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JaiminVadadoriya
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ai-system-testing

Test AI features including LLM prompts, tool calls, and nondeterministic outputs.

1|Updated Feb 18, 2026
Search Tags:#ai testing#ai safety#prompt testing#response quality#llm testing
One-click install
npx skills add https://github.com/JaiminVadadoriya/Distributed-Cloud-Storage---Sync-Platform --skill ai-system-testing-jaiminvadadoriya
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-system-testing
Source: https://github.com/JaiminVadadoriya/Distributed-Cloud-Storage---Sync-Platform/tree/main/.agents/skills/ai-system-testing
Command: npx skills add https://github.com/JaiminVadadoriya/Distributed-Cloud-Storage---Sync-Platform --skill ai-system-testing-jaiminvadadoriya

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires deepeval, promptfoo, ragas, trulens, inspectai, garak, pyrit, braintrust, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a comprehensive approach to testing AI-powered features, addressing challenges like nondeterminism, hallucination risk, and safety concerns.

Core Features & Use Cases

  • AI Testing Framework: Covers prompt regression, response quality evaluation, tool call validation, and safety testing.
  • Use Case: Utilize this Skill to test an AI-powered chatbot's responses, ensuring it adheres to quality and safety standards.

Quick Start

Run the ai-system-testing skill to assess the quality of the chatbot's responses to a set of predefined prompts.

Frequently Asked Questions about ai-system-testing

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

FAQPage Schema
How do I test LLM prompts for regressions and response quality?▼

Test LLM prompts by running predefined prompts against your chatbot to evaluate response quality, validate tool calls, and check for regressions using Python evaluation frameworks.

What is the best way to assess hallucination risk in AI chatbot responses?▼

Assess hallucination risk by executing AI safety testing scripts that evaluate nondeterministic outputs and validate response quality against predefined safety standards.

Can I use DeepEval and Ragas to validate nondeterministic AI outputs?▼

Yes, you can use DeepEval and Ragas along with Promptfoo, TruLens, and InspectAI to run comprehensive evaluations of nondeterministic AI outputs and tool call validations.

How do I validate tool calls made by an AI-powered feature?▼

Validate AI tool calls by running testing scripts that execute tool call validation checks, ensuring the AI system adheres to expected interaction patterns and safety standards.

Do I need Python libraries to perform prompt regression testing?▼

Yes, prompt regression testing requires Python libraries for LLM interaction and evaluation, utilizing frameworks like Garak, Pyrit, and Braintrust to assess response quality.

What are the limitations of testing nondeterministic LLM outputs?▼

Testing nondeterministic LLM outputs requires predefined prompts and relies on evaluation frameworks to catch regressions, but inherently faces challenges in predicting every possible response variation.

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