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always-works-testing

Enforce execution-based verification of code changes before user notification.

Updated Nov 16, 2025
Search Tags:#code quality#workflow#testing#debugging#software development#verification#reliability
One-click install
npx skills add https://github.com/FlorinPopaCodes/claude-marketplace --skill always-works-testing
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: always-works-testing
Source: https://github.com/FlorinPopaCodes/claude-marketplace/tree/main/plugins/always-works-testing
Command: npx skills add https://github.com/FlorinPopaCodes/claude-marketplace --skill always-works-testing

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill prevents the delivery of untested or non-functional code by enforcing a mandatory execution-based verification process. It ensures that any implemented solution genuinely works before being presented to the user, building trust, reducing rework, and saving valuable time.

Core Features & Use Cases

  • Mandatory Verification: Establishes a "30-Second Reality Check" to confirm code execution, expected results, and the absence of errors, moving beyond theoretical correctness to practical functionality.
  • Contextual Testing: Guides the AI to perform appropriate and specific tests for different change types, including UI interactions, API calls, data modifications, logic changes, configuration updates, and script executions.
  • Use Case: After writing a Python script to process log files, this Skill ensures the AI doesn't just assume it works. Instead, it will use available tools (like bash_tool) to run the script with sample inputs, check its output, and confirm it functions as intended before telling you the task is complete.

Quick Start

Apply the always-works-testing skill to verify the Python script I just wrote for parsing log files.

Frequently Asked Questions about always-works-testing

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

FAQPage Schema
How do I verify that my code changes actually work before deploying?▼

Code verification confirms execution by running your changes with sample inputs, checking outputs, and observing logs and exit codes. This ensures functionality works in practice, not just in theory, catching errors before deployment and reducing rework.

What's the best way to test scripts, APIs, and UI components together?▼

Execute verification across all change types—unit tests for logic, integration tests for APIs, end-to-end tests for UI workflows, and system tests for configurations. Running actual code through available tools confirms real behavior across your full stack.

Why should I verify code execution instead of just reviewing it?▼

Code review catches syntax and logic issues, but execution verification confirms the code actually runs, produces expected outputs, and handles errors correctly. This moves beyond theoretical correctness to practical functionality.

Can I verify code across different environments and deployment scenarios?▼

Yes. Execution verification applies to all environments—development, staging, production—and all scenarios including scripts, APIs, UI components, configurations, and data operations, ensuring consistent functionality wherever code runs.

What happens if my code fails verification?▼

Failed verification surfaces errors, unexpected outputs, or incorrect exit codes before delivery. Observing these failures during testing allows you to fix issues immediately rather than discovering problems in production.

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