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Install with the open skills CLI (global, non-interactive — available in every Claude Code session):
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill "mage-antibody-generator" -g -a claude-code -yOr manually — clone and copy the skill directory (SKILL.md + companion files):
git clone --depth 1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills /tmp/OpenClaw-Medical-Skills && cp -r /tmp/OpenClaw-Medical-Skills/skills/mage-antibody-generator ~/.claude/skills/mage-antibody-generatorThis skill is a directory: SKILL.md is the entry point; the files below ship with it.
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# COPYRIGHT NOTICE
# This file is part of the "Universal Biomedical Skills" project.
# Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>
# All Rights Reserved.
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# This code is proprietary and confidential.
# Unauthorized copying of this file, via any medium is strictly prohibited.
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---
name: mage-antibody-generator
description: Ab seq forge
keywords:
- antibody
- antigen
- FASTA
- generation
- validation
measurable_outcome: Generate the requested number of antibody sequences (default ≥5) with metadata (model checkpoint, seed) and deliver FASTA files within 10 minutes.
license: MIT
metadata:
author: MAGE Team
version: "1.0.0"
compatibility:
- system: Python 3.9+ / GPU
allowed-tools:
- run_shell_command
- read_file
---
# MAGE (Monoclonal Antibody Generator)
Run the MAGE antibody generation workflow to propose antigen-conditioned antibody sequences for downstream structural validation.
## Workflow
1. **Prep env:** `cd repo` and install dependencies, then point to GPU if available.
2. **Run generator:** `python generate_antibodies.py --antigen_sequence <SEQ> --num_candidates N --output_dir ./results`.
3. **Collect outputs:** Provide FASTA paths + metadata, optionally translate into JSON manifest.
4. **Recommend validation:** Suggest AlphaFold/Rosetta checks and wet-lab follow-up.
## Guardrails
- Never imply binding efficacy without structural/experimental confirmation.
- Track model version + seeds to ensure reproducibility.
- Encourage downstream filtering (liability motifs, developability metrics).
## References
- Source instructions in `README.md` and repo scripts.
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