What is the Scan-Compare-Report-Apply workflow?

It is a four-stage process where the engine first scans the filesystem, compares the current state to expected schemas, generates a structured report of issues, and finally recommends or applies fixes.

Can this skill fix issues automatically?

Yes, it can perform 'safe' auto-fixes such as adding missing optional fields, creating templates, or registering items in config files, while requiring human intervention for logic changes.

How does it integrate with my development workflow?

It can be invoked via the /popkit:sync command, used during plugin testing, or integrated into pre-commit hooks and GitHub Actions for continuous validation.

What components does it validate?

It validates AI agents, routing logic, output style schemas, and Python hook scripts within the PopKit ecosystem.

Is this used for runtime user input validation?

No, this engine is specifically designed for developer-side plugin component integrity and configuration checking, not for validating live user inputs.

PopKit Validation Engine

Name: PopKit Validation Engine
Author: jrc1883

byjrc1883

安全与测试

Validates PopKit plugin integrity through a structured Scan-Compare-Report-Apply workflow to ensure component consistency.

关于

The PopKit Validation Engine is a specialized utility designed to maintain the structural integrity of Claude Code plugins by systematically scanning components, comparing them against defined schemas, and generating actionable reports. It automates the verification of agent frontmatter, routing configurations, output styles, and hook scripts, allowing developers to identify and fix configuration drifts or syntax errors before deployment. By providing safe auto-fixes for common issues, it streamlines the maintenance of complex AI-powered workflows and ensures that all plugin components remain synchronized and compliant with required standards.

主要功能

Safe auto-fix recommendations for missing fields and template creation
Schema validation for agent frontmatter, routing paths, and output styles
0 GitHub stars
Actionable reporting with clear error, warning, and info-level findings
Automated Scan-Compare-Report-Apply workflow for plugin components
Integration with CI/CD pipelines and pre-commit development hooks

使用场景

Debugging hook script syntax and communication protocols during development
Verifying plugin structural integrity after manual configuration changes
Ensuring all AI agents are correctly registered and routed in the plugin configuration

关于

主要功能

Safe auto-fix recommendations for missing fields and template creation
Schema validation for agent frontmatter, routing paths, and output styles
0 GitHub stars
Actionable reporting with clear error, warning, and info-level findings
Automated Scan-Compare-Report-Apply workflow for plugin components
Integration with CI/CD pipelines and pre-commit development hooks

使用场景

Debugging hook script syntax and communication protocols during development
Verifying plugin structural integrity after manual configuration changes
Ensuring all AI agents are correctly registered and routed in the plugin configuration