🎯 Why You Need Professional GraphQL Formatting

GraphQL queries quickly become complex with nested fields, multiple fragments, and variable definitions. Without proper formatting, you face:

• Syntax errors that break production: Missing brackets, malformed fragments, and invalid field selections can crash your application
• Performance bottlenecks: Overly complex queries with deep nesting slow down your API and frustrate users
• Schema mismatches: Querying non-existent fields or using wrong types causes runtime failures
• Maintenance nightmares: Unformatted queries are impossible to read, debug, or optimize
• Team collaboration issues: Inconsistent formatting leads to code review delays and merge conflicts

Our GraphQL formatter solves these problems by providing instant validation, automatic beautification with customizable styles, comprehensive schema validation, real-time complexity analysis, and intelligent fragment management. Whether you're building new APIs, debugging production issues, or optimizing query performance, this tool ensures your GraphQL operations are correct, efficient, and maintainable.

📋 Step-by-Step Usage Guide

Step 1: Input Your GraphQL Code

You have multiple ways to load GraphQL queries into the formatter:

• Direct paste: Copy and paste your queries, mutations, or subscriptions directly into the left editor
• File upload: Click Upload Query to load .graphql, .gql, or .txt files (up to 2MB)
• Remote URL: Click Load from URL to fetch GraphQL from any public endpoint

The editor provides syntax highlighting with color-coded keywords, fields, types, and directives for better readability.

Step 2: Load Your Schema (Critical for Validation)

Loading your GraphQL schema unlocks powerful validation features:

• Click Load Schema and select your schema file in SDL (Schema Definition Language) format
• The schema enables field existence checking, type validation, argument verification, and directive validation
• Once loaded, use Validate Against Schema to catch errors before deployment

Pro tip: Always validate against your production schema before deploying queries to prevent runtime errors.

Step 3: Validate Syntax in Real-Time

The formatter validates your GraphQL syntax automatically as you type:

• Live feedback: Instant error messages with line and column numbers
• Operation detection: Automatically identifies queries, mutations, subscriptions, and fragments
• Statistics display: Shows field count, nesting depth, and operation type
• Manual validation: Click Validate Query for detailed syntax analysis

Step 4: Beautify with Custom Formatting

Transform messy, single-line queries into readable, properly indented code:

1. Select your preferred indentation: 2 spaces (default), 4 spaces, or tabs
2. Click Beautify to apply consistent formatting
3. The formatter aligns fields, organizes fragments, and structures nested selections
4. Use Sort Fields to alphabetically organize field selections for consistency

For production: Use Minify to create compact, single-line queries that reduce payload size and bandwidth usage.

Step 5: Analyze Query Complexity

Prevent performance issues before they impact users:

• Click Analyze Complexity to calculate your query's computational cost
• The analyzer considers field count, nesting depth, and overall structure
• Complexity scores above 50 trigger warnings; scores above 100 indicate high-risk queries
• Use these insights to optimize queries, implement cost limits, and maintain API performance

Step 6: Export and Share Results

Multiple export options for different use cases:

• Download saves formatted queries as .graphql files for version control
• Export PDF creates documentation-ready files with professional formatting
• Copy buttons instantly copy input or output to your clipboard
• All exports preserve formatting, comments, and structure

🚀 Advanced Features Explained

Schema Validation Engine

The most powerful feature for preventing errors: After loading your schema, the validator performs comprehensive checks including field existence verification (ensures all queried fields exist in your schema), type matching (validates that field types match expected return types), argument validation (checks argument names, types, and required fields), enum value verification (ensures enum values are valid), custom scalar checking (validates custom scalar types), and directive validation (verifies directive usage and arguments).

Real-world example: If your schema defines user(id: ID!) but your query uses user(userId: String), the validator immediately flags this mismatch, saving hours of debugging.

Fragment Management System

Fragments reduce code duplication and improve query maintainability:

• Automatic detection: The tool identifies all fragment definitions in your queries
• Usage validation: Checks that fragment spreads reference existing fragments
• Type compatibility: Ensures fragments are used on appropriate types
• Extraction tool: Click Extract Fragments to pull all fragments into a separate view
• Interactive browser: Switch to Fragments view to see all fragments with their type conditions

Example: Define fragment UserFields on User { id name email }, then reuse it across multiple queries with ...UserFields.

Variables Panel with JSON Editing

Variables separate query structure from data, improving security and reusability:

• Click Variables Panel to show the JSON editor
• Define variables matching your query's variable definitions
• Example: For query GetUser($id: ID!), provide { "id": "123" }
• The validator checks that variable types match your schema definitions
• Test queries with different variable values without rewriting the query

Operation Type Detection

The formatter automatically identifies and handles different GraphQL operations:

• Queries: Read operations for fetching data
• Mutations: Write operations for modifying data
• Subscriptions: Real-time operations for listening to updates
• Fragments: Reusable selection sets

Each operation type receives appropriate syntax highlighting, validation rules, and formatting conventions.

