signal_processing

$npx mdskill add InternScience/scp/signal_processing

Analyzes signals for duty cycle, frequency range, electron wavelength, and error

  • Solves signal analysis tasks involving duty cycle, frequency, wavelength, and error
  • Uses 4 tools from 3 SCP servers for signal processing calculations
  • Processes input parameters to determine required signal properties
  • Returns calculated results in a structured JSON format
SKILL.md
.github/skills/signal_processingView on GitHub ↗
---
name: signal_processing
description: "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)."
---

# Signal Processing Analysis

**Discipline**: Signal Processing | **Tools Used**: 4 | **Servers**: 3

## Description

Analyze signals: duty cycle, frequency range, electron wavelength, and measurement error analysis.

## Tools Used

- **`calculate_duty_cycle`** from `server-21` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/21/Electrical_Engineering_and_Circuit_Calculations`
- **`calculate_frequency_range`** from `server-23` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/23/Optics_and_Electromagnetics`
- **`electron_wavelength`** from `server-23` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/23/Optics_and_Electromagnetics`
- **`calculate_absolute_error`** from `server-26` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/26/Data_processing_and_statistical_analysis`

## Workflow

1. Calculate duty cycle
2. Calculate frequency range
3. Compute electron wavelength
4. Analyze measurement error

## Test Case

### Input
```json
{
    "pulse_width": 0.005,
    "period": 0.02
}
```

### Expected Steps
1. Calculate duty cycle
2. Calculate frequency range
3. Compute electron wavelength
4. Analyze measurement error

## 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-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, 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-23"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/23/Optics_and_Electromagnetics", "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 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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