用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/InternScience/Agents-A1 --skill molclaw-compound-retrieve命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
Predict the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of the input molecules.
Predict binding affinity between target protein sequence and small molecule SMILES using Boltz-2.
Predict protein structures with Chai-1 from sequence or FASTA input and return model scoring summaries.
基于 SOC 职业分类
正在显示 SKILL.md
| name | molclaw-compound-retrieve |
| description | Retrieve SMILES strings from PubChem database using compound names. |
| license | MIT license |
| metadata | {"skill-author":"PJLab"} |
The description of tool retrieve_smiles_by_compoundname.
Retrieve SMILES strings from PubChem using compound names.
Args:
compound_names (List[str]): List of input compound names (e.g., ["aspirin", "caffeine"])
Return:
status (str): success/partial_success/error
msg (str): message
retrieve_smiles (List[dict]): List of dict, each containing the keys 'compound_name' and 'smiles'.
--compound_name (str): A compound name of compound_names
--smiles (str): The retrieved SMILES string, if it exists; otherwise, None.
How to use tool retrieve_smiles_by_compoundname :
response = await client.session.call_tool(
"retrieve_smiles_by_compoundname",
arguments={
"compound_names": compound_names
}
)
result = client.parse_result(response)
retrieve_smiles = result["retrieve_smiles"]