Individual skill

jax-skills

High-performance numerical computing and machine learning workflows using JAX. Supports array operations, automatic differentiation, JIT compilation, RNN-style scans, map/reduce operations, and gradient computations. Ideal for scientific computing, ML models, and dynamic array transformations.

tasks/jax-computing-basics/environment/skills/jax-skills/SKILL.md

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# Requirements for Outputs

## General Guidelines

### Arrays
- All arrays MUST be compatible with JAX (`jnp.array`) or convertible from Python lists.
- Use `.npy`, `.npz`, JSON, or pickle for saving arrays.

### Operations
- Validate input types and shapes for all functions.
- Maintain numerical stability for all operations.
- Provide meaningful error messages for unsupported operations or invalid inputs.

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