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MAGE

Skill FridrichMethod/awesome-skills/skills/antibody-design-agent/MAGE

Ab seq forgeFrom its SKILL.md

Install
npx -y skills add FridrichMethod/awesome-skills --skill MAGE

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 13 stars13 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

1.7 KB, 305 tokens by cl100k_base, as published. Nobody here has run it

<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <[email protected]> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA -->

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.
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

What ships with it: 36 files

7065.6 KB alongside SKILL.md, 2 of them executable

repo/

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.