Schema Explorer Interface

Navigate and understand your entire GraphQL API structure:

• Click Schema Explorer after loading a schema
• Browse all types: objects, interfaces, unions, enums, and scalars
• View available fields with their return types and descriptions
• See required and optional arguments for each field
• Understand type relationships and API capabilities

Perfect for: API discovery, documentation generation, query planning, and team onboarding.

Conversion and Export Tools

• GraphQL → JSON: Convert operations to JSON AST format for programmatic analysis
• GraphQL → REST: Generate REST-equivalent endpoints to understand API mapping
• Introspection Query: Generate the standard GraphQL introspection query to fetch schema details

❓ Frequently Asked Questions

Q: What GraphQL syntax errors can this formatter detect and fix? A: The formatter detects every type of GraphQL syntax error including invalid field selections, malformed arguments, incorrect fragment usage and spreads, missing operation names and types, invalid directive placements, type mismatches and incompatibilities, missing required fields, incorrect bracket/brace matching, invalid variable definitions, enum value errors, and malformed string literals. Each error message provides the exact line number, column position, and a clear explanation of what's wrong. The beautify function automatically corrects indentation and formatting issues, though it cannot fix logical errors like querying non-existent fields (use schema validation for that). Example: If you write query { user { name } (missing closing brace), the validator pinpoints the exact location and suggests the fix. Q: How does schema validation work, and what specific checks does it perform? A: Schema validation is a comprehensive process that occurs after you load your GraphQL schema in SDL format. Here's what happens: First, the tool parses your schema to understand all types, fields, and their relationships. When you click "Validate Against Schema," it performs multiple layers of validation: (1) Field existence: Verifies every field in your query exists in the schema's type definitions. (2) Type matching: Ensures field return types match what the schema defines. (3) Argument validation: Checks that all arguments are defined in the schema, match expected types, and required arguments are provided. (4) Enum validation: Confirms enum values match schema definitions. (5) Interface/Union validation: Verifies correct fragment usage on interfaces and unions. (6) Directive validation: Ensures directives are used correctly with proper locations and arguments. (7) Variable type checking: Validates variable definitions match their usage in the query. This catches issues before runtime, saving debugging time and preventing production errors. The validator provides specific error messages for each violation, making fixes straightforward. Q: Can I use this tool for GraphQL subscriptions, and how does it handle real-time operations? A: Yes, absolutely! The formatter provides full support for GraphQL subscriptions alongside queries and mutations. Subscriptions are treated as first-class operations with all the same features: syntax validation ensures proper subscription structure and field selections, the beautifier formats subscription operations with correct indentation, schema validation verifies subscription fields exist in your schema, operation detection automatically identifies and labels subscriptions, complexity analysis calculates the cost of subscription operations, and fragment support works seamlessly in subscription operations. Example usage: Paste a subscription like subscription OnUserCreated { userCreated { id name email } }, validate it against your schema, beautify it with consistent formatting, and analyze its complexity just like any query or mutation. The tool recognizes subscription-specific patterns like single top-level fields and validates accordingly. While this formatter handles the query structure, remember that actual subscription execution requires WebSocket support in your GraphQL server, which is separate from query formatting. Q: How do I work with query variables, and what validation does the tool provide? A: Working with variables is essential for reusable, secure GraphQL queries. Here's the complete workflow: (1) Enable the variables panel: Click "Variables Panel" to show the JSON editor below the main query editor. (2) Define variables in your query: Use the syntax query GetUser($userId: ID!, $includeEmail: Boolean) { user(id: $userId) { name email @include(if: $includeEmail) } }. (3) Provide variable values: In the variables panel, enter JSON like { "userId": "abc123", "includeEmail": true }. (4) Validation: The tool validates that variable types in your JSON match the types declared in your query, required variables (marked with !) are provided, variable values match schema scalar types, variables are actually used in the query, and enum variables have valid values. (5) Testing: Change variable values in the JSON panel to test different scenarios without modifying the query. This separation of query structure from data prevents SQL-injection-style attacks, makes queries reusable across different contexts, enables better caching, and simplifies testing. The validator shows specific errors if variable types mismatch or required variables are missing. Q: What is the introspection query feature, and how can I use it? A: GraphQL introspection is a powerful feature that lets you query a GraphQL schema to discover its structure programmatically. When you click "Introspection Query" in our formatter, it generates the standard GraphQL introspection query that fetches complete schema information including all types (objects, interfaces, unions, enums, scalars), fields for each type with descriptions, arguments for each field, directives and their usage locations, and type relationships and implementations. Use cases: (1) API exploration: Run the introspection query against any GraphQL endpoint to understand its capabilities without documentation. (2) Documentation generation: Use introspection results to automatically generate API docs. (3) Developer tools: Build autocomplete, validation, or schema visualization tools. (4) Schema comparison: Compare introspection results across API versions to detect breaking changes. (5) Client code generation: Generate TypeScript types or other language bindings from introspection data. How to use it: Click the button to generate the query, copy it to your clipboard, execute it against your GraphQL endpoint (using curl, Postman, or GraphQL client), and analyze the returned JSON to understand your schema. Note that some