signal-processing

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).

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Repository: SpectrAI-Initiative/InnoClaw
Letzte Quellaktivität: 1. April 2026 um 17:03
Erkannte Sprache von SKILL.md: Englisch
Sterne: 390
Forks: 28

Installationsoptionen

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npx skills add https://github.com/SpectrAI-Initiative/InnoClaw --skill signal-processing

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SKILL.md

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innoclaw-cli

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paper-q-a

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Alle aus diesem Repository ansehen

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

Calculate duty cycle
Calculate frequency range
Compute electron wavelength
Analyze measurement error

Test Case

Input

{
    "pulse_width"

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())

signal-processing

Installationsoptionen

Quelldateien prüfen

Signal Processing Analysis

Description

Tools Used

Workflow

Test Case

Input

Signal Processing Analysis

Description

Tools Used

Workflow

Test Case

Input

Expected Steps

Usage Example

signal-processing

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Mehr aus diesem Repository

Mehr aus diesem Repository

Signal Processing Analysis

Description

Tools Used

Workflow

Test Case

Input

Signal Processing Analysis

Description

Tools Used

Workflow

Test Case

Input

Expected Steps

Usage Example