esm-protein-language-model
Protein language models (ESM3, ESM C) for sequence generation, structure prediction, inverse folding, and embeddings. Design novel proteins, extract ML features, or fold sequences. Local GPU or EvolutionaryScale Forge API. Use AlphaFold for traditional folding; RDKit for small molecules.
npx skills add BioTender-max/awesome-bio-agent-skills --skill esm-protein-language-model --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# ESM — Protein Language Models ## Overview ESM (Evolutionary Scale Modeling) provides pretrained protein language models for generative protein design and representation learning. ESM3 is a multimodal generative model conditioned on sequence, structure, and function simultaneously. ESM C is an efficient embedding model optimized for extracting protein representations for downstream ML tasks. ## When to Use - Generating novel protein sequences conditioned on desired structure or function - Extracting fixed-length embeddings from protein sequences for classification, clustering, or regression - Predicting 3D structure from amino acid sequence - Inverse folding: designing sequences that fold into a target structure - Annotating proteins with functional keywords (GO terms, EC numbers) - Comparing protein similarity via embedding distance instead of sequence alignment - Chain-of-thought protein design: iterative refinement of sequence/structure/function - For **traditional physics-based structure prediction**, use AlphaFold instead - For **sequence alignment and homology search**, use BLAST/HMMER via BioPython instead ## Prerequisites - **Python packages**: `esm` (EvolutionaryScale pac
- Overview
- When to Use
- Prerequisites
- Quick Start
- Core API
- 1. Protein Sequence Generation (ESM3)
- 2. Protein Embeddings (ESM C)
- 3. Structure Prediction
- 4. Inverse Folding
- 5. Function Conditioning
- 6. Forge Cloud API
- Key Concepts
- ESM3 vs ESM C: When to Use Which
- GenerationConfig Parameters
pip install esm For Forge cloud API pip install esm[forge]
What does the esm-protein-language-model skill do?
Protein language models (ESM3, ESM C) for sequence generation, structure prediction, inverse folding, and embeddings. Design novel proteins, extract ML features, or fold sequences. Local GPU or EvolutionaryScale Forge API. Use AlphaFold for traditional folding; RDKit for small molecules.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill esm-protein-language-model --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.