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Validating JSON data in shell scripts with jtd-validate

JSON Type Definition, aka RFC 8927, is an easy-to-learn, standardized way to define a schema for JSON data. You can use JSON Typedef to portably validate data across programming languages, create dummy data, generate code, and more.

jtd-validate is a CLI tool that can validate JSON input against a JSON Typedef schema. It lives on GitHub here.

This article will go over why jtd-validate may be useful to you, how to install it, and then go through an example of using jtd-validate in a shell script.

Why validating JSON from the shell is useful

First, to clarify terminology: a shell is the command language you write in when you’re using a terminal. Popular shells include bash and zsh. Shells are programming languages that specialized for running CLI tools and capturing and redirecting their input/output.

jtd-validate makes it easy to validate JSON from a shell script. This is useful in situations where you’re usually forced to write a shell script anyway, such as in many configuration files, such as a Dockerfile or Makefile, or in the configuration for your testing or CI/CD infrastructure (e.g. Jenkins or GitHub Actions).

If you want to validate JSON data from within a program written in a “traditional” (non-Shell) programming language, using jtd-validate is not recommended. Instead, use an implementation for the language you’re working in.

Installing jtd-validate

If you’re on macOS, the easiest way to install jtd-validate is via Homebrew:

brew install jsontypedef/jsontypedef/jtd-validate

For all other platforms, you can install a prebuilt binary from the latest release of jtd-validate. Supported platforms are:

  • Windows (
  • macOS (
  • Linux (

Using jtd-validate

You can always run jtd-validate --help to get details, but at a high level here’s how you usually use jtd-validate:

  1. First, you need a schema to validate against.

  2. Then, you need data to validate. This can be a single JSON message, or it can be a sequence of JSON messages, such as a file or stream of data with one JSON message per line.

  3. Then, you invoke jtd-validate on your schema and input.

For example, let’s say you have this schema in user.jtd.json:

  "properties": {
    "username": {
      "type": "string"
    "bio": {
      "type": "string"

And you have this message in input.json:

{ "username": "asdf", "bio": 5 }

Then you would run:

jtd-validate user.jtd.json input.json

Which would output:

{ "instancePath": "/bio", "schemaPath": "/properties/bio/type" }

If we “fixed” input.json to be compliant with the schema, such as by changing it to:

{ "username": "asdf", "bio": "foobar" }

Then jtd-validate would not output anything, indicating the input is valid.

When jtd-validate detects validation errors in the input, it will exit with a non-zero status code. This means you can use jtd-validate in a shell if statement:

if jtd-validate -q <(echo "$schema") <(echo "$input"); then
  echo "your input is good"
  echo "your input is not good"

Or as way to abort a script if the output is not what you expect:

# This technique only works if you `set -x` in your shell script. `set -x` makes
# it so that sh/bash/zsh will immediately exit your script if any command exits
# with non-zero status code.
set -x

# As an example, we'll just use `echo` as our "script" whose output we want to
# make sure is valid.
script_output=$(echo '{"username": "adsf", "bio": 3}')

# If "$script_output" isn't valid against the schema, jtd-validate will exit
# unsuccessfully, immediately halting this shell script.
echo "$script_output" | jtd-validate path/to/my/schema.jtd.json