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JAX best practices for numerical computing v1.0.0

Use this resource to write high-performance numerical code with JAX

New

  • 388 downloads
  • 237 likes
  • 173 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install jax-performance-transformations

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent applies jax.jit, jax.vmap and jax.grad to your numerical code and avoids side effects in compiled functions. You get code optimized for JIT compilation.

Mostly picked by

Updated November 2, 2026

Card for the “JAX best practices for numerical computing” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
Apache-2.0

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What you get

  • SKILL.md: principles and the jax.jit, jax.vmap and jax.grad transformations
  • SKILL.md: best practices and performance
  • SKILL.md: common patterns

Good fit for

  • Your computation loop is slow in plain Python
  • You want gradients over a batch of data

Not for

    Tags

    • jax
    • jit
    • vmap
    • numerical computing

    About

    You say

    “Vectorize this distance function with jax.vmap, then compile it with jax.jit.”

    Card for the “JAX best practices for numerical computing” skill

    Skill published by mindrally under the Apache-2.0 license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to write high-performance numerical code with JAX
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE11.3 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md1.5 KB

    Origin and licence

    Listed unmodified

    Author
    mindrally
    Source
    github.com/mindrally/skills/tree/7682ca77710e0971eab4e0ae5dddfa281aea0ba5/jax-best-practices
    Licence
    Apache-2.0

    Notice

    « jax-best-practices » (mindrally, Apache-2.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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