Astropy
zLanqing/codex-claude-academic-skills
Comprehensive Python library for astronomy and astrophysics.
Calculate atmospheric parameters including Coriolis parameter, geostrophic wind, heat index, potential temperature, and dewpoint for meteorology and climate science.
$ npx skills add InternScience/scp --skill atmospheric-science-calculations -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install InternScience/scp atmospheric-science-calculations --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/atmospheric-science-calculations .claude/skills/atmospheric-science-calculations && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "atmospheric-science-calculations" agent skill from https://github.com/InternScience/scp/tree/main/skills/atmospheric-science-calculations into .claude/skills/atmospheric-science-calculations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "atmospheric-science-calculations", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/InternScience/scp/tree/main/skills/atmospheric-science-calculationsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add InternScience/scp --skill atmospheric-science-calculations -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install InternScience/scp atmospheric-science-calculations --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/atmospheric-science-calculations .agents/skills/atmospheric-science-calculations && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "atmospheric-science-calculations" agent skill from https://github.com/InternScience/scp/tree/main/skills/atmospheric-science-calculations into .agents/skills/atmospheric-science-calculations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "atmospheric-science-calculations", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add InternScience/scp --skill atmospheric-science-calculations -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install InternScience/scp atmospheric-science-calculations --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/atmospheric-science-calculations .cursor/skills/atmospheric-science-calculations && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "atmospheric-science-calculations" agent skill from https://github.com/InternScience/scp/tree/main/skills/atmospheric-science-calculations into .cursor/skills/atmospheric-science-calculations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "atmospheric-science-calculations", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/InternScience/scp.git --path skills/atmospheric-science-calculations--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add InternScience/scp --skill atmospheric-science-calculations -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install InternScience/scp atmospheric-science-calculations --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/atmospheric-science-calculations .gemini/skills/atmospheric-science-calculations && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "atmospheric-science-calculations" agent skill from https://github.com/InternScience/scp/tree/main/skills/atmospheric-science-calculations into .gemini/skills/atmospheric-science-calculations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "atmospheric-science-calculations", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install InternScience/scp atmospheric-science-calculationsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add InternScience/scp --skill atmospheric-science-calculations -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/atmospheric-science-calculations .github/skills/atmospheric-science-calculations && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "atmospheric-science-calculations" agent skill from https://github.com/InternScience/scp/tree/main/skills/atmospheric-science-calculations into .github/skills/atmospheric-science-calculations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "atmospheric-science-calculations", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add InternScience/scp --skill atmospheric-science-calculations -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install InternScience/scp atmospheric-science-calculations --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/atmospheric-science-calculations .opencode/skills/atmospheric-science-calculations && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "atmospheric-science-calculations" agent skill from https://github.com/InternScience/scp/tree/main/skills/atmospheric-science-calculations into .opencode/skills/atmospheric-science-calculations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "atmospheric-science-calculations", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
atmospheric-science-calculationsCalculate atmospheric parameters including Coriolis parameter, geostrophic wind, heat index, potential temperature, and dewpoint for meteorology and climate science.
Atmospheric Science Calculations is an agent skill from InternScience/scp. Calculate atmospheric parameters including Coriolis parameter, geostrophic wind, heat index, potential temperature, and dewpoint for meteorology and climate science.
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science, covering Physical and earth sciences. The licence is MIT.
2 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit cea5398. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Atmospheric Science Calculations loads about 2.1k tokens when it runs. Until then it costs about 50 tokens; SKILL.md has 389 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from InternScience/scp at commit cea5398, republished under its MIT licence (© InternScience). 389 words, ~2,115 tokens.
.claude/skills/atmospheric-science-calculations/SKILL.md (or your agent's skills folder).import asyncio
import json
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
class AtmSciClient:
"""Atmospheric Science Tools 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):
print(f"Connecting to: {self.server_url}")
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()
print("✓ connect success")
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)
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:
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)}Calculate key atmospheric parameters for meteorology, climate science, and weather forecasting applications.
