JSON validator: validate & format JSON locally (fast workflow)

Step 1: validate syntax first

Start with syntax validation before you think about “structure”. A validator will tell you if the text is strict JSON (double quotes, no comments, no trailing commas). If syntax fails, nothing else matters.

Step 2: use position → line/column

Many errors include a character position (byte index). Convert that into a line/column hint to pinpoint the exact place where parsing breaks. Fix one issue at a time, re-validate, repeat.

Step 3: common quick fixes

• Single quotes → replace with double quotes.
• Trailing commas → remove the last comma in objects/arrays.
• Extra text → strip log prefixes/suffixes around the JSON.

Step 4: sanity-check the top-level shape

Converters often expect a specific shape. JSON → CSV usually needs an array of objects. If you have a single object, wrap it in an array or transform it first.

Practical checklist (fast)

If you’re stuck, use this quick checklist to narrow the problem before you try “random fixes”. Start by validating the input format (syntax first), then confirm shape expectations (array vs object, headers vs rows). Convert a small sample, inspect the output, and only then export the full result.

• Validate: confirm the input is strict JSON/XML/CSV (no stray characters).
• Confirm shape: arrays vs objects; headers vs row lengths; repeated tags vs arrays.
• Test a sample: first 20–50 rows/items are enough to detect parsing issues.
• Export: copy/download the output and re-check it in the consumer (script/spreadsheet/API).

This workflow is privacy-first by design: All processing happens locally in your browser. Files are never uploaded.

FAQ

Is formatting the same as validating? No. Pretty printing helps reading, but you still need strict syntax.

Can I validate confidential JSON safely? Yes—use no-upload validators that run locally.

Trust note: All processing happens locally in your browser. Files are never uploaded.