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msa-structure-prediction-pipeline

95 / 100 · Low risk

Fine to try.

By stanfish06/skillquarium (GitHub) · coding · 12 stars · scanned at commit ced6c96

NOTE: your protein sequence and the retrieved MSA alignment are transmitted to external NVIDIA-hosted APIs (health.api.nvidia.com) on every call. Use local NIM containers for confidential or proprietary sequences. Run a complete protein structure prediction pipeline using NVIDIA BioNeMo NIMs: search for MSA alignments with MSA-Search (ColabFold), then predict the structure with OpenFold3 using the retrieved alignments. Use this skill whenever the user wants to predict a protein structure with m…

Works with any agent that supports SKILL.md skills.

What this skill can do

Connects to the internet

The author does not mention this.

Found in 2 places.

Install

Paste this into your terminal. It downloads exactly the version we scanned, not whatever is newest.

if [ -e ~/.agents/skills/'msa-structure-prediction-pipeline' ] || [ -L ~/.agents/skills/'msa-structure-prediction-pipeline' ]; then echo 'A skill folder named msa-structure-prediction-pipeline already exists — not replacing it' >&2; false; else d=$(mktemp -d) && git clone --quiet --filter=blob:none --no-checkout 'https://github.com/stanfish06/skillquarium' "$d" && git -C "$d" checkout --quiet 'ced6c96bd67acccbf0280a5071e59a523c118c66' -- 'skills/msa-structure-prediction-pipeline' && mkdir -p ~/.agents/skills && cp -R "$d"/'skills/msa-structure-prediction-pipeline' ~/.agents/skills/'msa-structure-prediction-pipeline' && rm -rf "$d"; fi

Codex reads ~/.agents/skills directly. For Claude Code, Cursor, Copilot, Gemini CLI, Antigravity or OpenCode, also link it. For Claude Code: ln -s ~/.agents/skills/'msa-structure-prediction-pipeline' ~/.claude/skills/'msa-structure-prediction-pipeline' (other agents: ~/.cursor/skills, ~/.copilot/skills, ~/.gemini/skills, ~/.gemini/config/skills, ~/.config/opencode/skills). Or install through the finder skill, which does both.

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Score history

DateVersionScore
2026-11-13ced6c9695
2026-11-08f748ea9100