Skill · em Dados, IA e pesquisa

esm

Comprehensive toolkit for protein language models including ESM3 (generative multimodal protein design across sequence, structure, and function) and ESM C (efficient protein embeddings and representations). Use this skill when working with protein sequences, structures, or function prediction;…

Procedência

Origem: davila7/claude-code-templates
Caminho: cli-tool/components/skills/scientific/esm
Versão fixada: 57f899e5394bb8ca166f38eacae8f0853cbfe033
Licença: MIT
Espelhado em 25/09/2026
1 download no Claude Code Templates (lido em 25/09/2026)

Antes de instalar

5 arquivos · 74,6 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/esm/.

d=".claude/skills/esm"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/esm"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/esm-c-api.md" "$u/references/esm-c-api.md" \
  -o "$d/references/esm3-api.md" "$u/references/esm3-api.md" \
  -o "$d/references/forge-api.md" "$u/references/forge-api.md" \
  -o "$d/references/workflows.md" "$u/references/workflows.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Global: instala em ~/.claude/skills/esm/.

d="$HOME/.claude/skills/esm"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/esm"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/esm-c-api.md" "$u/references/esm-c-api.md" \
  -o "$d/references/esm3-api.md" "$u/references/esm3-api.md" \
  -o "$d/references/forge-api.md" "$u/references/forge-api.md" \
  -o "$d/references/workflows.md" "$u/references/workflows.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Codex

Neste projeto: instala em .agents/skills/esm/.

d=".agents/skills/esm"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/esm"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/esm-c-api.md" "$u/references/esm-c-api.md" \
  -o "$d/references/esm3-api.md" "$u/references/esm3-api.md" \
  -o "$d/references/forge-api.md" "$u/references/forge-api.md" \
  -o "$d/references/workflows.md" "$u/references/workflows.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Global: instala em ~/.agents/skills/esm/.

d="$HOME/.agents/skills/esm"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/esm"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/esm-c-api.md" "$u/references/esm-c-api.md" \
  -o "$d/references/esm3-api.md" "$u/references/esm3-api.md" \
  -o "$d/references/forge-api.md" "$u/references/forge-api.md" \
  -o "$d/references/workflows.md" "$u/references/workflows.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Antigravity

Neste projeto: instala em .agents/skills/esm/.

d=".agents/skills/esm"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/esm"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/esm-c-api.md" "$u/references/esm-c-api.md" \
  -o "$d/references/esm3-api.md" "$u/references/esm3-api.md" \
  -o "$d/references/forge-api.md" "$u/references/forge-api.md" \
  -o "$d/references/workflows.md" "$u/references/workflows.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Global: instala em ~/.gemini/antigravity-cli/skills/esm/.

d="$HOME/.gemini/antigravity-cli/skills/esm"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/esm"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/esm-c-api.md" "$u/references/esm-c-api.md" \
  -o "$d/references/esm3-api.md" "$u/references/esm3-api.md" \
  -o "$d/references/forge-api.md" "$u/references/forge-api.md" \
  -o "$d/references/workflows.md" "$u/references/workflows.md" \
  -o "$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.esm

Prévia do SKILL.md

---
name: esm
description: Comprehensive toolkit for protein language models including ESM3 (generative multimodal protein design across sequence, structure, and function) and ESM C (efficient protein embeddings and representations). Use this skill when working with protein sequences, structures, or function prediction; designing no…
---

# ESM: Evolutionary Scale Modeling

## Overview

ESM provides state-of-the-art protein language models for understanding, generating, and designing proteins. This skill enables working with two model families: ESM3 for generative protein design across sequence, structure, and function, and ESM C for efficient protein representation learning and embeddings.

## Core Capabilities

### 1. Protein Sequence Generation with ESM3

Generate novel protein sequences with desired properties using multimodal generative modeling.

**When to use:**
- Designing proteins with specific functional properties
- Completing partial protein sequences
- Generating variants of existing proteins
- Creating proteins with desired structural characteristics

**Basic usage:**

```python
from esm.models.esm3 import ESM3
from esm.sdk.api import ESM3InferenceClient, ESMProtein, GenerationConfig

# Load model locally
model: ESM3InferenceClient = ESM3.from_pretrained("esm3-sm-open-v1").to("cuda")

# Create protein prompt
protein = ESMProtein(sequence="MPRT___KEND")  # '_' represents masked positions

# Generate completion
protein = model.generate(protein, GenerationConfig(track="sequence", num_steps=8))
print(protein.sequence)
```
…

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