Charge Carrier Mobility Analysis
SkillProductivityCharge 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.
No other account needed.
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 spectrai-initiative/innoclaw in .claude/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_mobilityfromserver-21(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/21/Electrical_Engineering_and_Circuit_Calculationscalculate_vacuum_permittivityfromserver-21(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/21/Electrical_Engineering_and_Circuit_Calculationscalculate_absolute_errorfromserver-26(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysiscalculate_mean_squarefromserver-26(streamable-http) -https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis
Workflow
- Calculate new mobility
- Compute vacuum permittivity
- Calculate measurement error
- Compute mean square statistics
Test Case
Input
{
"mobility_data": [
1500,
1450,
1520
]
}
Expected Steps
- Calculate new mobility
- Compute vacuum permittivity
- Calculate measurement error
- Compute mean square statistics
Usage Example
Note: Replace
sk-b04409a1-b32b-4511-9aeb-22980abdc05cwith your own SCP Hub API Key. You can obtain one from the SCP Platform.
import asyncio
import json
from contextlib import AsyncExitStack
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, stack):
transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "sk-b04409a1-b32b-4511-9aeb-22980abdc05c"})
read, write, _ = await stack.enter_async_context(transport)
ctx = ClientSession(read, write)
session = await stack.enter_async_context(ctx)
await session.initialize()
return session
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():
async with AsyncExitStack() as stack:
# 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", stack)
sessions["server-26"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis", stack)
# 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
- 391
- Forks
- 28
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
mobility-analysis-spectrai-initiative- Source
- github.com/spectrai-initiative/innoclaw