---
name: mage-antibody-generator
source: https://app.decimal.ai/s/mage-antibody-generator@2/SKILL.md
source_sha256: b4c9f316d088
---

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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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