check-spots

Validate spots.json for missing fields, invalid URLs, and duplicate entries.

4|Updated May 26, 2025
One-click install
npx skills add https://github.com/pwittchen/varun.surf --skill check-spots
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: check-spots
Source: https://github.com/pwittchen/varun.surf/tree/main/.claude/skills/check-spots
Command: npx skills add https://github.com/pwittchen/varun.surf --skill check-spots

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Validate spots.json for common data quality issues, including missing fields, invalid URLs, and duplicate entries.

Core Features & Use Cases

  • Checks structure, required fields, URL formats, duplicates, and data consistency across spots.json.
  • Detects and reports issues to help maintain reliable kite-spots data for apps and analytics.
  • Integrates with CI to guard data quality before deployment.

Quick Start

Run the validation on src/main/resources/spots.json to generate a report of issues and suggested fixes.

Frequently Asked Questions about check-spots

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate JSON data for missing fields and duplicate entries?

To validate JSON for missing fields and duplicates, you need structural validation that checks required fields and duplication detection across all entries. This ensures consistent data quality and proper URL formats throughout the file.

Can I integrate JSON data quality validation into a CI pipeline?

Yes, you can integrate JSON data quality validation into CI pipelines to guard data quality before deployment. Running validation checks during CI catches missing fields and invalid URLs, preventing inconsistent data from reaching production.

What does structural validation for a JSON file check for?

Structural validation for a JSON file checks for required fields, proper URL formats, duplicate entries, and basic data-type validation. It enforces data consistency by applying field checks and duplication detection across all entries.

How do I check for invalid URLs and missing fields in a JSON dataset?

Checking for invalid URLs and missing fields in a JSON dataset requires applying field checks and URL format validation across all entries. The process reports detected issues to help maintain reliable data for apps and analytics.

Does this JSON validation tool require any external dependencies?

No, this JSON validation tool does not require any external dependencies to run. It operates independently to perform structural validation, field checks, duplication detection, and basic data-type validation on the target file.