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Functional Group Profiling

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'Functional Group Profiling - Profile functional groups: radical assignment,

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  • Added September 11, 2026
toolspythonapi

Works with

  • cli
  • api
  • mcp

Security analysis

A100/100

Scanned September 11, 2026

npx -y skills add InternScience/DrClaw --skill functional_group_profiling --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: functional_group_profiling
description: 'Functional Group Profiling - Profile functional groups: radical assignment,
  H-bond analysis, aromaticity, and abbreviation condensation. Use this skill for
  organic chemistry tasks involving AssignRadicals GetHBANum AromaticityAnalyzer CondenseAbbreviationSubstanceGroups.
  Combines 4 tools from 2 SCP server(s).'
i18n:
  zh:
    description: 官能团分析:自由基、氢键、芳香。
---

# Functional Group Profiling

**Discipline**: Organic Chemistry | **Tools Used**: 4 | **Servers**: 2

## Description

Profile functional groups: radical assignment, H-bond analysis, aromaticity, and abbreviation condensation.

## Tools Used

- **`AssignRadicals`** from `server-31` (sse) - `https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem`
- **`GetHBANum`** from `server-31` (sse) - `https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem`
- **`AromaticityAnalyzer`** from `server-28` (sse) - `https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent`
- **`CondenseAbbreviationSubstanceGroups`** from `server-31` (sse) - `https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem`

## Workflow

1. Assign radical sites
2. Count H-bond acceptors
3. Analyze aromaticity
4. Condense substance groups

## Test Case

### Input
```json
{
    "smiles": "CC(=O)Oc1ccccc1C(=O)O"
}
```

### Expected Steps
1. Assign radical sites
2. Count H-bond acceptors
3. Analyze aromaticity
4. Condense substance groups

## Usage Example

> **Note:** Replace `<YOUR_SCP_HUB_API_KEY>` with your own SCP Hub API Key. You can obtain one from the [SCP Platform](https://scphub.intern-ai.org.cn).

```python
import asyncio
import json
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.sse import sse_client

SERVERS = {
    "server-31": "https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem",
    "server-28": "https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent"
}

async def connect(url, transport_type):
    transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "<YOUR_SCP_HUB_API_KEY>"})
    read, write, _ = await transport.__aenter__()
    ctx = ClientSession(read, write)
    session = await ctx.__aenter__()
    await session.initialize()
    return session, ctx, transport

def parse(result):
    try:
        if hasattr(result, 'content') and result.content:
            c = result.content[0]
            if hasattr(c, 'text'):
                try: return json.loads(c.text)
                except: return c.text
        return str(result)
    except: return str(result)

async def main():
    # Connect to required servers
    sessions = {}
    sessions["server-31"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/31/SciToolAgent-Chem", "sse")
    sessions["server-28"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/28/InternAgent", "sse")

    # Execute workflow steps
    # Step 1: Assign radical sites
    result_1 = await sessions["server-31"].call_tool("AssignRadicals", arguments={})
    data_1 = parse(result_1)
    print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")

    # Step 2: Count H-bond acceptors
    result_2 = await sessions["server-31"].call_tool("GetHBANum", arguments={})
    data_2 = parse(result_2)
    print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")

    # Step 3: Analyze aromaticity
    result_3 = await sessions["server-28"].call_tool("AromaticityAnalyzer", arguments={})
    data_3 = parse(result_3)
    print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")

    # Step 4: Condense substance groups
    result_4 = await sessions["server-31"].call_tool("CondenseAbbreviationSubstanceGroups", arguments={})
    data_4 = parse(result_4)
    print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")

    # Cleanup
    print("Workflow complete!")

if __name__ == "__main__":
    asyncio.run(main())
```

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