Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/InternScience/MolClaw --skill molclaw-denovo-sampling명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
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All tools utilized within MolClaw skills connect via the MCP protocol. This skill is the unified guide for connecting to the deployed MCP server before invoking tools.
Formats extracted execution patterns into standard MolClaw skill documents. Accepts structured input from the Skill Crystallization Meta-Workflow (L2-12) and outputs a properly formatted L1 or L2 skill document conforming to MolClaw conventions. This skill ensures that auto-generated skills are structurally identical to expert-curated skills, enabling seamless integration into the skill matching and loading pipeline.
Predict the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of the input molecules.
SKILL.md 표시 중
SOC 직업 분류 기준
| name | molclaw-denovo-sampling |
| description | Generate new molecules de novo. |
| license | MIT license |
| metadata | {"skill-author":"PJLab"} |
Note:
molclaw-file-transfer before execution.molclaw-pdbfixer before execution.molclaw-scp-server to complete tool invocation.The description of tool reinvent_denovo_sampling.
Generate new molecules de novo.
Args:
n (int): Number of molecules for sampling
lipinski (bool): Required flag controlling Lipinski filtering (commonly True)
filter_preset (str): Required filter preset; options: ['none', 'minimal', 'default', 'strict', 'druglike', 'all'] (commonly 'druglike')
Return:
status (str): success/error
msg (str): message
save_smiles_file (str): Path to the saved SMILES file
output_smiles_list (List[str]): List of generated SMILES strings
How to use tool reinvent_denovo_sampling :
response = await client.session.call_tool(
"reinvent_denovo_sampling",
arguments={
"n": n,
"lipinski": True,
"filter_preset": filter_type
}
)
result = client.parse_result(response)
output_smiles_list = result["output_smiles_list"]