Data Validator
Paste CSV or JSON rows, write one rule per line (required, unique, type, min/max, length, regex, enum) and get every violation listed with its record, field, value and reason. Runs in your browser; nothing is uploaded.
About this tool
Data Validator checks pasted CSV or JSON rows against the field rules you write. It is useful before imports, migrations, mail merges, API uploads, or any other step where bad rows are expensive to discover later.
Write one rule per line:
email:required
email:type=email
age:type=int
age:min=18
age:max=120
plan:enum=free|pro|team
id:unique
The report lists every violation with its record, physical line, field, offending value, broken rule, and a short explanation. The tool is report-only: it never modifies your data and it runs locally in your browser.
Worked example
Input CSV:
email,age,plan
[email protected],34,pro
bad-email,200,gold
Rules:
email:required
email:type=email
age:type=int
age:min=0
age:max=120
plan:enum=free|pro|team
Output highlights three violations on record 2: the invalid email, age above
120, and plan outside the allowed enum.
Options and limits
- Read data as —
auto,csv, orjson. Auto treats values starting with[or{as JSON and everything else as CSV. - CSV delimiter — auto-detects comma, tab, semicolon, and pipe.
- CSV has a header row — on by default. If you turn it off, refer to columns
by 1-based index (
1:required,2:type=int). - Max violations to list — caps how many details are shown while still
reporting the total count. The accepted range is
1–1000. - JSON input can be an array of objects, a single object, or JSON Lines / NDJSON.
FAQ
Which validation rules are supported?
Use required, unique, type=int|float|bool|date|email|url, min / max for
numeric ranges, minlen / maxlen for character counts, regex=..., and
enum=a|b|c. You can also write bare type shorthand such as age:int.
Do optional blank values fail type, range, regex, or enum rules?
No. Every rule except required is skipped for a blank or missing value. Combine
rules such as email:required and email:type=email when a field must be present
and must match a format.
Can I validate JSON as well as CSV?
Yes. JSON can be an array of objects, one object, or JSON Lines. Field names come from object keys. CSV can use header names, or 1-based column numbers when the header option is off.
Are regex rules anchored automatically?
No. Regex rules use the pattern you provide. Add ^ and $ yourself when the
whole value must match, for example email:regex=^[^@\\s]+@[^@\\s]+\\.[^@\\s]+$.
Developer & Automation Access
Run it from the terminal
Same engine as this page, headless — via the gizza CLI:
gizza tool data-validator "email,age,plan
[email protected],34,pro
bad-email,200,gold" 'rules=email:required
email:type=email
age:type=int
age:max=120
plan:enum=free|pro|team'New to the CLI? Get gizza →
Open it by URL
Pre-fill and auto-run this tool with query parameters — the names match the API/CLI:
https://gizza.ai/tools/data-validator/?data=email%2Cage%2Cplan%0Aa%40b.com%2C34%2Cpro%0Abad-email%2C200%2Cgold&rules=email%3Arequired%0Aemail%3Atype%3Demail%0Aage%3Atype%3Dint%0Aage%3Amax%3D120%0Aplan%3Aenum%3Dfree%7Cpro%7Cteam&input_format=auto&header=true&delimiter=auto&max_issues=50&format=textMachine-readable descriptor: tool.json — title + parameters JSON Schema for agents.