Individual skill
tooluniverse-protein-sae-variant-interpretation
Interpret a missense variant via ESMC-6B Sparse Autoencoder (SAE) feature activations. For a given protein + variant, computes which interpretable SAE features (catalytic, ligand-binding, PTM, structural motif, domain, etc.) are lost or gained at the mutation site. Use when standard pathogenicity scores (AlphaMissense, ClinVar) say a variant is damaging but you need a MECHANISTIC explanation — e.g. 'why is this variant LoF?' Complements (does not replace) variant-interpretation and variant-to-mechanism skills, which focus on ACMG classification or regulatory mechanism.
plugin/skills/tooluniverse-protein-sae-variant-interpretation/SKILL.md
Source commit 5598a9fc97e32964fe9b703818e7d0747142f179
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 5, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 1,779
- Repository last updated
- Nov 8, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agents Repository topic
- reasoning-agent Repository topic
- reasoning-language-models Repository topic
- tool-use Repository topic
- ai-agents Repository topic
- ai-scientists Repository topic
- automated-science Repository topic
- co-pilot Repository topic
- co-scientist Repository topic
- ai-for-science Repository topic
- legal Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
Read excerpt
# Protein SAE Variant Interpretation
Interpret a single missense variant by comparing reference vs mutant Sparse Autoencoder (SAE) feature activations from the ESMC-6B protein language model. SAE features are interpretable latent dimensions of the model's hidden state — many activate on biologically meaningful patterns (active sites, ligand-binding pockets, PTM sequons, structural motifs).
---
## When to use this skill
Apply when users:
- Ask "why is variant X (a missense) loss-of-function?" and need a mechanistic answer beyond a pathogenicity score
- Have an AlphaMissense / ClinVar "damaging" variant and want to know **which functional feature breaks** (catalytic? binding? PTM site? structural?)
- Want to compare ref vs mutant protein representation at a specific residue
- Are interpreting why a structurally subtle change (single AA) has a big functional impact
