repo-eval

Assess GitHub repositories and generate a 0-100 score with extraction proposals.

Updated Mar 31, 2026

Search Tags:#automation #github #code-review #pattern-discovery #repository-analysis #skill-extraction

Ready to run

npx skills add https://github.com/GGEdu/claude-god-mode-template --skill repo-eval-ggedu

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: repo-eval
Source: https://github.com/GGEdu/claude-god-mode-template/tree/main/skills/repo-eval
Command: npx skills add https://github.com/GGEdu/claude-god-mode-template --skill repo-eval-ggedu

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Assess GitHub repositories to identify reusable skills, agents, rules, and stacks, and generate a structured evaluation score with extraction proposals.

Core Features & Use Cases

Screen repositories to determine if they introduce new skills, agents, rules, or patterns for the system.
Produce a 0-100 score and a structured extraction proposal to integrate into stacks/skills.
Support ongoing repo-review workflows and weekly repository discovery.

Quick Start

Run an evaluation on a target repository URL to generate a complete metadata payload.

Frequently Asked Questions about repo-eval

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

FAQPage Schema

How do I identify reusable skills and patterns in a GitHub repository?▼

To identify reusable skills in a GitHub repository, you can run an automated evaluation that checks for a valid SKILL.md at the root, extracts frontmatter metadata, and inspects optional scripts or assets to produce a structured 0-100 score.

What is a GitHub repository analysis score used for?▼

A GitHub repository analysis score is used to screen repositories for new skills, agents, rules, and patterns, generating a structured extraction proposal that can be integrated into your existing stacks and workflows.

Can I automate code review and skill extraction from GitHub repos?▼

Yes, you can automate skill extraction by applying this evaluation during repository screening or weekly repo discovery, processing a URL to extract frontmatter names, descriptions, and pattern metadata into a structured payload.

Does the repository evaluation check for specific files in the root directory?▼

The repository evaluation checks for the presence of a valid SKILL.md file in the root directory, extracts the frontmatter name and description, and inspects optional scripts, references, and assets to discover patterns.

How do I generate a structured extraction proposal for a GitHub repo?▼

You generate a structured extraction proposal by running an evaluation on a target repository URL, which assesses the repo's contents and outputs a complete metadata payload with a 0-100 score for integration into your system.

What are the limitations of automated pattern discovery in repositories?▼

Automated pattern discovery relies on identifying a valid SKILL.md at the repository root; if the frontmatter or optional scripts, references, and assets are missing or improperly formatted, the evaluation may not extract the intended patterns.