[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DJ4VVCG8MDJC7S1D8K3WZX":3,"skill-same:01M6DJ4VVCG8MDJC7S1D8K3WZX":100},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":32,"linkOnly":33,"markdownContent":34,"markdownBody":35,"frontMatter":36,"refName":40,"commitSha":41,"skillDirectory":42,"forksCount":43,"repositoryHtmlUrl":44,"repositoryHomepageUrl":6,"ownerHtmlUrl":45,"ownerBlogUrl":6,"ownerDescription":46,"updatedAt":47,"install":48,"resources":61},"01M6DJ4VVCG8MDJC7S1D8K3WZX","compound-name-retrieval",null,"Retrieve SMILES strings from PubChem database using compound names to obtain molecular structures from common chemical names.","InternScience\u002FDrClaw","InternScience","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F154449623?v=4","01M6DHY1ZF02QASNAVMNPT7NP6","Intern Science","01M6DHY2523FY56Q5572NKAAD0",172,"MIT","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Fagent_hub\u002Ftemplates\u002Fchemistry\u002Fskills\u002Fcompound-name-retrieval\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31],"compound","name","compound name retrieval","database","pubchem database","common","chemical","molecular","2026-11-10 10:12:30",false,"---\nname: compound-name-retrieval\ndescription: Retrieve SMILES strings from PubChem database using compound names to obtain molecular structures from common chemical names.\nlicense: MIT license\nmetadata:\n    skill-author: PJLab\n---\n\n# Compound Name to SMILES Retrieval\n\n## Usage\n\n### 1. MCP Server Definition\n\n```python\nimport asyncio\nimport json\nfrom mcp.client.streamable_http import streamablehttp_client\nfrom mcp import ClientSession\n\nclass DrugSDAClient:\n    \"\"\"DrugSDA-Tool MCP Client\"\"\"\n\n    def __init__(self, server_url: str, api_key: str):\n        self.server_url = server_url\n        self.api_key = api_key\n        self.session = None\n\n    async def connect(self):\n        \"\"\"Establish connection and initialize session\"\"\"\n        try:\n            self.transport = streamablehttp_client(\n                url=self.server_url,\n                headers={\"SCP-HUB-API-KEY\": self.api_key}\n            )\n            self.read, self.write, self.get_session_id = await self.transport.__aenter__()\n            self.session_ctx = ClientSession(self.read, self.write)\n            self.session = await self.session_ctx.__aenter__()\n            await self.session.initialize()\n            return True\n        except Exception as e:\n            print(f\"✗ connect failure: {e}\")\n            return False\n\n    async def disconnect(self):\n        \"\"\"Disconnect from server\"\"\"\n        try:\n            if self.session:\n                await self.session_ctx.__aexit__(None, None, None)\n            if hasattr(self, 'transport'):\n                await self.transport.__aexit__(None, None, None)\n        except Exception as e:\n            print(f\"✗ disconnect error: {e}\")\n\n    def parse_result(self, result):\n        \"\"\"Parse MCP tool call result\"\"\"\n        try:\n            if hasattr(result, 'content') and result.content:\n                content = result.content[0]\n                if hasattr(content, 'text'):\n                    return json.loads(content.text)\n            return str(result)\n        except Exception as e:\n            return {\"error\": f\"parse error: {e}\", \"raw\": str(result)}\n```\n\n### 2. Compound Name Retrieval Workflow\n\nThis workflow retrieves SMILES strings from PubChem using common chemical names.\n\n**Workflow Steps:**\n\n1. **Input Compound Names** - Provide list of chemical names\n2. **Query PubChem** - Search for each compound in PubChem database\n3. **Extract SMILES** - Retrieve canonical SMILES representations\n\n**Implementation:**\n\n```python\n## Initialize client\nclient = DrugSDAClient(\n    \"https:\u002F\u002Fscp.intern-ai.org.cn\u002Fapi\u002Fv1\u002Fmcp\u002F2\u002FDrugSDA-Tool\",\n    \"\u003Cyour-api-key>\"\n)\n\nif not await client.connect():\n    print(\"connection failed\")\n    exit()\n\n## Input: List of compound names\ncompound_names = [\"aspirin\", \"caffeine\", \"ibuprofen\"]\n\n## Retrieve SMILES from compound names\nresult = await client.session.call_tool(\n    \"retrieve_smiles_from_name\",\n    arguments={\n        \"compound_names\": compound_names\n    }\n)\n\nresult_data = client.parse_result(result)\nsmiles_list = result_data[\"retrieve_smiles\"]\n\n## Display results\nprint(\"Retrieved SMILES strings:\")\nfor item in smiles_list:\n    print(f\"Name: {item['compound_name']}\")\n    print(f\"SMILES: {item['smiles']}\\n\")\n\nawait client.disconnect()\n```\n\n### Tool Descriptions\n\n**DrugSDA-Tool Server:**\n- `retrieve_smiles_from_name`: Retrieve SMILES from PubChem by compound name\n  - Args:\n    - `compound_names` (list): List of chemical compound names\n  - Returns:\n    - `retrieve_smiles` (list): List of name-SMILES pairs\n      - `compound_name` (str): Input compound name\n      - `smiles` (str): Canonical SMILES string\n\n### Input\u002FOutput\n\n**Input:**\n- `compound_names`: List of chemical names (common names, IUPAC names, or synonyms)\n\n**Output:**\n- List of results:\n  - `compound_name`: Query compound name\n  - `smiles`: Canonical SMILES representation\n\n### Use Cases\n\n- Convert chemical names to machine-readable formats\n- Batch retrieve molecular structures\n- Validate compound names against PubChem\n- Prepare datasets for computational chemistry\n- Integration with molecular analysis pipelines\n\n### Performance Notes\n\n- **Data source**: PubChem public database\n- **Name matching**: Supports common names, IUPAC names, and synonyms\n- **Execution time**: ~1-2 seconds per compound\n- **Availability**: Requires internet connection to PubChem API\n","# Compound Name to SMILES Retrieval\n\n## Usage\n\n### 1. MCP Server Definition\n\n```python\nimport asyncio\nimport json\nfrom mcp.client.streamable_http import streamablehttp_client\nfrom mcp import ClientSession\n\nclass DrugSDAClient:\n    \"\"\"DrugSDA-Tool MCP Client\"\"\"\n\n    def __init__(self, server_url: str, api_key: str):\n        self.server_url = server_url\n        self.api_key = api_key\n        self.session = None\n\n    async def connect(self):\n        \"\"\"Establish connection and initialize session\"\"\"\n        try:\n            self.transport = streamablehttp_client(\n                url=self.server_url,\n                headers={\"SCP-HUB-API-KEY\": self.api_key}\n            )\n            self.read, self.write, self.get_session_id = await self.transport.__aenter__()\n            self.session_ctx = ClientSession(self.read, self.write)\n            self.session = await self.session_ctx.__aenter__()\n            await self.session.initialize()\n            return True\n        except Exception as e:\n            print(f\"✗ connect failure: {e}\")\n            return False\n\n    async def disconnect(self):\n        \"\"\"Disconnect from server\"\"\"\n        try:\n            if self.session:\n                await self.session_ctx.__aexit__(None, None, None)\n            if hasattr(self, 'transport'):\n                await self.transport.__aexit__(None, None, None)\n        except Exception as e:\n            print(f\"✗ disconnect error: {e}\")\n\n    def parse_result(self, result):\n        \"\"\"Parse MCP tool call result\"\"\"\n        try:\n            if hasattr(result, 'content') and result.content:\n                content = result.content[0]\n                if hasattr(content, 'text'):\n                    return json.loads(content.text)\n            return str(result)\n        except Exception as e:\n            return {\"error\": f\"parse error: {e}\", \"raw\": str(result)}\n```\n\n### 2. Compound Name Retrieval Workflow\n\nThis workflow retrieves SMILES strings from PubChem using common chemical names.\n\n**Workflow Steps:**\n\n1. **Input Compound Names** - Provide list of chemical names\n2. **Query PubChem** - Search for each compound in PubChem database\n3. **Extract SMILES** - Retrieve canonical SMILES representations\n\n**Implementation:**\n\n```python\n## Initialize client\nclient = DrugSDAClient(\n    \"https:\u002F\u002Fscp.intern-ai.org.cn\u002Fapi\u002Fv1\u002Fmcp\u002F2\u002FDrugSDA-Tool\",\n    \"\u003Cyour-api-key>\"\n)\n\nif not await client.connect():\n    print(\"connection failed\")\n    exit()\n\n## Input: List of compound names\ncompound_names = [\"aspirin\", \"caffeine\", \"ibuprofen\"]\n\n## Retrieve SMILES from compound names\nresult = await client.session.call_tool(\n    \"retrieve_smiles_from_name\",\n    arguments={\n        \"compound_names\": compound_names\n    }\n)\n\nresult_data = client.parse_result(result)\nsmiles_list = result_data[\"retrieve_smiles\"]\n\n## Display results\nprint(\"Retrieved SMILES strings:\")\nfor item in smiles_list:\n    print(f\"Name: {item['compound_name']}\")\n    print(f\"SMILES: {item['smiles']}\\n\")\n\nawait client.disconnect()\n```\n\n### Tool Descriptions\n\n**DrugSDA-Tool Server:**\n- `retrieve_smiles_from_name`: