Skill · em Dados, IA e pesquisa
molfeat
Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.
Procedência
- Origem: davila7/claude-code-templates
- Caminho:
cli-tool/components/skills/scientific/molfeat - Versão fixada:
57f899e5394bb8ca166f38eacae8f0853cbfe033 - Licença: MIT
- Espelhado em 25/09/2026
- nenhum download no Claude Code Templates (lido em 25/09/2026)
Antes de instalar
4 arquivos · 53,4 KB · só texto, nenhum script
Instalar na sua CLI
O comando baixa a versão fixada (commit 57f899e) direto da origem, para a pasta que a CLI lê. Precisa de curl (macOS e Linux); no Windows não há comando, porque o Rook Labs é para macOS.
Claude Code
Neste projeto: instala em .claude/skills/molfeat/.
d=".claude/skills/molfeat" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/molfeat" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/api_reference.md" "$u/references/api_reference.md" \ -o "$d/references/available_featurizers.md" "$u/references/available_featurizers.md" \ -o "$d/references/examples.md" "$u/references/examples.md" \ -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"
Global: instala em ~/.claude/skills/molfeat/.
d="$HOME/.claude/skills/molfeat" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/molfeat" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/api_reference.md" "$u/references/api_reference.md" \ -o "$d/references/available_featurizers.md" "$u/references/available_featurizers.md" \ -o "$d/references/examples.md" "$u/references/examples.md" \ -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"
Codex
Neste projeto: instala em .agents/skills/molfeat/.
d=".agents/skills/molfeat" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/molfeat" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/api_reference.md" "$u/references/api_reference.md" \ -o "$d/references/available_featurizers.md" "$u/references/available_featurizers.md" \ -o "$d/references/examples.md" "$u/references/examples.md" \ -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"
Global: instala em ~/.agents/skills/molfeat/.
d="$HOME/.agents/skills/molfeat" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/molfeat" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/api_reference.md" "$u/references/api_reference.md" \ -o "$d/references/available_featurizers.md" "$u/references/available_featurizers.md" \ -o "$d/references/examples.md" "$u/references/examples.md" \ -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"
Antigravity
Neste projeto: instala em .agents/skills/molfeat/.
d=".agents/skills/molfeat" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/molfeat" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/api_reference.md" "$u/references/api_reference.md" \ -o "$d/references/available_featurizers.md" "$u/references/available_featurizers.md" \ -o "$d/references/examples.md" "$u/references/examples.md" \ -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"
Global: instala em ~/.gemini/antigravity-cli/skills/molfeat/.
d="$HOME/.gemini/antigravity-cli/skills/molfeat" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/molfeat" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/api_reference.md" "$u/references/api_reference.md" \ -o "$d/references/available_featurizers.md" "$u/references/available_featurizers.md" \ -o "$d/references/examples.md" "$u/references/examples.md" \ -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"
Peça ao Rook
Já usa o Rook Labs? Cole no chat do Rook: instale a skill https://rooklabs.sh/marketplace/cct.molfeat
Prévia do SKILL.md
---
name: molfeat
description: "Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML."
---
# Molfeat - Molecular Featurization Hub
## Overview
Molfeat is a comprehensive Python library for molecular featurization that unifies 100+ pre-trained embeddings and hand-crafted featurizers. Convert chemical structures (SMILES strings or RDKit molecules) into numerical representations for machine learning tasks including QSAR modeling, virtual screening, similarity se…
## When to Use This Skill
This skill should be used when working with:
- **Molecular machine learning**: Building QSAR/QSPR models, property prediction
- **Virtual screening**: Ranking compound libraries for biological activity
- **Similarity searching**: Finding structurally similar molecules
- **Chemical space analysis**: Clustering, visualization, dimensionality reduction
- **Deep learning**: Training neural networks on molecular data
- **Featurization pipelines**: Converting SMILES to ML-ready representations
- **Cheminformatics**: Any task requiring molecular feature extraction
## Installation
```bash
uv pip install molfeat
# With all optional dependencies
uv pip install "molfeat[all]"
```
**Optional dependencies for specific featurizers:**
- `molfeat[dgl]` - GNN models (GIN variants)
- `molfeat[graphormer]` - Graphormer models
- `molfeat[transformer]` - ChemBERTa, ChemGPT, MolT5
- `molfeat[fcd]` - FCD descriptors
- `molfeat[map4]` - MAP4 fingerprints
## Core Concepts
…