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julia-jet

Analyze Julia code for type errors and optimization failures using JET.jl.

30|6|Updated Jan 21, 2026
Search Tags:#static analysis#performance#debugging#julia#type errors#jet
One-click install
npx skills add https://github.com/Krastanov/JuliaLLMAgentSkills --skill julia-jet
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: julia-jet
Source: https://github.com/Krastanov/JuliaLLMAgentSkills/tree/main/julia-jet
Command: npx skills add https://github.com/Krastanov/JuliaLLMAgentSkills --skill julia-jet

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps developers identify type errors, undefined references, and optimization failures in Julia code without executing it, leading to more robust and performant packages.

Core Features & Use Cases

  • Static Analysis: Leverages Julia's compiler inference to detect issues early.
  • Error Detection: Catches MethodError, undefined references, bad field access, and BoundsError.
  • Optimization Analysis: Identifies runtime dispatch, captured variables, and unresolvable calls.
  • Use Case: Before committing changes to a critical Julia package, use this Skill to run a comprehensive static analysis to ensure no new type instabilities or errors have been introduced.

Quick Start

Analyze the provided Julia code for type errors using the julia-jet skill.

Frequently Asked Questions about julia-jet

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

FAQPage Schema
How do I find type errors and optimization failures in Julia code before running it?▼

Static analysis detects type errors and optimization failures in Julia code before execution. By leveraging compiler inference, it catches MethodError, undefined references, and runtime dispatch without running the program.

What is static analysis for Julia packages and how does it work?▼

Static analysis for Julia packages uses compiler inference to identify type instabilities and method errors pre-runtime. This approach scopes analysis to specific modules and filters reports to focus on user-defined code for robust package development.

Can I analyze specific modules in my Julia project to avoid noise from dependencies?▼

Yes, static analysis scopes to specific modules and filters reports to focus on user-defined code. This ensures package stability by isolating type errors and runtime dispatch issues within your own codebase.

How do I detect runtime dispatch and captured variables in Julia before committing changes?▼

Run static analysis to identify runtime dispatch, captured variables, and unresolvable calls. This pre-runtime detection ensures no new type instabilities or performance bottlenecks have been introduced into your Julia package.

What kind of errors can static analysis catch in Julia code?▼

Static analysis catches MethodError, undefined references, bad field access, and BoundsError in Julia code. It also identifies optimization failures like runtime dispatch and unresolvable calls to improve performance.

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