Retrieve SMILES from PubChem by compound name\n  - Args:\n    - `compound_names` (list): List of chemical compound names\n  - Returns:\n    - `retrieve_smiles` (list): List of name-SMILES pairs\n      - `compound_name` (str): Input compound name\n      - `smiles` (str): Canonical SMILES string\n\n### Input\u002FOutput\n\n**Input:**\n- `compound_names`: List of chemical names (common names, IUPAC names, or synonyms)\n\n**Output:**\n- List of results:\n  - `compound_name`: Query compound name\n  - `smiles`: Canonical SMILES representation\n\n### Use Cases\n\n- Convert chemical names to machine-readable formats\n- Batch retrieve molecular structures\n- Validate compound names against PubChem\n- Prepare datasets for computational chemistry\n- Integration with molecular analysis pipelines\n\n### Performance Notes\n\n- **Data source**: PubChem public database\n- **Name matching**: Supports common names, IUPAC names, and synonyms\n- **Execution time**: ~1-2 seconds per compound\n- **Availability**: Requires internet connection to PubChem API\n",{"name":5,"license":37,"metadata":38,"description":7},"MIT license",{"skill-author":39},"PJLab","main","4f96df0d9df0eae24a992afabe08edec5fc575f0","drclaw\u002Fagent_hub\u002Ftemplates\u002Fchemistry\u002Fskills\u002Fcompound-name-retrieval",10,"https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw","https:\u002F\u002Fgithub.com\u002FInternScience","Shanghai Artificial Intelligence Laboratory","2026-03-20 17:06:10",{"source":8,"skillName":5,"commands":49,"prompt":59,"zipAvailable":60},[50,53,56],{"tool":51,"command":52},"npx","npx skills add InternScience\u002FDrClaw --skill compound-name-retrieval",{"tool":54,"command":55},"bunx","bunx skills add InternScience\u002FDrClaw --skill compound-name-retrieval",{"tool":57,"command":58},"pnpm","pnpm dlx skills add InternScience\u002FDrClaw --skill compound-name-retrieval","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Fagent_hub\u002Ftemplates\u002Fchemistry\u002Fskills\u002Fcompound-name-retrieval\u002FSKILL.md",true,[62,68,72,76,82,86,90,94],{"path":63,"resourceType":64,"resourceTypeDesc":65,"sizeBytes":66,"sourceHtmlUrl":67},"assets\u002Ftemplates\u002Fprocedures\u002FCAPA-procedure-template.md","ASSET","资产文件",15055,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fscience-research-data-analysis\u002Flatest-release-community\u002Fiso-13485-certification\u002Fassets\u002Ftemplates\u002Fprocedures\u002FCAPA-procedure-template.md",{"path":69,"resourceType":64,"resourceTypeDesc":65,"sizeBytes":70,"sourceHtmlUrl":71},"assets\u002Ftemplates\u002Fprocedures\u002Fdocument-control-procedure-template.md",18062,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fscience-research-data-analysis\u002Flatest-release-community\u002Fiso-13485-certification\u002Fassets\u002Ftemplates\u002Fprocedures\u002Fdocument-control-procedure-template.md",{"path":73,"resourceType":64,"resourceTypeDesc":65,"sizeBytes":74,"sourceHtmlUrl":75},"assets\u002Ftemplates\u002Fquality-manual-template.md",20618,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fscience-research-data-analysis\u002Flatest-release-community\u002Fiso-13485-certification\u002Fassets\u002Ftemplates\u002Fquality-manual-template.md",{"path":77,"resourceType":78,"resourceTypeDesc":79,"sizeBytes":80,"sourceHtmlUrl":81},"references\u002Fgap-analysis-checklist.md","REFERENCE","参考文档",27586,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fscience-research-data-analysis\u002Flatest-release-community\u002Fiso-13485-certification\u002Freferences\u002Fgap-analysis-checklist.md",{"path":83,"resourceType":78,"resourceTypeDesc":79,"sizeBytes":84,"sourceHtmlUrl":85},"references\u002Fiso-13485-requirements.md",25697,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fscience-research-data-analysis\u002Flatest-release-community\u002Fiso-13485-certification\u002Freferences\u002Fiso-13485-requirements.md",{"path":87,"resourceType":78,"resourceTypeDesc":79,"sizeBytes":88,"sourceHtmlUrl":89},"references\u002Fmandatory-documents.md",21428,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fscience-research-data-analysis\u002Flatest-release-community\u002Fiso-13485-certification\u002Freferences\u002Fmandatory-documents.md",{"path":91,"resourceType":78,"resourceTypeDesc":79,"sizeBytes":92,"sourceHtmlUrl":93},"references\u002Fquality-manual-guide.md",26197,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fscience-research-data-analysis\u002Flatest-release-community\u002Fiso-13485-certification\u002