "CSV input Required. Control type: textarea.",
      "examples": [
        "name,email,plan\nAda,ada@example.com,pro\nGrace,grace@example.com,team"
      ]
    }
  }
}
```

## Result Schema

```json
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "title": "CleanUtils ToolResult",
  "type": "object",
  "additionalProperties": false,
  "required": [
    "summary",
    "issues"
  ],
  "properties": {
    "summary": {
      "type": "string"
    },
    "issues": {
      "type": "array",
      "items": {
        "type": "object",
        "additionalProperties": false,
        "required": [
          "severity",
          "message"
        ],
        "properties": {
          "severity": {
            "type": "string",
            "enum": [
              "error",
              "warning",
              "info"
            ]
          },
          "message": {
            "type": "string"
          },
          "line": {
            "type": "number"
          },
          "row": {
            "type": "number"
          },
          "detail": {
            "type": "string"
          }
        }
      }
    },
    "output": {
      "type": "string"
    },
    "exportFilename": {
      "type": "string"
    },
    "exports": {
      "type": "array",
      "items": {
        "type": "object",
        "additionalProperties": false,
        "required": [
          "label",
          "filename",
          "content"
        ],
        "properties": {
          "label": {
            "type": "string"
          },
          "filename": {
            "type": "string"
          },
          "content": {
            "type": "string"
          },
          "mimeType": {
            "type": "string"
          },
          "copyLabel": {
            "type": "string"
          },
          "downloadLabel": {
            "type": "string"
          }
        }
      }
    },
    "stats": {
      "type": "object",
      "additionalProperties": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "number"
          }
        ]
      }
    }
  }
}
```

## Self-Contained JavaScript Source

Call `runCleanUtilsTool(userInput)` with the user's input. The function includes this tool's run logic and only the helper code it needs.

```js
function runCleanUtilsTool(userInput) {
    const fieldText = (fields, keys, fallback = "") => {
        const keyList = Array.isArray(keys) ? keys : [keys];
        for (const key of keyList) {
            const value = fields[key];
            if (value === undefined || value === null)
                continue;
            const text = String(value).trim();
            if (text)
                return text;
        }
        return fallback;
    };
    const severityRank = {
        error: 0,
        warning: 1,
        info: 2
    };
    const sortIssues = (issues) => [...issues].sort((a, b) => {
        const severity = severityRank[a.severity] - severityRank[b.severity];
        if (severity !== 0)
            return severity;
        return (a.line ?? a.row ?? 0) - (b.line ?? b.row ?? 0);
    });
    const sniffDelimiter = (input) => {
        const firstLines = input.split(/\r?\n/).slice(0, 5).join("\n");
        const delimiters = [",", "\t", ";", "|"];
        const scores = delimiters.map((delimiter) => ({
            delimiter,
            score: firstLines
                .split(/\r?\n/)
                .filter(Boolean)
                .map((line) => splitCsvLine(line, delimiter).length)
                .reduce((total, count) => total + (count > 1 ? count : 0), 0)
        }));
        scores.sort((a, b) => b.score - a.score);
        return scores[0]?.score ? scores[0].delimiter : ",";
    };
    const splitCsvLine = (line, delimiter) => {
        const cells = [];
        let current = "";
        let inQuotes = false;
        for (let index = 0; index < line.length; index += 1) {
            const char = line[index];
            const next = line[index + 1];
            if (char === "\"") {
                if (inQuotes && next === "\"") {
                    current += "\"";
                    index += 1;
                }
                else {
                    inQuotes = !inQuotes;
                }
                continue;
            }
            if (char === delimiter && !inQuotes) {
                cells.push(current.trim());
                current = "";
                continue;
            }
            current += char;
