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How it works
Ask it something hard.
📎 ai-skill-for-julia.txtLOADED ✓
This loop summing x^2 over a Float64 vector is slow in the REPL. Why, and how do I fix it?
CLAUDE · WITH THIS SKILLYou get: the cause in one line (non-const globals stop type inference, so every iteration boxes) -> a type-stable sumsq function using zero(eltype(v)) and @inbounds -> the BenchmarkTools call with $data interpolation and the @code_warntype check to run -> what to look for in the output (no red Any) -> a one-line why on functions vs top-level code -> the single next action: compare allocations, the function should report 0 bytes.
Questions before you buy? A person answers, usually the same day: hello@kissmyskills.com
// the file itself
Read it before you buy it.
The first lines of the file your AI will read, exactly as delivered. Nothing rewritten for the page.
Use the name Once the file is loaded, talk to it by name: “Serge, check this page.” That is what the name is for. It also keeps several skills apart in one chat.
// the skill your AI runs on
You are a senior Julia pair programmer sitting next to the user while they write numerical and scientific code. You have been activated to hand over code that runs in the REPL, benchmarks with BenchmarkTools, and reviews that catch type instability.
KissMySkills.com | Install: paste this whole file into Claude Projects (Project instructions), a custom GPT (Instructions), a Gemini Gem, or your AI's system prompt. Then just ask questions the way you normally would. You are a senior Julia pair programmer sitting next to the user while they write numerical, scientific and data code. You know the type system and multiple dispatch, the performance rules that make Julia fast or slow, the package manager and the main scientific packages. You hand over code that runs in the REPL, benchmarks that show whether it is fast, and reviews that catch type instability early. You are the helper inside the user's Julia work, not a job-role persona. Tone: direct, practical, code first. · Language: multiple dispatch, abstract and concrete types, parametric types, structs and mutable structs, broadcasting with dot syntax, comprehensions, do-blocks, macros, modules. · Performance rules: type stability, no non-const globals, preallocation, in-place functions ending in !, @views, column-major layout, abstract fields in structs, safe use of @inbounds and @simd. · Diagnostics: @code_warntype, @time, @allocated, BenchmarkTools (@btime, @benchmark), Profile and ProfileView, JET, Cthulhu. · Pkg: the ] REPL mode, add, rm, update, status, activate, instantiate, Project.toml and Manifest.toml, compat entries, dev, PkgTemplates. · REPL modes: help (?), shell (;), Pkg (]); Revise.jl for live reloading; startup.jl. · Arrays: Base arrays, LinearAlgebra, SparseArrays, StaticArrays, views, reshaping, broadcast fusion. · Data: DataFrames.jl, CSV.jl, Arrow.jl, JSON3.jl, Dates, Statistics, StatsBase, Distributions. · Scientific stack: DifferentialEquations.jl, Optimization.jl, JuMP, Flux.jl and Lux.jl, Zygote and ForwardDiff, Turing.jl, Symbolics.jl. · Plotting: Plots.jl (GR default, PlotlyJS), Makie (CairoMakie, GLMakie), StatsPlots. · Parallelism: Threads.@threads and @spawn, Distributed with pmap, Channels, CUDA.jl. · Interop: PythonCall, RCall, ccall. · Tooling: juliaup, VS Code Julia extension, Pluto, IJulia, PackageCompiler.
88 lines · .txt · instant download
// what's inside
What's inside this skill
REPL-ready functions with using statements and docstrings
Type stability fixes with @code_warntype and @btime verification steps
Exact Pkg command sequences for broken environments
DataFrames.jl, JuMP, DifferentialEquations.jl and Plots.jl code
Scientists, quants, engineers and data developers who write numerical code in Julia every day.
// two ways to get it
Use it inside your AI, or download it once.
Library plan
This skill and 2,500+ others, inside your chat
$9/mocancel anytime, or $59 a year
All 2,500+ skills, prompt packs and agents, loaded the moment you ask
Nothing to download or paste: connect once in Claude, ChatGPT, Claude Code or Cursor
New skills every week and 10 catalog files a month to download
Trademarks of their respective owners. KissMySkills is not affiliated with or endorsed by them.
// ask your assistant
Or let your AI set up this skill for you.
Go to kissmyskills.com/pages/connector and set up the "AI Skill for Julia" skill (handle: ai-skill-for-julia) for me
Paste it into Claude, ChatGPT, Claude Code, Cursor or Codex. Your AI walks you through connecting KissMySkills (about 3 minutes, 7-day free trial) and loads the skill. What your AI will read →
What you're actually buying
This Claude/ChatGPT skill is a Julia AI pair programmer inside your daily scientific and data work: it writes REPL-ready functions with docstrings, rewrites slow loops into type-stable code and shows the @code_warntype and @btime commands to prove it, explains MethodError and BoundsError traces, repairs broken Project.toml and Manifest.toml environments with exact Pkg commands, and builds DataFrames.jl, DifferentialEquations.jl, JuMP and Plots.jl code for your problem.
It knows multiple dispatch, the performance rules around globals, allocations and column-major arrays, the Pkg REPL modes, threading and Distributed, and how to translate NumPy, pandas or MATLAB into idiomatic Julia. It is a helper in your Julia work, not a job-role persona, and it does not run or benchmark code itself; it gives you the code and the exact check to run.
Works the same way in Claude, ChatGPT and Gemini. One purchase, download the file, install it in under 2 minutes, then paste your code or error and get a fix with the reasoning.
// how to install
Under 2 minutes
Four steps. Any AI chat.
01
Download the file
After checkout, the download link lands in your inbox. Save the .txt file anywhere on your device.
02
Open your AI chat
Any AI chat you already use: Claude, ChatGPT, Gemini, Grok, Copilot or another.
03
Paste the prompt
Open the .txt file, copy the prompt section and paste it into Claude or ChatGPT - or add it to a Project so it is always there.
04
Start working
Your AI is now configured as a specialist. Ask it anything inside its domain.
No technical knowledge required.
With Library there is nothing to download. Connect your AI once, then ask for any skill by name.
It turns Claude or ChatGPT into a Julia AI pair programmer that writes type-stable Julia code, diagnoses slow loops and MethodErrors, fixes Pkg environments, and builds DataFrames.jl, JuMP, DifferentialEquations.jl and Plots.jl code for your problem.
Does it run or benchmark my Julia code for me?+
No. It does not execute anything. It gives you the Julia code plus the exact @btime, @code_warntype or Pkg commands to run in your REPL so you can verify the result yourself.
Can it help translate Python or MATLAB code to Julia?+
Yes. It rewrites NumPy, pandas or MATLAB code into idiomatic Julia, flags the 1-based indexing, broadcasting and mutation differences, and names the matching Julia packages.
Does it know the Julia scientific packages?+
Yes. It writes code for DataFrames.jl, CSV.jl, DifferentialEquations.jl, JuMP, Flux.jl, Turing.jl, Plots.jl and Makie, and tells you when to check the package docs for a solver option it is not certain about in your Julia version.
Ready to give your AI a specialist?
This one and 2,500+ others, inside Claude, ChatGPT, Claude Code, Codex or Cursor. Cancel anytime.