production APIs disable introspection for security; this is normal and expected. Q: How does complexity analysis help with GraphQL performance and security? A: Query complexity analysis is critical for both performance optimization and security. Here's why it matters and how it works: The problem: GraphQL's flexibility lets clients request exactly the data they need, but this also means a single malicious or poorly-written query can request enormous amounts of data, potentially causing denial-of-service conditions, database overload, slow response times for all users, and server crashes. Our solution: The complexity analyzer calculates a "cost" for your query based on (1) Field count: How many fields are selected across all levels. (2) Nesting depth: How many levels deep your selections go. (3) Multiplicative factors: List fields that return multiple items increase complexity. Interpretation: Complexity score 0-50 (green) indicates efficient, well-optimized queries. Score 51-100 (yellow) suggests moderate complexity; monitor for performance issues. Score 101+ (red) indicates high risk; queries may be too expensive for production. Actions you can take: Optimize high-complexity queries by reducing unnecessary nesting, limiting field selections to only required data, breaking complex queries into multiple smaller requests, and implementing pagination for list fields. On the server side, use complexity analysis to implement query cost limits (reject queries above a threshold), rate limit expensive operations, and protect your API from abuse. Example: A query with 100 nested levels requesting every field would have extreme complexity and could timeout; analysis helps you catch and fix this before deployment. Q: What's the difference between beautify and minify, and when should I use each? A: Beautify and minify serve opposite purposes in your GraphQL development workflow, and choosing the right one depends on your context: BEAUTIFY: Formats queries with proper indentation (2 spaces, 4 spaces, or tabs), adds line breaks for readability, aligns fields and brackets consistently, and makes code human-friendly. Use beautify when: developing and writing new queries, code reviewing with your team, debugging and troubleshooting issues, documenting API usage examples, learning GraphQL patterns and best practices, and maintaining query files in version control. MINIFY: Removes all unnecessary whitespace, creates single-line compact queries, eliminates comments and formatting, and makes code machine-friendly. Use minify when: deploying queries to production, sending queries over the network (reduces bandwidth), embedding queries in client applications, optimizing for bundle size in SPAs, and preparing queries for CDN distribution. Practical workflow: (1) Development: Keep queries beautified for readability. (2) Testing: Use beautified versions to understand what's being tested. (3) Production: Minify queries to reduce payload size. (4) Documentation: Always beautify examples for clarity. You can customize beautification style via the indent dropdown to match your team's coding standards. The formatter preserves all logical structure and semantics regardless of which option you choose—only the presentation changes. Q: How does the Schema Explorer help me understand and work with GraphQL APIs? A: The Schema Explorer transforms your GraphQL schema into an interactive, visual interface that makes understanding complex APIs effortless. What it shows: After loading a schema (click "Load Schema"), click "Schema Explorer" to see (1) All types: Every object type, interface, union, enum, and scalar defined in your schema. (2) Type metadata: Each type displays its kind (object, interface, union, etc.), name, and description from schema comments. (3) Fields: All available fields for each type with their return types, arguments with types and default values, required vs optional indicators, and field-level descriptions. (4) Relationships: How types connect to each other through field references. Practical applications: API discovery: Explore unfamiliar APIs without reading documentation. Query planning: Understand what fields and arguments are available before writing queries. Type exploration: Navigate complex nested type structures. Documentation: Use explorer output to create internal API guides. Onboarding: Help new team members understand API capabilities quickly. Schema validation: Verify your schema has all expected types and fields. Example workflow: Load a schema, open Schema Explorer, browse the "Query" type to see available top-level queries, click into nested types to understand what data they expose, and use this information to build complex queries confidently. It's especially valuable for large APIs with hundreds of types where documentation may be incomplete or outdated. Q: Is my GraphQL data secure and private when using this online tool? A: Yes, your data is completely secure and private. Here's why: 100% client-side processing: All GraphQL parsing, validation, formatting, beautification, minification, complexity analysis, schema validation, and fragment management happens entirely in your web browser using JavaScript. Zero server communication: No queries, no schemas, no variables, no operations, and no data of any kind is transmitted to our servers or any third-party services. Local file processing: When you upload files, they're read directly by your browser and processed in memory—never sent across the network. Offline capable: Once the page loads, you can disconnect from the internet and the formatter continues working perfectly. No tracking or analytics on your code: We don't collect, store, or analyze any GraphQL content you process. Browser privacy: All data stays in your browser's memory and is cleared when you close the tab. What this means for you: Your proprietary business logic encoded in queries, your sensitive schema structures revealing database design, your API endpoints and authentication patterns, your variables containing potentially sensitive test data, and your entire GraphQL codebase remains completely private. You can safely format production queries, validate confidential schemas, and work with sensitive GraphQL operations without any security concerns. The only data we might collect is anonymous page analytics (visits, but not content), which helps us improve the tool. For maximum security in enterprise environments, you can even download this page and run it completely offline.

Need Help? Visit our Support Center for assistance with GraphQL formatting, feature requests, or technical questions. We're here to help make your GraphQL development workflow as smooth and efficient as possible.