optics_analysis
$
npx mdskill add InternScience/scp/optics_analysis**Discipline**: Optics | **Tools Used**: 4 | **Servers**: 1
SKILL.md
.github/skills/optics_analysisView on GitHub ↗
---
name: optics_analysis
description: "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)."
---
# Optical System Analysis
**Discipline**: Optics | **Tools Used**: 4 | **Servers**: 1
## Description
Analyze optical system: calculate photon rate, frequency range, radiation pressure, and electron wavelength.
## Tools Used
- **`calculate_incident_photon_rate`** from `server-23` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/23/Optics_and_Electromagnetics`
- **`calculate_frequency_range`** from `server-23` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/23/Optics_and_Electromagnetics`
- **`calculate_radiation_pressure`** 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`
## Workflow
1. Calculate incident photon rate
2. Calculate frequency range
3. Compute radiation pressure
4. Calculate electron wavelength
## Test Case
### Input
```json
{
"wavelength": 5e-07,
"power": 1.0
}
```
### Expected Steps
1. Calculate incident photon rate
2. Calculate frequency range
3. Compute radiation pressure
4. Calculate electron wavelength
## 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-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())
```