Charge Carrier Mobility Analysis

SkillProductivity

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).

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Charge Carrier Mobility Analysis skill

What this skill tells your AI

The instructions your AI receives, as published by internscience/scp in skills/mobility_analysis/SKILL.md and read by ahel’s review.

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

{
    "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.

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())

Signals

GitHub stars
167
Forks
9
Last commit
Jun 2026
Advanced
Catalog kind
skill
Gateway key
mobility-analysis-internscience
Source
github.com/internscience/scp