Agent skill · data analytics · aiskillstore
json-validator
Validate, format, and fix JSON data. Use this skill when working with JSON files, API responses, or configuration files that need validation or formatting.
Why this skill is useful
Codifies best practices for JSON validation and formatting that the AI could infer but now doesn't have to guess.
What it needs
About 3k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
JSON Validator Validate, format, and fix JSON data with helpful error messages and suggestions. When to Use This Skill Use this skill when you need to: Validate JSON syntax and structure Format/prettify JSON data Fix common JSON errors Convert between JSON and other formats Analyze JSON structure Validation When validating JSON: 1. Check syntax: Identify syntax errors with line numbers 2. Provide context: Show the problematic section 3. Suggest fixes: Offer specific corrections 4. Explain issues: Describe what's wrong and why Common JSON Errors to Check Missing or extra commas Unclosed brackets/braces Unquoted keys Trailing commas (invalid in strict JSON) Single quotes instead of double quotes Comments (not allowed in JSON) Undefined/NaN/Infinity values Example Validation Output Formatting When formatting JSON: 1. Use 2-space indentation (standard) 2. Sort keys alphabetically (optional, ask user) 3. Remove unnecessary whitespace 4. Ensure consistent structure Example Input (minified): Output (formatted): Fixing Common Issues Trailing Commas Single Quotes Unquoted Keys Comments Conversion When converting to/from JSON: From JSON to other formats YAML: Preserve structure, use proper indentation TOML: Handle nested objects appropriately CSV: Flatten structure if needed, handle arrays XML: Choose appropriate tag names To JSON from other formats Ensure proper escaping Validate the result Maintain data types (strings, numbers, booleans, null) Analysis When analyzing JSON structure: 1. Report schema: Top-level type (object/array) Key names and types Nesting depth Array sizes 2. Identify patterns: Repeated structures Optional fields Data types used 3. Suggest improvements: Inconsistent naming Deep nesting issues Large array optimization Example Analysis Best Practices 1. Always validate before formatting - Don't format invalid JSON 2. Show clear error messages - Include line numbers and context 3. Preserve data types - Don't convert numbers to strings unnecessarily 4. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/json-validator