self-normalizing-networks
self-normalizing-networks is a Model training & evaluation skill for AI agents, published by bioinf-jku in the SNNs repository on GitHub. Skillspace rates self-normalizing-networks B (80/100) and it passed the safety scan; the rating is based on static analysis only.
Use this skill when working in the Self-Normalizing Networks tutorial repository, especially for TensorFlow, PyTorch, Conda environment, or SELU/AlphaDropout implementation tasks.
- Grade
- B
- Quality
- 80 / 100
- Safety
- Passed
- GitHub stars
- 1,588
Unproven: rated by static analysis only, not yet compared head-to-head.
Not launch-quality. It is graded B with a clean safety verdict, but our quality filters exclude it: a model that read it found it written only for the repository it lives in. So it is not in our launch-quality set, the skills our MCP server searches and recommends. How launch-quality is decided
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 98 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- GPL-3.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Repo-internal: written for the repository it lives in. Explicitly scoped to working in this tutorial repository's examples
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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