MAGE
MAGE,来自 FreedomIntelligence/OpenClaw-Medical-Skills 的 agent 技能。
它会碰到什么
逐条看命中(3 条严重或高危)
- 高
repo/Fine_tuning/full_model_training_24-03-12.py:12cred-envread# os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID" # see issue #152
- 高
repo/Fine_tuning/full_model_training_24-03-12.py:13cred-envread# os.environ["CUDA_VISIBLE_DEVICES"]= '0,1,2,3'
- 高
repo/generate_antibodies.py:47exec-spawnmodel.eval()
这一栏是扫描器报的事实,不是结论。命中多不等于有毒(安全工具、规则库、示例脚本本来就会包含危险写法),命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系,需要你自己看。
技能内容
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This code is proprietary and confidential.
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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
- 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.
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->
想直接用这个技能?
本站把开放许可(MIT / Apache 等)的技能按仓库打包整理到网盘,点一下转存到你自己的网盘,不用一个个从 GitHub 拉。许可未声明的技能只给原始仓库链接,不打包。
它属于哪个仓库
skills/antibody-design-agent/MAGE/SKILL.md