JSONL Validator for Agent Data

Validate and normalize JSON Lines used for agent traces, evaluations, batch requests, and datasets.

Runs locally in your browser. No account required.

API for direct AI agent use

Agents can call the same deterministic engine with a standard JSON POST request or import the OpenAPI document to discover every available tool.

POST https://toolfable.com/api/agent-tools/jsonl-validator

Open the OpenAPI 3.1 document ยท Open the agent tool manifest

Browser mode still runs locally. Only an Agent API call sends input and options to Cloudflare Edge; the service processes them in memory, does not write them to a ToolFable database, and limits request size.

Practical usage guide

What this tool does

JSONL Validator checks JSON Lines and NDJSON one physical line at a time. Every non-empty line must contain one complete JSON value, which allows malformed records to be reported with their exact line number. The format is common in agent traces, evaluation sets, batch APIs, logs, and data pipelines.

JSONL is not a pretty-printed JSON array. Records can each be valid while still using incompatible fields or value types. This tool checks line boundaries and JSON syntax, optionally requires objects, and can normalize valid records; dataset schemas, duplicates, role ordering, and domain correctness need separate review.

Quick start

Paste raw line-delimited records

Do not wrap records in square brackets or add commas between lines. Keep every complete object or value on one physical line.

Fix the earliest reported line first

A broken quote or brace can make later diagnostics confusing. Repair the first invalid line, then run validation again.

Review record consistency after syntax passes

Compare keys, value types, IDs, labels, and required fields across representative records before submitting a batch or dataset.

Common use cases

Prepare agent evaluation data

Find malformed cases in evaluation, retrieval, conversation, or training datasets before an upload or long-running job fails.

Inspect traces and event streams

Validate exported agent events, audit records, and log fragments while preserving the physical line numbers used by other diagnostics.

Check batch request files

Review NDJSON requests for asynchronous APIs, bulk indexing, or database imports before submitting the complete file.

Limitations and important notes

Pretty-printed records are not valid JSONL

An object spread across several lines can be valid JSON but is not one JSONL record. Minify each record before placing it on its own line.

Syntax does not guarantee consistent records

Valid lines may omit required fields or use incompatible types. Apply JSON Schema or a dataset-specific validator when uniform records are required.

Large inputs remain memory-bound

Browser mode is local and the API has a request-size limit. Extremely large files, long lines, or encoding problems should be handled with streaming tooling.

Examples

Agent evaluation cases

Validate two independent JSON objects as a JSONL dataset.

Frequently asked questions

Is JSONL the same as a JSON array?

No. JSONL contains one complete JSON value per physical line and does not wrap the records in square brackets.

Will the formatter merge records?

No. Each input line remains an independent output line; invalid line numbers are reported instead of silently joining data.

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