Freferences\u002Fquality-manual-guide.md",{"path":95,"resourceType":96,"resourceTypeDesc":97,"sizeBytes":98,"sourceHtmlUrl":99},"scripts\u002Fgap_analyzer.py","SCRIPT","脚本",15519,"https:\u002F\u002Fgithub.com\u002Fstrmt7\u002Fai_skills_collection_benchmarked\u002Fblob\u002Fmain\u002Fincluded\u002Fskills\u002Fby-category\u002Fscience-research-data-analysis\u002Flatest-release-community\u002Fiso-13485-certification\u002Fscripts\u002Fgap_analyzer.py",[101,136,159,175,192,207],{"skillNo":102,"name":103,"nameZh":6,"description":104,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":105,"categories":106,"keywords":115,"publishedAt":32},"01M6DMQESTSBW8VJW03QWHMT85","scientific-critical-thinking","Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fthinking\u002Fscientific-critical-thinking\u002FSKILL.md",[107,110],{"categoryNo":108,"categoryName":109,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":111,"categoryName":112,"taxonomyType":113,"taxonomyTypeDesc":114},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135],"critical","scientific critical thinking","thinking","design","writing","review","risk","analysis","peer review","Bash","quality","read","write","edit","use","evidence","peer","frameworks","teaching","bias",{"skillNo":137,"name":138,"nameZh":6,"description":139,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":140,"categories":141,"keywords":142,"publishedAt":32},"01M6DMQ77Z121463E049G2DG8K","scientific-brainstorming","Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fthinking\u002Fscientific-brainstorming\u002FSKILL.md",[],[143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,130],"brainstorming","scientific brainstorming","research ideation","stage","connections","generation","exploration","do","planning","creative","ideation","research","sessions","data","hypothesis","open",{"skillNo":160,"name":161,"nameZh":6,"description":162,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":163,"categories":164,"keywords":169,"publishedAt":32},"01M6DMPV4AMCCTWARGPSFHDWJB","scientific-literature-search","Search scientific literature and research papers using FlowSearch to find relevant academic articles and publications.","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fsearch\u002Fscientific-literature-search\u002FSKILL.md",[165,168],{"categoryNo":166,"categoryName":167,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[170,171,154,172,173,174],"search","scientific literature search","find","Academic","搜索",{"skillNo":176,"name":177,"nameZh":6,"description":178,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":179,"categories":180,"keywords":187,"publishedAt":32},"01M6DMPQJP8HVFV54V05D6K9HA","pubmed-article-search","Search PubMed database for scientific articles and publications to retrieve biomedical literature.","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fsearch\u002Fpubmed-article-search\u002FSKILL.md",[181,184],{"categoryNo":182,"categoryName":183,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":185,"categoryName":186,"taxonomyType":113,"taxonomyTypeDesc":114},"01JBSEEDCAT000000000000036","内容创作者",[188,189,170,174,27,190,191],"pubmed article search","article","pubmed database","biomedical",{"skillNo":193,"name":194,"nameZh":6,"description":195,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":196,"categories":197,"keywords":199,"publishedAt":32},"01M6DMPK4H3JQ185M97BRB9KQJ","biomedical-web-search","Search biomedical literature and web content using Tavily search engine for research and clinical information.","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fsearch\u002Fbiomedical-web-search\u002FSKILL.md",[198],{"categoryNo":166,"categoryName":167,"taxonomyType":21,"taxonomyTypeDesc":22},[200,191,201,170,202,203,154,204,205,174,206],"biomedical web search","web search","web","tavily","content","engine","clinical",{"skillNo":208,"name":209,"nameZh":6,"description":210,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":211,"categories":212,"keywords":214,"publishedAt":32},"01M6DMNNJH9V1S5PQHZRX0N934","uniprot-protein-retrieval","Retrieve protein sequences and functional information from UniProt database by protein name, enabling protein analysis and bioinformatics workflows.","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fscience\u002Fprotein\u002Funiprot-protein-retrieval\u002FSKILL.md",[213],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[215,27,123,216,217,25,218],"uniprot protein retrieval","uniprot database","bioinformatics","workflows"]