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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; designing novel proteins; generating protein embeddings; performing inverse folding; or conducting protein engineering tasks. Supports both local model usage and cloud-based Forge API for scalable inference.

K-Dense-AI

Core Features

Ready to Use

Quick integration into your workflow with minimal setup

Community Verified

Active open-source community with continuous updates

Completely Free

MIT/Apache licensed for commercial and personal use

Flexible Extension

Customizable and extendable based on your needs

How to Use

1Get Skill File

Download or copy the skill file from the source repository

2Install to Claude

Place the skill file in Claude's skills directory (usually ~/.claude/skills/)。

3Start Using

Restart Claude or run the reload command to load the skill

Tip: Read the documentation and code carefully before first use to understand functionality and permission requirements

Related Tags

#ai-ml#authentication#documentation#git#python#testing

Technical Information

Author
K-Dense-AI
Category
Development
File Size
10.25 KB
Source Repository
K-Dense-AI__claude-scientific-skills
Metadata
Includes YAML metadata
License
MIT

All Skills from open-source community, preserving original authors' copyrights

K-Dense-AI__claude-scientific-skills/scientific-skills/esm/skill.md

Why Choose This Skill

Proven benefits and measurable impact

50%

Faster feedback cycle

Reduce code review time by automating initial quality checks

80%

Fewer post-deployment bugs

Catch issues early to minimize emergency fixes and hotfixes

3x

Increased review coverage

Review more code thoroughly without expanding human resources

Use Cases

Perfect for these scenarios

🔍

Pre-commit validation

Ensure code meets requirements before committing to repository

📋

Feature completion check

Verify implementation aligns with original feature specifications

🚀

Pre-deployment review

Identify potential issues before deploying to production environment

👥

Team collaboration aid

Standardize review process across distributed development teams

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