wind-site-assessment
Assess wind energy potential and perform site analysis using atmospheric science calculations.
Best use case
wind-site-assessment is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Assess wind energy potential and perform site analysis using atmospheric science calculations.
Teams using wind-site-assessment 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/wind-site-assessment/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How wind-site-assessment Compares
| Feature / Agent | wind-site-assessment | 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?
Assess wind energy potential and perform site analysis using atmospheric science calculations.
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
# Wind Site Assessment
## Usage
### 1. MCP Server Definition
```python
import asyncio
import json
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
class AtmSciClient:
"""AtmSci-Tool MCP Client"""
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.read, self.write, self.get_session_id = await self.transport.__aenter__()
self.session_ctx = ClientSession(self.read, self.write)
self.session = await self.session_ctx.__aenter__()
await self.session.initialize()
return True
except Exception as e:
print(f"✗ connect failure: {e}")
return False
async def disconnect(self):
try:
if self.session:
await self.session_ctx.__aexit__(None, None, None)
if hasattr(self, 'transport'):
await self.transport.__aexit__(None, None, None)
except Exception as e:
print(f"✗ disconnect error: {e}")
def parse_result(self, result):
try:
if hasattr(result, 'content') and result.content:
content = result.content[0]
if hasattr(content, 'text'):
return json.loads(content.text)
return str(result)
except Exception as e:
return {"error": f"parse error: {e}", "raw": str(result)}
```
### 2. Wind Site Assessment Workflow
Evaluate wind energy potential at a specific location.
**Implementation:**
```python
## Initialize client
client = AtmSciClient(
"https://scp.intern-ai.org.cn/api/v1/mcp/35/AtmSci-Tool",
"<your-api-key>"
)
if not await client.connect():
print("connection failed")
exit()
## Input: Wind measurements
wind_speeds = [6.5, 7.2, 8.1, 5.9, 9.3] # m/s at hub height
hub_height = 80 # meters
air_density = 1.225 # kg/m³
## Calculate wind power and assess site viability
# Note: Use appropriate atmospheric science tools
result = await client.session.call_tool(
"wind_power_assessment",
arguments={
"wind_speeds": wind_speeds,
"hub_height": hub_height,
"air_density": air_density
}
)
assessment = client.parse_result(result)
print(f"Average wind speed: {assessment['avg_speed']:.2f} m/s")
print(f"Wind power density: {assessment['power_density']:.2f} W/m²")
print(f"Site classification: {assessment['classification']}")
await client.disconnect()
```
### Use Cases
- Wind farm site selection
- Renewable energy assessment
- Atmospheric boundary layer studies
- Wind resource mappingRelated Skills
protein_quality_assessment
Protein Structure Quality Assessment - Assess structure quality: basic info, geometry analysis, quality metrics, composition, and visualization. Use this skill for structural biology tasks involving calculate pdb basic info calculate pdb structural geometry calculate pdb quality metrics calculate pdb composition info visualize protein. Combines 5 tools from 1 SCP server(s).
binding_site_characterization
Binding Site Characterization - Characterize binding sites: predict pockets with fpocket and P2Rank, get binding site info from ChEMBL, and visualize. Use this skill for structural biology tasks involving run fpocket pred pocket prank get binding site by id visualize protein. Combines 4 tools from 3 SCP server(s).
toxicity_assessment
Drug Toxicity Assessment - Comprehensive toxicity assessment: FDA adverse reactions, nonclinical toxicology, carcinogenicity data, and ADMET prediction. Use this skill for toxicology tasks involving get adverse reactions by drug name get nonclinical toxicology info by drug name get carcinogenic mutagenic fertility impairment info by drug name pred molecule admet. Combines 4 tools from 2 SCP server(s).
chemical_safety_assessment
Chemical Safety Assessment - Assess chemical safety: PubChem compound info, FDA drug data, ADMET prediction, and structural alerts from ChEMBL. Use this skill for chemical safety tasks involving get general info by compound name get warnings and cautions by drug name pred molecule admet get compound structural alert. Combines 4 tools from 4 SCP server(s).
fda-drug-risk-assessment
Assess drug risks and adverse effects using FDA drug database to retrieve safety information and risk profiles.
acpx
Use the ACPX CLI through DrClaw's existing exec/long_exec tools to run Codex in the current project workspace.
ui-ux-pro-max
[Frontend] Frontend UI/UX design intelligence - activate FIRST when user requests beautiful, stunning, gorgeous, or aesthetic interfaces. 50 styles, 21 palettes, 50 font pairings, 20 charts, 8 stacks. Triggers on ui design, ux design, design system, color palette, typography, glassmorphism, claymorphism, neumorphism, bento grid, font pairing, ui-ux-pro-max, stunning interface, beautiful ui.
fetch
Fetch metadata and links from arXiv for a given query.
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).
uniprot_deep_analysis
UniProt Deep Protein Analysis - Deep UniProt analysis: entry data, UniRef clusters, UniParc cross-references, and gene-centric view. Use this skill for protein science tasks involving get uniprotkb entry by accession get uniref cluster by id get uniparc entry by upi get gene centric by accession. Combines 4 tools from 1 SCP server(s).
synthetic_biology_design
Synthetic Biology Design - Design synthetic biology construct: gene lookup, codon optimization, protein property prediction, and structure prediction. Use this skill for synthetic biology tasks involving get sequence id DegenerateCodonCalculatorbyAminoAcid calculate protein sequence properties pred protein structure esmfold. Combines 4 tools from 4 SCP server(s).
structural_homology_modeling
Structural Homology & Evolution Analysis - Analyze protein evolution: get gene tree from Ensembl, find homologs, compare sequences, and predict structure. Use this skill for evolutionary biology tasks involving get homology symbol get genetree member symbol calculate protein sequence properties pred protein structure esmfold. Combines 4 tools from 3 SCP server(s).