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molfeat

80 / 100 · Low risk

Fine to try.

By lamm-mit/scienceclaw (GitHub) · data · 251 stars · scanned at commit 894598c

Molecular ML featurization library (100+ featurizers: ECFP, descriptors, ChemBERTa). Input: SMILES strings you already possess. Output: numerical feature vectors for QSAR/ML models. Does NOT retrieve compounds from any database — querying by topic name returns only a metadata stub. Use pubchem or chembl to obtain SMILES first, then featurize here. For ADMET predictions use tdc.

Works with any agent that supports SKILL.md skills.

What this skill can do

Install

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

if [ -e ~/.agents/skills/'molfeat' ] || [ -L ~/.agents/skills/'molfeat' ]; then echo 'A skill folder named molfeat already exists — not replacing it' >&2; false; else d=$(mktemp -d) && git clone --quiet --filter=blob:none --no-checkout 'https://github.com/lamm-mit/scienceclaw' "$d" && git -C "$d" checkout --quiet '894598cd3a90891a077c254566276bd379038bad' -- 'skills/molfeat' && mkdir -p ~/.agents/skills && cp -R "$d"/'skills/molfeat' ~/.agents/skills/'molfeat' && 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/'molfeat' ~/.claude/skills/'molfeat' (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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