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Reference documentation for AI coding assistants covering: - cuequivariance: custom group definition (Irrep subclass with @DataClass), segmented tensor products, CG coefficients, descriptors, EquivariantPolynomial - cuequivariance_jax: segmented_polynomial primitive (naive/uniform_1d), RepArray and ir_dict interfaces, NNX layers, indexing, multi-batch axes Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Move SKILL.md files from repo root into the Python package directories
so they ship with pip install. Add __main__.py so users can retrieve
the skill content with:
python -m cuequivariance skill
python -m cuequivariance_jax skill
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Fix jax/poly.rst: output ShapeDtypeStruct was (3,3) for a flat size-9 operand, causing a warning. Use (-1,) to infer from descriptor. - Add jax/ir_dict.rst tutorial: split_operand_by_irrep, segmented_polynomial_uniform_1d, gather/scatter indexing, utilities. - Add ir_dict, nnx, and Repeats sections to cuequivariance_jax API docs. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Makes the `python -m <package> skill` command discoverable via `help()` or docstring inspection, which is typically the first thing an AI coding assistant does when exploring an unfamiliar library. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Can you ask Claude to add a skill for torch too? |
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