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llm-evaluation

Automate LLM evaluation with BLEU, ROUGE, and BERTScore metrics.

2|Updated Apr 6, 2026
Search Tags:#metrics#LLM evaluation#regression detection#performance measurement#A/B comparison
One-click install
npx skills add https://github.com/bingeli1379/eli-marketplace --skill llm-evaluation-bingeli1379
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llm-evaluation
Source: https://github.com/bingeli1379/eli-marketplace/tree/main/plugins/sdd-python/skills/llm-evaluation
Command: npx skills add https://github.com/bingeli1379/eli-marketplace --skill llm-evaluation-bingeli1379

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, nltk, transformers, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps evaluate the quality of LLM applications, enabling automated metrics, regression detection, A/B comparison, and building eval/benchmark harnesses.

Core Features & Use Cases

  • Automated Metrics: Provides automated metrics for various aspects like text generation, classification, and retrieval.
  • Regression Detection: Detects performance regressions in LLM applications.
  • A/B Comparison: Enables comparison of different models or prompts.
  • Use Case: For a company looking to improve their LLM model, this Skill can be used to measure performance, detect regressions, and compare models.

Quick Start

To start evaluating your LLM model, use the llm-evaluation skill with the 'evaluate' command.

Frequently Asked Questions about llm-evaluation

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

FAQPage Schema
How do I calculate BLEU and ROUGE scores for LLM evaluation?▼

To calculate BLEU and ROUGE scores for LLM evaluation, use this Skill's automated metrics scripts to measure text generation quality against reference outputs.

What is the best way to detect performance regressions in LLM applications?▼

Detect LLM application performance regressions using this Skill's automated regression detection, which evaluates outputs across versions to identify metric drops like BERTScore.

Can I use this Skill for A/B comparison of different LLM models or prompts?▼

Yes, this Skill enables A/B comparison of different LLM models or prompts by evaluating automated metrics side-by-side to determine which variation performs better.

Do I need Python libraries like numpy and transformers to run BERTScore evaluation?▼

Yes, running BERTScore evaluation requires Python libraries like numpy, nltk, and transformers to handle numerical operations, text processing, and model-based semantic similarity calculations.

How do I build an eval harness for classification and retrieval metrics?▼

Build an eval harness for classification and retrieval metrics using this Skill's automated evaluation framework, which provides reference scripts to systematically measure task performance.

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