disco-kernel-dev
disco-kernel-dev is a Model training & evaluation skill for AI agents, published by NVIDIA in the torch-harmonics repository on GitHub. Skillspace rates disco-kernel-dev D (59/100) and it passed the safety scan; the rating is based on static analysis only.
Expert guide for adding, optimizing, or debugging DISCO convolution kernels in torch-harmonics. Use this skill whenever the user mentions: adding a new kernel variant or GPU arch path, wiring up a kernel through the Python dispatch layer, fixing bf16/fp16/autocast issues in DISCO, profiling or benchmarking the CSR or kpacked forward/backward, propagating kernel changes to the distributed DISCO path, or writing tests that cover all dispatch branches. Also use for debugging correctness issues in the DISCO fwd/bwd path or distributed a2a collectives.
- Grade
- D
- Quality
- 59 / 100
- Safety
- Passed
- GitHub stars
- 687
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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