# Mage Antibody Generator

> Ab seq forge

- Skill: `fridrichmethod/mage-antibody-generator` (Agent Skill, multi-file: 37 files)
- Install (CLI): `npx skillmds@latest add fridrichmethod/mage-antibody-generator`
- Raw SKILL.md: https://api.skillmd.com/api/skills/fridrichmethod/mage-antibody-generator/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- License: MIT
- Author: FridrichMethod (https://skillmd.com/u/fridrichmethod)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/fridrichmethod/mage-antibody-generator

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# 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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