← All skills

diffdock

80 / 100 · Low risk

Fine to try.

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

Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction.

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/'diffdock' ] || [ -L ~/.agents/skills/'diffdock' ]; then echo 'A skill folder named diffdock 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 "$d" checkout --quiet '894598cd3a90891a077c254566276bd379038bad' -- 'skills/diffdock' && mkdir -p ~/.agents/skills && cp -R "$d"/'skills/diffdock' ~/.agents/skills/'diffdock' && 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/'diffdock' ~/.claude/skills/'diffdock' (other agents: ~/.cursor/skills, ~/.copilot/skills, ~/.gemini/skills, ~/.gemini/config/skills, ~/.config/opencode/skills). Or install through the finder skill, which does both.

Badge for your README

The badge for lamm-mit/scienceclaw shows the score of its lowest-scoring skill.

[![SkillTrust](https://zalavijaysinh.github.io/skilltrust/badges/lamm-mit/scienceclaw.svg)](https://zalavijaysinh.github.io/skilltrust/repos/lamm-mit/scienceclaw/)

Score history