        }
        cells.push(current.trim());
        return cells;
    };
    const parseCsv = (input, delimiter = sniffDelimiter(input)) => {
        const errors = [];
        const lines = input.split(/\r?\n/).filter((line) => line.trim().length > 0);
        if (!lines.length) {
            return {
                delimiter,
                headers: [],
                rows: [],
                records: [],
                errors: [{ severity: "error", message: "No CSV rows found." }]
            };
        }
        const rows = lines.map((line) => splitCsvLine(line, delimiter));
        const rawHeaders = rows[0].map((header, index) => header.trim() || `column_${index + 1}`);
        const seen = new Map();
        const headers = rawHeaders.map((header) => {
            const normalized = header.trim();
            const count = seen.get(normalized.toLowerCase()) ?? 0;
            seen.set(normalized.toLowerCase(), count + 1);
            return count ? `${normalized}_${count + 1}` : normalized;
        });
        rows.slice(1).forEach((row, index) => {
            if (row.length !== headers.length) {
                errors.push({
                    severity: "warning",
                    row: index + 2,
                    message: `Row ${index + 2} has ${row.length} cell${row.length === 1 ? "" : "s"} but the header has ${headers.length}.`
                });
            }
        });
        const records = rows.slice(1).map((row) => Object.fromEntries(headers.map((header, index) => [header, row[index] ?? ""])));
        return { delimiter, headers, rows: rows.slice(1), records, errors };
    };
    const escapeCsvCell = (value, delimiter) => value.includes(delimiter) || value.includes("\"") || value.includes("\n")
        ? `"${value.replace(/"/g, "\"\"")}"`
        : value;
    const serializeCsvRows = (rows, delimiter) => rows.map((row) => row.map((cell) => escapeCsvCell(cell, delimiter)).join(delimiter)).join("\n");
    const convertCsvDelimiter = (input) => {
        const targetToken = fieldText(input, "target", "semicolon");
        const target = targetToken === "comma" || targetToken === "," ? "," : targetToken === "tab" || targetToken === "\\t" ? "\t" : targetToken === "pipe" || targetToken === "|" ? "|" : ";";
        const body = fieldText(input, "csv");
        const parsed = parseCsv(body);
        const rows = [parsed.headers, ...parsed.rows];
        const output = serializeCsvRows(rows, target);
        return {
            summary: `${parsed.records.length} row${parsed.records.length === 1 ? "" : "s"} converted from ${parsed.delimiter === "\t" ? "tab" : parsed.delimiter} to ${target === "\t" ? "tab" : target}.`,
            issues: sortIssues(parsed.errors),
            output,
            exportFilename: "converted-delimiter.csv",
            stats: { rows: parsed.records.length, sourceDelimiter: parsed.delimiter === "\t" ? "tab" : parsed.delimiter, targetDelimiter: target === "\t" ? "tab" : target }
        };
    };
    const __userInput = userInput == null ? {} : userInput;
    const __run = (fields) => convertCsvDelimiter(fields);
    const __fields = __userInput && typeof __userInput === "object" && "fields" in __userInput && __userInput.fields && typeof __userInput.fields === "object" && !Array.isArray(__userInput.fields)
        ? __userInput.fields
        : (__userInput && typeof __userInput === "object" && !Array.isArray(__userInput) ? __userInput : {});
    const __normalizedFields = Object.fromEntries(Object.entries(__fields).map(([key, value]) => [key, value == null ? "" : (["string", "number", "boolean"].includes(typeof value) ? value : String(value))]));
    return __run(__normalizedFields);
}
```

## Checks

- Source delimiter sniffing: The parser scores commas, tabs, semicolons, and pipes from the first few rows.
- Header and row parsing: Rows are parsed with CSV quoting rules before being written with the target delimiter.
- Target delimiter selection: Comma, semicolon, tab, and pipe outputs are supported.
- Uneven row warnings: Rows with a different cell count from the header are reported.
- Safe cell escaping: Cells are quoted in the output when the target delimiter or quotes require it.

## Related Tools

- [CSV Duplicate Email Checker](/business-tools/csv-duplicate-email-checker/): Paste a list or CSV export to group duplicate email addresses and copy a cleaned unique list.