benchmark

Compare local code patterns against open-source implementations and generate ranked recommendations.

2|Updated Mar 16, 2026
One-click install
npx skills add https://github.com/hamzaPixl/pixl-ai --skill benchmark-hamzapixl
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: benchmark
Source: https://github.com/hamzaPixl/pixl-ai/tree/main/packages/crew/skills/benchmark
Command: npx skills add https://github.com/hamzaPixl/pixl-ai --skill benchmark-hamzapixl

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Quickly find high-quality open-source implementations that illustrate how a pattern, feature, or architecture is implemented in the wild, and identify concrete gaps between your local code and industry examples so you can prioritize improvements.

Core Features & Use Cases

  • Reference discovery: Search GitHub and technical articles to surface 3–5 relevant, high-quality examples filtered by recency, popularity, and stack match.
  • Targeted extraction: Fetch and inspect specific files (README, implementation files, config) from selected repos rather than reading entire repositories.
  • Side-by-side analysis & recommendations: Produce a structured comparison matrix and ranked, actionable recommendations grouped by quick wins, significant changes, and architectural considerations.
  • Use case: Compare an "auth middleware" implementation in your codebase to production-ready open-source projects and get a prioritized playbook for improvements.

Quick Start

Use the benchmark skill to compare your auth middleware against three recent, high-star GitHub implementations and return a structured markdown report with recommendations.

Frequently Asked Questions about benchmark

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

FAQPage Schema
How do I compare my local code patterns against open-source best practices?▼

Benchmarking code against open-source best practices involves searching GitHub to fetch relevant repository files, performing side-by-side analysis, and producing a structured markdown report with ranked recommendations for improvement.

How do I find high-quality GitHub repositories to review for architecture decisions?▼

You can find high-quality GitHub repositories by filtering search results for recency, popularity, and stack match to surface 3–5 relevant examples, then fetching specific implementation files for targeted extraction.

How do I generate a structured code analysis report with ranked improvement recommendations?▼

To generate a structured code analysis report, compare local implementations to fetched open-source files, categorize gaps into quick wins, significant changes, and architectural considerations, and output a prioritized markdown playbook.

Can I use this approach to benchmark an auth middleware implementation?▼

Yes, you can benchmark an auth middleware implementation by comparing it against recent, high-star GitHub projects to identify concrete gaps and receive a prioritized playbook for production-ready improvements.

Do I need to read entire GitHub repositories to identify code improvement opportunities?▼

No, targeted extraction fetches and inspects only specific files like READMEs, implementation files, and configs from selected repositories to perform side-by-side analysis without reading the entire codebase.