unit_conversion_suite

Multi-Unit Conversion Suite - Convert units across domains: length mm to m, radius m to cm, dimensions to meters, nm to um, volume to cm3. Use this skill for metrology tasks involving convert length mm to m convert radius m to cm convert dimensions to meters convert nm to um convert volume to cm3. Combines 5 tools from 1 SCP server(s).

157 stars

Best use case

unit_conversion_suite is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Multi-Unit Conversion Suite - Convert units across domains: length mm to m, radius m to cm, dimensions to meters, nm to um, volume to cm3. Use this skill for metrology tasks involving convert length mm to m convert radius m to cm convert dimensions to meters convert nm to um convert volume to cm3. Combines 5 tools from 1 SCP server(s).

Teams using unit_conversion_suite should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/unit_conversion_suite/SKILL.md --create-dirs "https://raw.githubusercontent.com/InternScience/DrClaw/main/drclaw/local_skill_hub/science/physics/unit_conversion_suite/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/unit_conversion_suite/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How unit_conversion_suite Compares

Feature / Agentunit_conversion_suiteStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Multi-Unit Conversion Suite - Convert units across domains: length mm to m, radius m to cm, dimensions to meters, nm to um, volume to cm3. Use this skill for metrology tasks involving convert length mm to m convert radius m to cm convert dimensions to meters convert nm to um convert volume to cm3. Combines 5 tools from 1 SCP server(s).

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Multi-Unit Conversion Suite

**Discipline**: Metrology | **Tools Used**: 5 | **Servers**: 1

## Description

Convert units across domains: length mm to m, radius m to cm, dimensions to meters, nm to um, volume to cm3.

## Tools Used

- **`convert_length_mm_to_m`** from `server-27` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/27/Physical_Quantities_Conversion`
- **`convert_radius_m_to_cm`** from `server-27` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/27/Physical_Quantities_Conversion`
- **`convert_dimensions_to_meters`** from `server-27` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/27/Physical_Quantities_Conversion`
- **`convert_nm_to_um`** from `server-27` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/27/Physical_Quantities_Conversion`
- **`convert_volume_to_cm3`** from `server-27` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/27/Physical_Quantities_Conversion`

## Workflow

1. Convert mm to m
2. Convert radius m to cm
3. Convert dimensions to meters
4. Convert nm to um
5. Convert volume to cm3

## Test Case

### Input
```json
{
    "length_mm": 100,
    "radius_m": 0.5,
    "nm_val": 500
}
```

### Expected Steps
1. Convert mm to m
2. Convert radius m to cm
3. Convert dimensions to meters
4. Convert nm to um
5. Convert volume to cm3

## 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-27": "https://scp.intern-ai.org.cn/api/v1/mcp/27/Physical_Quantities_Conversion"
}

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-27"], _, _ = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/27/Physical_Quantities_Conversion", "streamable-http")

    # Execute workflow steps
    # Step 1: Convert mm to m
    result_1 = await sessions["server-27"].call_tool("convert_length_mm_to_m", arguments={})
    data_1 = parse(result_1)
    print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")

    # Step 2: Convert radius m to cm
    result_2 = await sessions["server-27"].call_tool("convert_radius_m_to_cm", arguments={})
    data_2 = parse(result_2)
    print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")

    # Step 3: Convert dimensions to meters
    result_3 = await sessions["server-27"].call_tool("convert_dimensions_to_meters", arguments={})
    data_3 = parse(result_3)
    print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")

    # Step 4: Convert nm to um
    result_4 = await sessions["server-27"].call_tool("convert_nm_to_um", arguments={})
    data_4 = parse(result_4)
    print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")

    # Step 5: Convert volume to cm3
    result_5 = await sessions["server-27"].call_tool("convert_volume_to_cm3", arguments={})
    data_5 = parse(result_5)
    print(f"Step 5 result: {json.dumps(data_5, indent=2, ensure_ascii=False)[:500]}")

    # Cleanup
    print("Workflow complete!")

if __name__ == "__main__":
    asyncio.run(main())
```

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