drclaw/agent_hub/templates/chemistry/skills/chemical-structure-analysis/SKILL.md
Analyze chemical structures from compound names to retrieve SMILES, molecular formulas, molecular weight, and LogP values.
npx skillsauth add qzzqzzb/drclaw chemical-structure-analysisInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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import asyncio
import json
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
class InternAgentClient:
"""InternAgent MCP Client"""
def __init__(self, server_url: str, api_key: str):
self.server_url = server_url
self.api_key = api_key
self.session = None
async def connect(self):
try:
self.transport = streamablehttp_client(
url=self.server_url,
headers={"SCP-HUB-API-KEY": self.api_key}
)
self.read, self.write, self.get_session_id = await self.transport.__aenter__()
self.session_ctx = ClientSession(self.read, self.write)
self.session = await self.session_ctx.__aenter__()
await self.session.initialize()
return True
except Exception as e:
print(f"✗ connect failure: {e}")
return False
async def disconnect(self):
try:
if self.session:
await self.session_ctx.__aexit__(None, None, None)
if hasattr(self, 'transport'):
await self.transport.__aexit__(None, None, None)
except Exception as e:
print(f"✗ disconnect error: {e}")
def parse_result(self, result):
try:
if hasattr(result, 'content') and result.content:
content = result.content[0]
if hasattr(content, 'text'):
return json.loads(content.text)
return str(result)
except Exception as e:
return {"error": f"parse error: {e}", "raw": str(result)}
Analyze chemical structures from compound names.
Implementation:
## Initialize client
client = InternAgentClient(
"https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent",
"<your-api-key>"
)
if not await client.connect():
print("connection failed")
exit()
## Input: Compound name
compound_name = "aspirin"
## Analyze chemical structure
result = await client.session.call_tool(
"ChemicalStructureAnalyzer",
arguments={
"compound_name": compound_name
}
)
data = client.parse_result(result)
print(f"Compound: {compound_name}")
print(f"SMILES: {data.get('smiles', 'N/A')}")
print(f"Molecular Formula: {data.get('molecular_formula', 'N/A')}")
print(f"Molecular Weight: {data.get('molecular_weight', 'N/A')}")
print(f"LogP: {data.get('logP', 'N/A')}")
await client.disconnect()
InternAgent Server:
ChemicalStructureAnalyzer: Analyze chemical structure from compound name
compound_name (str): Chemical compound namesmiles (str): SMILES notationmolecular_formula (str): Chemical formulamolecular_weight (float): Molecular weight (g/mol)logP (float): Partition coefficientcontent-media
当用户明确要求“写/生成 NSFC 预算说明书”“写预算说明”“生成 budget.tex / budget.pdf”“写国自然预算 justification”时使用。基于用户标书正文或补充材料,输出一份可提交的预算说明书 LaTeX 项目并渲染 `budget.pdf`。若用户未指定工作目录,必须暂停并先要求其指定。⚠️ 不适用:用户只是想了解预算原则;用户仅要预算表数字而不写说明书;或用户是 2026 青年 A/B/C 默认包干制且无需预算说明书的场景。
tools
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documentation
当用户明确要求"更新项目指南""同步指南""沉淀洞见到指南"时使用。将对话中新产生的可复用写作洞见实时沉淀到项目指南文件,保持术语口径一致、结构稳定、可检验与可复现。调用时必须指定指南文件路径。
content-media
当用户明确要求"从文件/图片/网页/描述中提取综述主题"或"生成主题+关键词+核心问题结构化输出"时使用。支持文件(PDF/Word/Markdown/Tex)、文件夹、图片、自然语言描述、网页 URL 等多种输入源,自动识别输入类型并提取内容,生成可直接用于 systematic-literature-review 及其他文献综述技能的结构化输出。