About this tool
Audit logs, dataset records, bulk API payloads, and search imports without allowing one malformed line to hide the evidence for the rest of the file.
JSON Lines Validator is useful when logs, NDJSON exports, AI dataset records, or indexing payloads need line-by-line validation instead of normal JSON array formatting. It helps you find the exact row that breaks a pipeline without wrapping the whole file manually.
- Uses Microsoft jsonc-parser 3.3.1 in strict mode for each physical record and reports line, column, duplicate-key JSON Pointer, unsafe integer, root type, and depth evidence.
- Controls whether blank lines are ignored or rejected and whether every record must be an object, while keeping invalid datasets available as downloadable JSON validation reports.
- Creates clean JSONL with LF or CRLF and optional final newline, or a formatted JSON array, only when every record passes the selected policy.
How to use JSONL Validator
Paste the JSONL or NDJSON content, review valid and invalid line counts, and fix any reported row before copying clean JSONL or switching to JSON array output. If the data will be imported, keep one complete JSON value per non-empty line and avoid comments or trailing commas.
When this tool is useful
- Validate newline-delimited log records before importing them into analytics or search tools.
- Check JSONL training or evaluation data before a batch job rejects the file.
- Convert valid NDJSON records into a formatted JSON array for tools that do not accept JSON Lines.
Practical tips
- Keep exactly one complete JSON value on each non-empty line. JSONL does not use commas between records.
- Treat comments, trailing commas, and partial lines as invalid even if a lenient editor accepts them.
- Use the original line numbers when fixing export files so the corrected row matches the source.
Examples you can test
Load an example, compare the result with the expected output, then replace it with your own input.
Validate log records
Example input
{"event":"signup","userId":42}
{"event":"login","userId":42}Expected output
2 valid JSONL records
Useful before importing logs into search, analytics, or data processing workflows.
Find a broken line
Example input
{"id":1}
{"id":2,}Expected output
Line 2 reports a JSON syntax error
Line-level errors are easier to fix than validating the entire file as one JSON document.
Validation checklist
- Keep exactly one complete JSON value on each non-empty line.
- Remove trailing commas, comments, and partial records before import.
- Convert to a JSON array only when the destination expects bracketed JSON.
- Review line numbers after filtering blank lines so fixes match the original file.