eval-skills

Evaluate AI agent skills atomically with deterministic scoring and regression diffing.

4|Updated Feb 28, 2026
One-click install
npx skills add https://github.com/isLinXu/eval-skills --skill eval-skills-islinxu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: eval-skills
Source: https://github.com/isLinXu/eval-skills/tree/main
Command: npx skills add https://github.com/isLinXu/eval-skills --skill eval-skills-islinxu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill provides a framework to evaluate AI agent skills at the atomic unit level (L1), enabling reliable quality gates before integration into agents and pipelines.

Core Features & Use Cases

  • Framework-agnostic discovery, scaffolding, evaluation, and reporting for AI Skill units.
  • Regression diffing, multi-dimensional scoring, sandboxed execution, and CI/CD integration.
  • Use cases include comparing candidate skills on the same benchmark, enforcing quality gates in CI, and producing human-readable reports for teams.

Quick Start

Install the skill and run eval-skills to generate a quality report for a sample skill.

Frequently Asked Questions about eval-skills

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

FAQPage Schema
How do I evaluate AI agent skills for quality gates in CI/CD pipelines?▼

You evaluate AI agent skills by applying atomic evaluation units with runtime validation and deterministic scoring. This framework enforces quality gates in CI/CD pipelines through regression diffing and structured outputs.

What is atomic skill evaluation and how does it work?▼

Atomic skill evaluation assesses AI agent skills at the L1 unit level to ensure reliable quality gates. It applies adapter-agnostic evaluation across the full skill lifecycle, from discovery and scaffolding to multi-dimensional scoring and reporting.

Do I need specific dependencies to run adapter-agnostic skill evaluation?▼

No specific dependencies are required to run adapter-agnostic skill evaluation. The framework operates independently using scripts to provide sandboxed execution, deterministic scoring, and structured outputs for candidate skills.

Can I compare candidate AI skills on the same benchmark?▼

Yes, you can compare candidate AI skills on the same benchmark. The framework applies regression diffing and multi-dimensional scoring to evaluate multiple skills and produce human-readable comparison reports.

How do I generate multi-format reports for AI skill benchmarks?▼

You generate multi-format reports for AI skill benchmarks by executing the evaluation scripts across the skill lifecycle. The framework produces human-readable reports with structured outputs and deterministic scoring for team review.

What's the best way to enforce runtime validation when evaluating AI skills?▼

The best way to enforce runtime validation when evaluating AI skills is using adapter-agnostic evaluation with deterministic scoring. This framework ensures structured outputs and sandboxed execution across the full skill lifecycle.