mobility_analysis
$
npx mdskill add InternScience/scp/mobility_analysisAnalyzes charge carrier mobility and computes related physical and statistical values
- Solves semiconductor physics tasks involving mobility and error analysis
- Uses four tools from two SCP servers for mobility, permittivity, and statistical calculations
- Processes input data to calculate new mobility, vacuum permittivity, absolute error, and mean square
- Returns computed results in structured JSON format for further analysis or reporting
SKILL.md
.github/skills/mobility_analysisView on GitHub ↗
---
name: mobility_analysis
description: "Charge Carrier Mobility Analysis - Analyze carrier mobility: calculate new mobility, compute vacuum permittivity, and error analysis. Use this skill for semiconductor physics tasks involving calculate new mobility calculate vacuum permittivity calculate absolute error calculate mean square. Combines 4 tools from 2 SCP server(s)."
---
# Charge Carrier Mobility Analysis
**Discipline**: Semiconductor Physics | **Tools Used**: 4 | **Servers**: 2
## Description
Analyze carrier mobility: calculate new mobility, compute vacuum permittivity, and error analysis.
## Tools Used
- **`calculate_new_mobility`** from `server-21` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/21/Electrical_Engineering_and_Circuit_Calculations`
- **`calculate_vacuum_permittivity`** from `server-21` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/21/Electrical_Engineering_and_Circuit_Calculations`
- **`calculate_absolute_error`** from `server-26` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis`
- **`calculate_mean_square`** from `server-26` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis`
## Workflow
1. Calculate new mobility
2. Compute vacuum permittivity
3. Calculate measurement error
4. Compute mean square statistics
## Test Case
### Input
```json
{
"mobility_data": [
1500,
1450,
1520
]
}
```
### Expected Steps
1. Calculate new mobility
2. Compute vacuum permittivity
3. Calculate measurement error
4. Compute mean square statistics
## 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-21": "https://scp.intern-ai.org.cn/api/v1/mcp/21/Electrical_Engineering_and_Circuit_Calculations",
"server-26": "https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis"
}
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-21"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/21/Electrical_Engineering_and_Circuit_Calculations", "streamable-http")
sessions["server-26"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis", "streamable-http")
# Execute workflow steps
# Step 1: Calculate new mobility
result_1 = await sessions["server-21"].call_tool("calculate_new_mobility", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Compute vacuum permittivity
result_2 = await sessions["server-21"].call_tool("calculate_vacuum_permittivity", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Calculate measurement error
result_3 = await sessions["server-26"].call_tool("calculate_absolute_error", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Compute mean square statistics
result_4 = await sessions["server-26"].call_tool("calculate_mean_square", 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())
```