Model Evaluation Benchmark Skill
CommunityAutomate AI model benchmarking.
Software Engineering#reporting#benchmark#performance testing#model evaluation#ai comparison#workflow adherence
Authorrysweet
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill automates the complex and time-consuming process of evaluating and comparing the performance of different AI models against standardized benchmarks.
Core Features & Use Cases
- End-to-End Benchmarking: Orchestrates setup, execution, analysis, and reporting for model evaluations.
- Comprehensive Metrics: Measures efficiency (duration, cost), quality (code scores), and workflow adherence.
- Use Case: When deciding between deploying GPT-4 or Claude Opus for a new feature, use this skill to run a benchmark suite that objectively measures which model performs better on relevant tasks.
Quick Start
Run the model evaluation benchmark suite for Opus and Sonnet models.
Dependency Matrix
Required Modules
pythongh-cli
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: Model Evaluation Benchmark Skill Download link: https://github.com/rysweet/RustyClawd/archive/main.zip#model-evaluation-benchmark-skill Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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