.claude/skills/signal_processing/SKILL.md
Signal Processing Analysis - Analyze signals: duty cycle, frequency range, electron wavelength, and measurement error analysis. Use this skill for signal processing tasks involving calculate duty cycle calculate frequency range electron wavelength calculate absolute error. Combines 4 tools from 3 SCP server(s).
npx skillsauth add SpectrAI-Initiative/InnoClaw signal_processingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Discipline: Signal Processing | Tools Used: 4 | Servers: 3
Analyze signals: duty cycle, frequency range, electron wavelength, and measurement error analysis.
calculate_duty_cycle from server-21 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/21/Electrical_Engineering_and_Circuit_Calculationscalculate_frequency_range from server-23 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/23/Optics_and_Electromagneticselectron_wavelength from server-23 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/23/Optics_and_Electromagneticscalculate_absolute_error from server-26 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis{
"pulse_width": 0.005,
"period": 0.02
}
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-23": "https://scp.intern-ai.org.cn/api/v1/mcp/23/Optics_and_Electromagnetics",
"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-23"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/23/Optics_and_Electromagnetics", 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 duty cycle
result_1 = await sessions["server-21"].call_tool("calculate_duty_cycle", arguments={})
data_1 = parse(result_1)
print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")
# Step 2: Calculate frequency range
result_2 = await sessions["server-23"].call_tool("calculate_frequency_range", arguments={})
data_2 = parse(result_2)
print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")
# Step 3: Compute electron wavelength
result_3 = await sessions["server-23"].call_tool("electron_wavelength", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Analyze measurement error
result_4 = await sessions["server-26"].call_tool("calculate_absolute_error", 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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