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Jax Best Practices

Checked
mindrally·vlatest·other·Apache-2.0

Ensures JAX code adheres to best practices for performance, readability, and maintainability, optimizing your machine learning workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add mindrally/skills --skill jax-best-practices -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

mindrally

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned mindrally/skills at 7682ca7771.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
7682ca7771
Manifest
jax-best-practices/SKILL.md
Scanned
1 file, 57 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill enables AI agents to review and optimize JAX code, ensuring adherence to best practices for high-performance numerical computing and machine learning. It focuses on functional programming principles, leveraging key JAX transformations like jax.jit, jax.vmap, and jax.grad to improve performance, readability, and maintainability of your workflows. The skill guides the agent towards writing pure functions, utilizing appropriate data types, and employing techniques like checkpointing for memory efficiency.

When to use it

  • When you need to optimize existing JAX code for faster execution.
  • To ensure new JAX code follows established best practices from the start.
  • When debugging performance bottlenecks in your machine learning models using JAX.
  • For guidance on effectively utilizing JAX transformations like jax.jit and jax.vmap.

Key capabilities

  • Functional Programming Guidance: Encourages writing pure functions without side effects.
  • JAX Transformation Expertise: Provides advice on effective use of jax.jit, jax.vmap, and jax.grad.
  • Performance Optimization: Suggests techniques to minimize Python overhead, choose appropriate data types, and batch operations.
  • Pytree Utilization: Recommends using pytrees for managing nested data structures.
  • Profiling Support: Encourages the use of the JAX profiler to identify and address performance bottlenecks.

Example prompts

  • "Review this JAX code snippet and suggest improvements for performance."
  • "How can I best utilize jax.vmap in this function?"
  • "What are some common pitfalls when using jax.jit, and how can I avoid them?"

Tips & gotchas

  • This skill assumes a working knowledge of JAX fundamentals.
  • The agent's recommendations are based on established best practices; always profile your code to confirm improvements.
  • For complex custom operations, the skill may suggest implementing custom vjp/jvp functions.