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Preview GraphQL queries. Free online tool, no login, no sign-up.

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Usage Guide & Tech FAQ

Usage Guide

  1. Paste the original GraphQL query/mutation.
  2. Review the formatted indentation and hierarchy.
  3. Open FAQ as needed to understand input limitations.
  4. Copy the result back to your project and continue editing.
  5. If multiple operations exist, ensure `operationName` matches client calls.
  6. Huge introspection schemas are easier to review after folding unrelated types.
  7. When pasting variables JSON, keep shapes aligned with the GraphQL variable definitions.
  8. Comments/descriptions may be stripped by some pipelines—confirm before publishing docs.
  9. Format both sides before diffing two versions to reduce whitespace noise.
  10. In code review, watch selection depth and potential N+1 query patterns.
  11. Read the title and description first to confirm this utility matches your task (avoid using the wrong tool and misinterpreting output).
  12. Paste or type input in the editor; if a sample/template is provided, load it first to learn the expected output shape.

Related Tech Knowledge

  • Formatting uses syntax analysis to re-layout fields and nesting.
  • Variables, aliases and nesting affect the final structure.
  • Processing is local and does not send requests to remote servers.
  • If the input is not well-formed, parsing may fail.
  • Server-specific scalars/directives may not be fully understood by generic formatters.
  • Fragment expansion/merging is semantic; formatting improves readability, not query planning.
  • Some errors (duplicate selections, bad aliases) need schema context to detect.
  • Persisted queries hash the canonical text—keep registration in sync with what clients send.
  • Integrations with `gql` tags/build loaders may treat newlines/escapes differently.
  • Never paste production endpoints and auth headers into public channels.
  • Core parsing and computation run in your browser; by default your raw business payload is not persisted to this site’s servers (see on-page privacy notes).
  • The pipeline is typically: read input → parse (lexical/syntactic/structured) → transform → render; failures aim to be diagnosable.