Developer and data tools to inspect, convert, and validate

Work with API responses, configuration files, encoded values, and tabular data without pasting them into a remote service. This collection brings the site's data, validation, and encoding utilities into one practical developer workspace.

Choose the exact operation rather than a generic editor: compare JSON structures, validate XML or YAML, decode a JWT locally, escape a payload, or move between CSV and structured formats while keeping the source on your device.

Start by deciding whether you need validation, formatting or a change of representation. A JSON formatter can make nested values easier to read, but it does not establish that fields satisfy an API schema. A validator can catch malformed structure without proving that a customer ID or date is valid for the destination. Use the tool that answers the actual failure you are investigating.

When converting CSV into JSON, check headers, delimiters and quoted line breaks before treating each row as a record. A spreadsheet can silently change leading-zero identifiers or long numbers; preserving those fields as text may matter. When converting JSON or YAML, compare values and types after the round trip rather than expecting comments, ordering or original whitespace to survive. A valid output can still be unsuitable for a particular application schema.

Encoded strings are not necessarily trustworthy. Base64 says how bytes are represented, not who produced them. A decoded JWT payload can describe claims without establishing that its signature is valid. Do not paste live credentials into a troubleshooting example. Use a harmless synthetic token or payload where possible, and verify any real signature or permission decision in the system responsible for it.

For sensitive configuration, review both the input and the saved or copied result before sharing it. Formatting a secret does not remove it. Keep a known-good source so that an unexpected converter result can be checked against the original. If a parser reports an error, reduce a non-sensitive sample to the smallest case that still reproduces it; that often reveals a stray quote, delimiter or indentation problem faster than inspecting a whole file.