unit-conversion-nanoscale
Convert physical quantities and units at nanoscale for materials science and nanotechnology applications.
Best use case
unit-conversion-nanoscale is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Convert physical quantities and units at nanoscale for materials science and nanotechnology applications.
Teams using unit-conversion-nanoscale 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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/unit-conversion-nanoscale/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How unit-conversion-nanoscale Compares
| Feature / Agent | unit-conversion-nanoscale | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Convert physical quantities and units at nanoscale for materials science and nanotechnology applications.
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
# Unit Conversion for Nanoscale
## Usage
```python
import asyncio
import json
from contextlib import AsyncExitStack
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
class UnitClient:
def __init__(self, server_url: str, api_key: str):
self.server_url = server_url
self.api_key = api_key
self.session = None
async def connect(self):
try:
self.transport = streamablehttp_client(url=self.server_url, headers={"SCP-HUB-API-KEY": self.api_key})
self._stack = AsyncExitStack()
await self._stack.__aenter__()
self.read, self.write, self.get_session_id = await self._stack.enter_async_context(self.transport)
self.session_ctx = ClientSession(self.read, self.write)
self.session = await self._stack.enter_async_context(self.session_ctx)
await self.session.initialize()
return True
except:
return False
async def disconnect(self):
"""Disconnect from server"""
try:
if hasattr(self, '_stack'):
await self._stack.aclose()
print("✓ already disconnect")
except Exception as e:
print(f"✗ disconnect error: {e}")
def parse_result(self, result):
try:
if hasattr(result, 'content') and result.content:
return json.loads(result.content[0].text)
return str(result)
except:
return {"error": "parse error"}
## Initialize and use
client = UnitClient("https://scp.intern-ai.org.cn/api/v1/mcp/27/Physical_Quantities_Conversion", "<your-api-key>")
await client.connect()
# Nanoscale unit conversions
nm_to_m = 1e-9
angstrom_to_m = 1e-10
length_nm = 50 # nanometers
length_m = length_nm * nm_to_m
length_angstrom = length_m / angstrom_to_m
print(f"{length_nm} nm = {length_m:.2e} m = {length_angstrom:.1f} Å")
# Energy conversion (eV to Joules)
eV_to_J = 1.602e-19
energy_eV = 2.5
energy_J = energy_eV * eV_to_J
print(f"{energy_eV} eV = {energy_J:.2e} J")
await client.disconnect()
```
### Use Cases
- Nanotechnology, semiconductor physics, quantum mechanics, materials characterizationRelated Skills
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).
smiles-to-cas-conversion
Convert SMILES strings to CAS registry numbers using material informatics tools to identify chemical substances.
molecular-format-conversion
Convert between molecular formats including SMILES, InChI, InChIKey, and SELFIES for cheminformatics applications.
energy_conversion
Energy Unit Conversion Pipeline - Convert between energy units and analyze: MeV to Joules, scientific notation, and error calculation. Use this skill for physics tasks involving convert energy MeV to J convert to scientific notation format scientific notation calculate absolute error. Combines 4 tools from 2 SCP server(s).
wind-site-assessment
Assess wind energy potential and perform site analysis using atmospheric science calculations.
web_literature_mining
Scientific Literature Mining - Mine scientific literature: PubMed search, arXiv search, web search, and Tavily deep search. Use this skill for scientific informatics tasks involving pubmed search search literature search web tavily search. Combines 4 tools from 2 SCP server(s).
virus_genomics
Virus Genomics Analysis - Analyze virus genomics: NCBI virus dataset, annotation, taxonomy, and literature search. Use this skill for virology tasks involving get virus dataset report get virus annotation report get taxonomy search literature. Combines 4 tools from 2 SCP server(s).
virtual_screening
Virtual Screening Pipeline - Virtual screening: search PubChem by substructure, compute similarity, filter by drug-likeness, and predict binding affinity. Use this skill for drug discovery tasks involving search pubchem by smiles calculate smiles similarity calculate mol drug chemistry boltz binding affinity. Combines 4 tools from 3 SCP server(s).
variant_pathogenicity
Variant Pathogenicity Assessment - Assess variant pathogenicity: Ensembl VEP prediction, ClinVar lookup, variation details, and gene phenotype associations. Use this skill for clinical genetics tasks involving get vep hgvs clinvar search get variation get phenotype gene. Combines 4 tools from 2 SCP server(s).
variant-population-frequency
Query gnomAD for variant allele frequency across populations. Uses FAVOR to convert rsID→variant_id first, then queries gnomAD.
variant-pharmacogenomics
Query PharmGKB (clinPGx) for pharmacogenomic clinical annotations — how a variant affects drug response, dosing, and adverse reactions.
variant-gwas-associations
Query EBI GWAS Catalog for GWAS statistical associations (p-value, effect size, risk allele) between a variant and traits/diseases.