JSON Input
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JSON Output
Enter valid JSON to see the formatted output
JSON Viewer & Formatter
Validate, format, and explore JSON data instantly
Enter valid JSON to see the formatted output
Validate, format, and explore JSON data instantly
In the era of AI and Large Language Models (LLMs), JSON has become the critical format for structured outputs from ChatGPT, Claude, Gemini, and other AI systems. Our advanced JSON viewer and formatter is specifically designed for developers working with AI-generated JSON, prompt engineering, and structured output validation. Whether you're debugging ChatGPT's JSON mode responses, validating Claude's tool outputs, or formatting structured data from any LLM API, our tool ensures your AI integrations work flawlessly.
With OpenAI achieving 100% reliability in JSON schema compliance and Anthropic's Claude offering robust structured outputs through tool calling, JSON has become the lingua franca of AI communication. Major developments in 2025 include:
response_format: { type: 'json_object' } in OpenAI API callsValidate and debug function arguments and responses from ChatGPT, Claude, and other AI assistants using tool/function calling features.
Extract and validate structured information from unstructured text using AI, ensuring the output matches your expected schema.
Debug JSON data flowing between multiple AI services, RAG systems, and vector databases in complex AI applications.
Instantly validate AI-generated JSON against your schemas to ensure prompt engineering produces consistent results.
You must respond with valid JSON only. No explanation or markdown.
Follow this exact schema:
{
"result": "your analysis here",
"confidence": 0.95,
"reasoning": "explanation of your logic",
"data": []
}Pro tip: Including a "reasoning" field improves accuracy by 35% according to 2025 studies, even if you don't use it in production.
Catch syntax errors immediately with real-time validation and helpful error messages that pinpoint exactly where issues occur.
Switch between tree view for navigation, raw view for editing, and table view for data analysis - all optimized for different workflows.
Automatically format messy JSON with proper indentation, or minify it for production use with a single click.
Click any value to get its exact JSON path - perfect for documentation or accessing nested data programmatically.
Quickly find specific keys or values within large JSON documents using our advanced search functionality with highlighting.
Download formatted JSON files, copy to clipboard with one click, or export selected paths for use in your code.
Validate your JSON against schemas to ensure data integrity and catch structural issues early in development.
Efficiently handle JSON files up to several megabytes with optimized rendering and virtual scrolling.
1. Consistent Naming: Use camelCase for keys in JavaScript environments, snake_case for Python/Ruby, and follow your team's conventions consistently throughout your JSON structures.
2. Avoid Deep Nesting: Deeply nested JSON is hard to read and process. Consider flattening structures or breaking them into separate objects when nesting exceeds 3-4 levels.
3. Use Meaningful Keys: Choose descriptive key names that clearly indicate the data they contain. Avoid abbreviations that might confuse other developers.
4. Validate Early: Always validate JSON data at system boundaries - when receiving from APIs, reading from files, or accepting user input.
5. Handle Null Values: Be explicit about null values and empty arrays/objects. They have different meanings and should be handled appropriately in your application logic.
| Format | Best For | Pros | Cons |
|---|---|---|---|
| JSON | Web APIs, JavaScript apps | Human-readable, widespread support | No comments, limited data types |
| XML | Document markup, SOAP APIs | Schema validation, namespaces | Verbose, complex parsing |
| YAML | Configuration files, CI/CD | Very readable, supports comments | Indentation-sensitive, security concerns |
| CSV | Tabular data, spreadsheets | Simple, Excel-compatible | No nested structures, type ambiguity |
| Protocol Buffers | High-performance APIs | Compact, fast, strongly typed | Binary format, requires schema |
Usually caused by missing quotes around strings, trailing commas, or using single quotes instead of double quotes.
Special characters in strings must be properly escaped. Use \\ for backslash, \" for quotes, \n for newlines.
Check for missing closing brackets or braces. Our viewer highlights matching pairs to help identify mismatches.
While technically valid JSON, duplicate keys can cause unexpected behavior. The last value typically wins.
Solution: Add "response_format" parameter or explicitly state "Return only valid JSON, no markdown formatting" in your prompt.
Solution: Use tool/function calling instead of direct prompting, or add "Output only the JSON object, no additional text" to your prompt.
Solution: Use OpenAI's strict mode or provide the exact JSON schema in your system prompt with examples.
Solution: Increase max_tokens parameter or break complex requests into smaller chunks.
When working with AI models, providing a clear JSON schema dramatically improves output reliability. Here's an example schema for a common AI task - sentiment analysis with structured output:
{
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"required": ["sentiment", "confidence", "aspects"],
"properties": {
"sentiment": {
"type": "string",
"enum": ["positive", "negative", "neutral", "mixed"]
},
"confidence": {
"type": "number",
"minimum": 0,
"maximum": 1
},
"aspects": {
"type": "array",
"items": {
"type": "object",
"required": ["aspect", "sentiment", "keywords"],
"properties": {
"aspect": {"type": "string"},
"sentiment": {"type": "string"},
"keywords": {"type": "array", "items": {"type": "string"}}
}
}
},
"reasoning": {
"type": "string",
"description": "AI's explanation for the analysis"
}
}
}Our JSON viewer efficiently handles files up to 10MB. For larger files, consider using our streaming mode or breaking the data into smaller chunks.
Yes! Switch to raw view mode for direct editing with syntax highlighting and real-time validation. The tree view also supports inline editing of values.
Use our schema validation feature to check your JSON against JSON Schema drafts 4, 6, 7, or 2019-09. Simply paste your schema and JSON to validate.
Absolutely. All JSON processing happens entirely in your browser. No data is sent to our servers, ensuring complete privacy and security.
Yes! Use Ctrl/Cmd+F to search, Ctrl/Cmd+C to copy selected paths, and Ctrl/Cmd+V to paste JSON. Press ? to see all available shortcuts.
Ready to streamline your JSON workflow? Our viewer is free, requires no registration, and works entirely in your browser. Paste your JSON above to get started, or load one of our sample files to explore the features.