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llm-evaluation

Automates LLM evaluation across prompts, outputs, and safety checks with promptfoo, TruLens, and OpenAI evals.

Updated Jan 12, 2026
Search Tags:#llm#evaluation#benchmark#promptfoo#evals#trulens
One-click install
npx skills add https://github.com/FlexNetOS/ripple-env --skill llm-evaluation-flexnetos
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llm-evaluation
Source: https://github.com/FlexNetOS/ripple-env/tree/main/.claude/skills/llm-evaluation
Command: npx skills add https://github.com/FlexNetOS/ripple-env --skill llm-evaluation-flexnetos

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Streamlines the development and assurance of LLM-based systems by providing a structured toolkit for testing, evaluation, and monitoring of prompts, outputs, and safety across models and datasets.

Core Features & Use Cases

  • Prompt testing with promptfoo to validate prompt behavior and output structure.
  • Behavioral evaluation with TruLens to measure relevance, coherence, groundedness, and safety signals.
  • Benchmarking and CI/CD integration using evals frameworks to track performance across models and prompts in robotics and AI assistants.

Quick Start

Install the evaluation tools and run a basic prompt test to generate a benchmark report.

Frequently Asked Questions about llm-evaluation

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

FAQPage Schema
How do I evaluate LLM outputs for relevance and safety?▼

You can evaluate LLM outputs for relevance and safety by running behavioral evaluations with TruLens and promptfoo to measure coherence, groundedness, and safety signals across your prompts and datasets.

Can I integrate LLM benchmarking into a CI/CD pipeline?▼

Yes, you can integrate LLM benchmarking into a CI/CD pipeline using OpenAI eval frameworks to automatically track prompt and model performance across changes.

What is the best way to test prompt reliability for AI copilots?▼

The best way to test prompt reliability for AI copilots is using promptfoo to validate prompt behavior and output structure, generating comprehensive benchmark reports.

Does this LLM evaluation approach support custom metrics and dashboards?▼

Yes, this LLM evaluation approach supports custom metrics and dashboards, allowing you to define specific testing criteria and visualize benchmarking results for your models.

How do I benchmark LLM performance across different models and datasets?▼

Benchmark LLM performance across models and datasets by applying OpenAI eval frameworks and TruLens to automate testing, compare outputs, and track reliability metrics.

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