llm-evaluation SKILL.md skillA

This file is byte-identical to the first copy the registry indexed. Same content hash, so the same checks give both the same grade.

llm-evaluation from hermeticormus/libreuiux-claude-code is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

mdr add hermeticormus/libreuiux-claude-code/llm-evaluation@git:20251120.288a379

Pins git:20251120.288a379 in mdr.lock. Pin the fingerprint instead.

Audit grade

A, 17 of 17 checks passed

Kind

SKILL.md skill

Repository

hermeticormus/libreuiux-claude-code

Path

plugins/llm-application-dev/skills/llm-evaluation/SKILL.md

Versions recorded

1

Latest version

git:20251120.288a379, committed Nov 20, 2025

Size

13,752 bytes

Repository stars

118

License

MIT

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# LLM Evaluation

Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.

## When to Use This Skill

- Measuring LLM application performance systematically
- Comparing different models or prompts
- Detecting performance regressions before deployment
- Validating improvements from prompt changes
- Building confidence in production systems
- Establishing baselines and tracking progress over time
- Debugging unexpected model behavior

## Core Evaluation Types

### 1. Automated Metrics
Fast, repeatable, scalable evaluation using computed scores.

**Text Generation:**
- **BLEU**: N-gram overlap (translation)
- **ROUGE**: Recall-oriented (summarization)
- **METEOR**: Semantic similarity
- **BERTScore**: Embedding-based similarity
- **Perplexity**: Language model confidence

**Classification:**
- **Accuracy**: Percentage correct
- **Precision/Recall/F1**: Class-specific performance
- **Confusion Matrix**: Error patterns
- **AUC-ROC**: Ranking quality

**Retrieval (RAG):**
- **MRR**: Mean Reciprocal Rank
- **NDCG**: Normalized Discounted Cumulative Gain
- **Precision@K**: Relevant in top K
…

Read the whole file at its exact version.

How to install

mdr add hermeticormus/libreuiux-claude-code/llm-evaluation@sha256:b37039b062cd5d97

[![mdr](https://markdownregistry.com/badge/art_pxg6o7gdzivmbqfl.svg)](https://markdownregistry.com/a/art_pxg6o7gdzivmbqfl)

Versions

The registry has recorded 1 version of this file, committed on Nov 20, 2025.

Audit of the latest version

Source

API

GET https://markdownregistry.com/api/v1/artifacts/art_pxg6o7gdzivmbqfl
GET https://markdownregistry.com/api/v1/resolve?ref=hermeticormus/libreuiux-claude-code/llm-evaluation
GET https://markdownregistry.com/api/v1/blob/b37039b062cd5d977ab66863cd74b493686a5ec2d25b04178a0032df4c6c2b59

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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