drclaw/agent_hub/templates/physics/skills/optics-analysis/SKILL.md
Optical System Analysis - Analyze optical system: calculate photon rate, frequency range, radiation pressure, and electron wavelength. Use this skill for optics tasks involving calculate incident photon rate calculate frequency range calculate radiation pressure electron wavelength. Combines 4 tools from 1 SCP server(s).
npx skillsauth add qzzqzzb/drclaw optics_analysisInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Discipline: Optics | Tools Used: 4 | Servers: 1
Analyze optical system: calculate photon rate, frequency range, radiation pressure, and electron wavelength.
calculate_incident_photon_rate from server-23 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/23/Optics_and_Electromagneticscalculate_frequency_range from server-23 (streamable-http) - https://scp.intern-ai.org.cn/api/v1/mcp/23/Optics_and_Electromagneticscalculate_radiation_pressure 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_Electromagnetics{
"wavelength": 5e-07,
"power": 1.0
}
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-23": "https://scp.intern-ai.org.cn/api/v1/mcp/23/Optics_and_Electromagnetics"
}
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-23"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/23/Optics_and_Electromagnetics", "streamable-http")
# Execute workflow steps
# Step 1: Calculate incident photon rate
result_1 = await sessions["server-23"].call_tool("calculate_incident_photon_rate", 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 radiation pressure
result_3 = await sessions["server-23"].call_tool("calculate_radiation_pressure", arguments={})
data_3 = parse(result_3)
print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")
# Step 4: Calculate electron wavelength
result_4 = await sessions["server-23"].call_tool("electron_wavelength", 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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