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Write, debug, review, profile, or shard JAX numerical code. Use when the hard part is JAX tracing, autodiff, control flow, PRNGs, compilation, array placement, or runtime performance. Do not impose JAX on a NumPy-only or unrelated GPU task.

Use this Skill: https://skilld.dev/gh/tristanmanchester/agent-skills/jax-development

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referencesSOURCES.md

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Source baseline and maintenance

Reviewed 2026-09-13. The public release baseline is JAX 0.11.1, released 2026-08-17, whose PyPI metadata requires Python >=3.12. There is no blanket upper bound in that metadata; this does not guarantee wheels/backend support for every future interpreter. Check jaxlib, accelerator plugin, driver, and platform requirements separately. Python 3.13 free-threaded support was dropped in 0.11.0; do not conflate it with ordinary CPython 3.13.

Traceable upstream source: tag jax-v0.11.1, commit 2d66622450e2c8633cda2307688ef7aa294bd6eb in jax-ml/jax. This supersedes the unidentified jax-main.zip provenance claim; it does not assert every bundled example came from that tag or that a current-version runtime test was performed.

Current changes relevant to the retained references

  • Prefer with jax.set_mesh(mesh):; the old Mesh context is deprecated.
  • NamedSharding is a placement object. Explicit sharding-in-types requires the appropriate mesh axis types and propagation rules; merely constructing this object is not enough to claim explicit-mode semantics.
  • Ordinary pure-function design remains a useful default. Public jax.ref offers explicit stateful arrays with defined effects; inspect its rules for transforms, autodiff, and lifetimes rather than categorically banning all state.
  • jnp.empty/empty_like are uninitialised in 0.11.0+, not zero constructors.
  • Current export deserialisation checks its compatibility window. Keep provenance, producer/consumer versions and actual load/execute tests; do not bypass expiry errors to pretend an artefact is still supported. Prefer in_shardings_jax and out_shardings_jax over the deprecated HLO sharding fields.
  • Many jax.core/jax.interpreters internals were removed. Use public interfaces and documented jax.extend where appropriate; match source-level debugging to the exact installed commit. Experimental hijax, Pallas, and custom rematerialisation are targeted tools, not obligatory rewrites for every numerical function.
  • A persistent compilation cache is trusted executable infrastructure. Do not use a cache directory writable by untrusted users or accept arbitrary exported executables as inert data.

Primary references

For maintenance, identify the latest stable release, read its versioned changes, then inspect the exact changed method/types. Do not copy unreleased examples into stable guidance. Test selected numerical templates, backend features, and helper failure paths, recording the runtime actually used. Keep static scan/evaluation fixtures separate from measured runtime evidence.

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub1mo

    The skill provides a suite of JAX development tools. It includes functionality for dynamic loading of local modules for benchmarking and a code scanner that processes user files, which introduces a low risk of dynamic execution and indirect prompt injection.

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  • Snyk1mo

    Risk: LOW · No issues

  • ZeroLeaks6mo

    Score: 93/100 · 2 sections analyzed

Signed by skilld at 3323bc9. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 weeks ago.

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Other metadata
compatibility
Current-release baseline JAX 0.11.1 requires Python >=3.12; wheel/backend support must be checked separately. Diagnostics need Python 3.12+ and the project's JAX environment for runtime probes. Static helpers can run without JAX. Benchmark/probe commands execute trusted project code.
metadata
{
  "version": "3.0.0",
  "reviewed": "2026-09-13",
  "source": "https://github.com/jax-ml/jax/tree/jax-v0.11.1"
}

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