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skill-tester

Validate AI agent skills through scenario-based testing and static analysis.

3|Updated Nov 30, 2025
Search Tags:#automation#testing#validation#qa#regression#agent-skills
One-click install
npx skills add https://github.com/alpoxdev/hypercore-skills --skill skill-tester-alpoxdev
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skill-tester
Source: https://github.com/alpoxdev/hypercore-skills/tree/main/skills/skill-tester
Command: npx skills add https://github.com/alpoxdev/hypercore-skills --skill skill-tester-alpoxdev

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill eliminates the uncertainty of deploying AI agent skills by providing a structured, deterministic framework to verify that your skills trigger correctly and perform as intended under various conditions.

Core Features & Use Cases

  • Scenario-Based Testing: Automatically generates and executes positive, negative, boundary, and edge-case scenarios to ensure robust trigger precision.
  • Static Analysis: Performs structural validation of skill metadata, support file references, and corpus integrity to prevent runtime failures.
  • Evidence Reporting: Generates standardized, actionable test reports with clear pass/fail verdicts and failure taxonomy, making it easy to hand off fixes to developers.

Quick Start

Use the skill-tester to validate the git-maker skill and generate a comprehensive test report including edge cases.

Frequently Asked Questions about skill-tester

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

FAQPage Schema
How do I validate AI agent skills to ensure correct trigger routing?▼

Validate AI agent skills by running scenario-based testing and static analysis of SKILL.md metadata to verify trigger precision, workflow correctness, and resource integrity. This deterministic framework prevents runtime failures and ensures reliable execution.

What is scenario-based testing for AI agent skill regression?▼

Scenario-based testing for AI agent skills automatically generates and executes positive, negative, boundary, and edge-case scenarios to ensure robust trigger precision. It simulates user-facing prompts against defined failure taxonomies to verify workflow correctness.

How do I perform static analysis on skill metadata and support file references?▼

Perform static analysis on skill metadata by validating structural integrity of SKILL.md files, support file references, and corpus assets. This structural validation identifies resource inconsistencies and prevents runtime failures during execution.

Can I generate evidence-based test reports for AI agent skill QA?▼

Yes, you can generate evidence-based test reports for AI agent skill QA that provide standardized pass/fail verdicts and failure taxonomies. These actionable reports make it easy to hand off fixes to developers.

Do I need existing skill repositories to test trigger precision and workflow correctness?▼

Yes, you need existing skill repositories containing SKILL.md metadata and support files to test trigger precision and workflow correctness. The testing framework requires static analysis of these resources to simulate user-facing prompts and prevent runtime failures.

What are the limitations of automated validation for AI agent skills?▼

Automated validation for AI agent skills is limited to static analysis of metadata and simulation of user-facing prompts against defined failure taxonomies. It verifies trigger precision and resource integrity but cannot guarantee live execution behavior in all runtime environments.

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