Validate YAML

Quickly check a YAML file for supported syntax errors and report the first error with line and column details.

The validator stops at the first supported syntax problem it can identify and reports a line and column. That makes it useful as a quick pre-deployment check for indentation mistakes, missing mapping separators, malformed inline collections, and other common configuration errors. In every case the main workflow is deliberately visible: enter or load data, run the primary action, inspect the result or validation message, and then copy or download the output when the tool provides an export. The editor is a normal accessible textarea with a connected label, keyboard-focusable controls, visible error and success states, and a responsive two-column layout that stacks on smaller screens. There is no requirement to create an account, select a server-side processing job, or wait for an upload queue.

The parser is intentionally focused on the YAML forms most often used for application and infrastructure configuration. It handles nested mappings, sequences, scalar values, quoted strings, numbers, booleans, nulls, inline arrays, inline mappings, comments, document markers, and simple literal or folded text blocks. Input is normalized only as part of parsing; a conversion or formatting operation then creates a new representation from the resulting data structure. This distinction matters because YAML is not just indentation around arbitrary text: the same characters can represent different data types depending on quoting and context.

For validate yaml, the input is treated as untrusted text. The browser code escapes error content before placing it in the page, does not evaluate pasted text, and does not construct executable code from the input. The generated template also avoids third-party runtime dependencies, external APIs, and CDN libraries. As a result, the core operation can run without a network request once the page itself has loaded. The local-only design is useful when configuration contains internal hostnames, credentials placeholders, deployment settings, feature flags, or other material that should not be copied into a public conversion service.

Output behavior is intentionally conservative. Formatting does not promise to preserve comments as comments because comments are discarded when the input becomes a plain data structure. Conversion tools similarly do not invent application schema information. A syntactically valid configuration can still fail a product-specific validation rule, and this interface does not pretend to know those rules. The validator therefore reports parser validity, while the transformation tools report whether the input could be parsed into the supported data model. When something outside that model is encountered, the tool shows an error rather than silently guessing a replacement.

Several edge cases are handled explicitly. Empty input is rejected instead of being treated as a successful document. Indentation with tab characters is rejected because the parser expects spaces for structural indentation. Missing mapping colons, empty mapping keys, unsupported indentation changes, malformed inline collections, and invalid JSON for the JSON-to-YAML tool produce a visible error and leave the previous source text intact. Clear removes both the input and generated state. Load Sample restores a known-good configuration so the primary workflow can be tested immediately after the page loads.

The statistics shown after successful processing are a practical sanity check rather than a schema report. They summarize keys, arrays, objects, scalar values, nesting depth, or output character count depending on the tool. These counts help confirm that the parser saw roughly the structure you expected before you copy the result elsewhere. The export action uses a browser Blob and a temporary download URL, so the generated file is created on the device. Clipboard copying uses the browser Clipboard API when available and falls back to a hidden textarea copy path for environments where the modern API is unavailable.

Performance is kept proportional to the size of the text being entered. The implementation does not make a remote request for each validation or conversion, and it does not add a package dependency that has to be fetched at runtime. The practical ceiling is therefore the browser’s available memory and the size of the editor content. For normal configuration files this keeps the interaction immediate. For extremely large generated manifests, users should still treat the browser as a convenience tool rather than assume unlimited file size or command-line scale.

Use Validate YAML when you need a controlled, repeatable browser workflow for common YAML configuration tasks. It is especially useful for small edits, documentation examples, deployment snippets, API configuration, CI files, local development settings, and quick checks before committing a file. The tool deliberately favors predictable behavior over broad claims of complete YAML language coverage, making its success and failure states easier to understand and safer to act on.

Before relying on a converted or formatted configuration in production, compare the generated output with the original source and validate it with the target application or platform. A serializer can preserve the parsed data model without knowing whether a particular key, value range, environment variable, or deployment option is valid for your application. This tool gives you a reliable syntax-and-transformation step; your target system remains the final authority on configuration semantics.

• Syntax validation: Parses supported YAML structures before reporting the document as valid.
• Line feedback: Parser errors include the source line when the issue can be located.
• Column feedback: Indentation and mapping errors include a useful column position.
• Empty-input handling: Blank input is rejected with a direct message rather than being treated as valid data.
• Structural checks: Detects missing colons, empty keys, unsupported indentation patterns, and malformed inline structures.
• Scalar checks: Recognizes common null, boolean, numeric, quoted, and plain scalar values.
• Sample validation: Loads a valid configuration so the success state can be tested immediately.
• Statistics: Displays counts for scalar values, arrays, objects, and nesting depth.
• Clear action: Resets the validation state and editor without reloading the page.
• Browser-only operation: The validator does not send the YAML document to an external API.

1. Paste the YAML you want to check into the editor.
2. Click Load Sample to verify the valid-result state before using your own document.
3. Click Validate YAML to run the parser.
4. Read the success panel when the document is valid and review the structure statistics.
5. For invalid input, note the reported line and column and inspect the corresponding indentation or mapping token.
6. Correct the YAML and validate it again.
7. Use Clear to reset the editor and validation result for another file.

Example 1 - Valid service configuration. A normal nested mapping and sequence validates successfully.

server:
  host: localhost
  ports:
    - 8080

Example 2 - Missing colon. A mapping line without : is rejected.

server localhost

Example 3 - Bad indentation. A child line that does not belong to a consistent parent can produce an indentation error.

server:
    host: localhost
  port: 8080

Example 4 - Inline mapping. A small flow-style object is accepted by the supported parser.

db: {host: localhost, port: 5432}

Example 5 - Empty input. A blank editor produces a clear empty-input error instead of a false positive.

<empty>

• Catch mistakes early: Find common YAML syntax problems before deploying a configuration.
• Actionable errors: Line and column information speeds up manual correction.
• No upload step: Validation can happen without transferring a potentially sensitive config.
• Reusable parser: Transformation tools in the same bundle use the same parsing rules.
• Quick iteration: Validate, correct, and validate again without page reloads.
• Useful statistics: Structure counts give a quick sanity check on a document.
• Lightweight workflow: No external editor or command-line YAML dependency is required.