skill
sparse-autoencoder-training Review findings
orchestra-researchorchestra-research/ai-research-skillsupdated
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.
- Stars
- 14,234
- Version
- v1
- Copies
- 0
Overview
Waxell's checks found 2 findings to review, highest severity high.
- Highest severity
- high
- Findings
- 2
- What ran
- Static analysis
A clean result means nothing alarming in what is published, not a guarantee. How the checks work
We don't republish the skill's instructions. Read them on GitHub at the reviewed commit.
Security
Security scan
Checked 2 days ago
Result
Review findings Waxell's checks found 2 findings to review, highest severity high.
Checked with static analysis: servers it launches, packages it installs at runtime, scripts piped to a shell and bundled binaries. Nothing was run. How the checks work
Findings (2)
high · 2
- high
Tells Claude to install unpinned packages (sae-lens)
SKILL.md:40 · skill_risk:S2
- high
Tells Claude to install unpinned packages (sae-lens)
references/README.md:20 · skill_risk:S2
Versions
Version history
Each distinct content we have seen, newest first, with the verdict it got at the time.
One version so far: v1 (1.0.0), seen 2026-11-03.
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SOC 2 Type II attested · ISO/IEC 27001:2022 certified · HIPAA with a BAA · aligned to the EU AI Act and NIST AI RMF
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