mage-antibody-generator
SkillDev toolsRun the MAGE antibody generation workflow to propose antigen-conditioned antibody sequences for downstream structural validation.
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Details
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About this skill
The largest open-source medical AI skills library for OpenClaw🦞.
What this skill tells your AI
The instructions your AI receives, as published by freedomintelligence/openclaw-medical-skills in skills/mage-antibody-generator/SKILL.md and read by Ahel’s review.
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
- Prep env:
cd repoand install dependencies, then point to GPU if available. - Run generator:
python generate_antibodies.py --antigen_sequence <SEQ> --num_candidates N --output_dir ./results. - Collect outputs: Provide FASTA paths + metadata, optionally translate into JSON manifest.
- 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.mdand repo scripts.
Signals
- GitHub stars
- 3k
- Forks
- 412
- Last commit
- Jul 2026
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- Item type
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- Key
mage-antibody-generator- Source
- github.com/freedomintelligence/openclaw-medical-skills
github.com/freedomintelligence/openclaw-medical-skills