Workflow Steps:
Implementation:
## 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()
print("=== Atmospheric Science Calculations ===\n")
## Step 1: Calculate Coriolis parameter
print("Step 1: Coriolis Parameter")
latitude = 45.0 # degrees
result = await client.session.call_tool(
"atm_calc_coriolis_parameter",
arguments={"latitude": latitude}
)
result_data = client.parse_result(result)
print(f"Latitude: {latitude}°")
print(f"Coriolis parameter: {result_data} s⁻¹\n")
## Step 2: Calculate geostrophic wind
print("Step 2: Geostrophic Wind")
result = await client.session.call_tool(
"atm_calc_geostrophic_wind",
arguments={
"pressure_gradient_x": 1.0, # Pa/m
"pressure_gradient_y": 0.5, # Pa/m
"latitude": latitude,
"air_density": 1.225 # kg/m³
}
)
result_data = client.parse_result(result)
print(f"Geostrophic wind (u, v): {result_data} m/s\n")
## Step 3: Calculate heat index
print("Step 3: Heat Index")
result = await client.session.call_tool(
"atm_calc_heat_index",
arguments={
"temperature_f": 95.0, # °F
"relative_humidity": 65.0 # %
}
)
result_data = client.parse_result(result)
print(f"Temperature: 95°F, Humidity: 65%")
print(f"Heat index: {result_data}°F\n")
## Step 4: Calculate potential temperature
print("Step 4: Potential Temperature")
result = await client.session.call_tool(
"atm_calc_potential_temperature",
arguments={
"temperature_k": 288.15, # K (15°C)
"pressure_pa": 85000.0 # Pa (850 hPa)
}
)
result_data = client.parse_result(result)
print(f"Temperature: 288.15 K, Pressure: 850 hPa")
print(f"Potential temperature: {result_data} K\n")
## Step 5: Calculate dewpoint
print("Step 5: Dewpoint Temperature")
result = await client.session.call_tool(
"atm_calc_dewpoint",
arguments={
"temperature_c": 25.0, # °C
"relative_humidity": 60.0 # %
}
)
result_data = client.parse_result(result)
print(f"Temperature: 25°C, Humidity: 60%")
print(f"Dewpoint: {result_data}°C\n")
## Step 6: Check for heatwave conditions
print("Step 6: Heatwave Detection")
temperatures = [32, 34, 35, 36, 35, 34] # °C over 6 days
result = await client.session.call_tool(
"atm_check_heatwave",
arguments={
"temperatures": temperatures,
"threshold": 32.0, # °C
"min_duration": 3 # days
}
)
result_data = client.parse_result(result)
print(f"Temperatures: {temperatures}°C")
print(f"Heatwave detected: {result_data}\n")
await client.disconnect()AtmSci-Tool Server:
atm_calc_coriolis_parameter: Calculate Coriolis parameter (f = 2Ω sin φ)
latitude (float) - Latitude in degreesatm_calc_geostrophic_wind: Calculate geostrophic wind from pressure gradient
pressure_gradient_x, pressure_gradient_y (Pa/m), latitude (deg), air_density (kg/m³)atm_calc_heat_index: Calculate heat index (apparent temperature)
temperature_f (°F), relative_humidity (%)atm_calc_potential_temperature: Calculate potential temperature
temperature_k (K), pressure_pa (Pa)atm_calc_dewpoint: Calculate dewpoint temperature
temperature_c (°C), relative_humidity (%)atm_check_heatwave: Detect heatwave conditions
temperatures (list), threshold (°C), min_duration (days)Inputs:
Outputs:
Coriolis Parameter:
Geostrophic Wind:
Heat Index:
80°F: Caution (fatigue possible)
90°F: Extreme caution (heat exhaustion possible)
103°F: Danger (heat stroke likely)
125°F: Extreme danger
Potential Temperature:
Dewpoint:
atm_calc_standard_atmosphere: Calculate standard atmosphere propertiesgenerate_synthetic_sounding: Create atmospheric sounding profilesworkflow_storm_diagnosis: Analyze storm conditionsworkflow_wind_site_assessment: Assess wind energy potentialgeo_calc_distance: Calculate geographic distancesstats_calc_anomaly: Calculate climate anomaliesstats_calc_rolling_mean: Compute running averagesstats_linear_trend: Determine climate trends© InternScience, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/atmospheric-science-calculations of InternScience/scp.
Open the folder on GitHubat commit cea5398
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in InternScience/scp, which our catalogue first saw on October 7, 2026.
Atmospheric Science Calculations next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Atmospheric Science Calculations this skillInternScience/scp | 170 | 1 repos | ~2.1k | Automated safety check: Pass | MIT | |
| AstropyzLanqing/codex-claude-academic-skills | 4.7k | 13 repos | ~2.9k | Automated safety check: Pass | BSD-3-Clause | |
| PymatgenzLanqing/codex-claude-academic-skills | 4.7k | 11 repos | ~5k | Automated safety check: Pass | MIT | |
| Cantera Ignition DelayK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~2.2k | Automated safety check: Pass | MIT | |
| Weathertrpc-group/trpc-agent-go | 1.9k | 8 repos | ~591 | Automated safety check: Pass | Apache-2.0 | |
| Pymol VisualizationChatMol/ChatMol | 373 | — | ~1.2k | Automated safety check: Pass | MIT |
zLanqing/codex-claude-academic-skills
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zLanqing/codex-claude-academic-skills
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ChatMol/ChatMol
Generate publication-quality molecular visualization images using PyMOL.
Muuuun/luxas
Write domain-authentic review articles that synthesize rather than stack.
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Search biomedical literature and web content using Tavily search engine for research and clinical information.
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Calculate electrical capacitance from geometric parameters and dielectric properties for circuit design.
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Predict protein-ligand binding affinity using Boltz-2 model to assess molecular interactions and binding probability for drug discovery.
Categories
Calculate atmospheric parameters including Coriolis parameter, geostrophic wind, heat index, potential temperature, and dewpoint for meteorology and climate science. Atmospheric Science Calculations is an agent skill from InternScience/scp. Calculate atmospheric parameters including Coriolis parameter, geostrophic wind, heat index, potential temperature, and dewpoint for meteorology and climate science.
Atmospheric Science Calculations fits situations like: tasks that involve Physical and earth sciences.
Run `npx skills add InternScience/scp --skill atmospheric-science-calculations -a claude-code`. Or copy the skill folder (skills/atmospheric-science-calculations in InternScience/scp) into .claude/skills/atmospheric-science-calculations in your project. Claude Code loads it when a task matches its description.
Run `npx skills add InternScience/scp --skill atmospheric-science-calculations -a codex`. Or copy the skill folder (skills/atmospheric-science-calculations in InternScience/scp) into .agents/skills/atmospheric-science-calculations in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add InternScience/scp --skill atmospheric-science-calculations -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/atmospheric-science-calculations, .gemini/skills/atmospheric-science-calculations, .github/skills/atmospheric-science-calculations and .opencode/skills/atmospheric-science-calculations in your project.
SKILL.md names no scripts, command-line tools or credentials: Atmospheric Science Calculations is instructions for the agent only. Our summary lists: Python 3.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Atmospheric Science Calculations is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.1k tokens (SKILL.md is roughly 8.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Atmospheric Science Calculations: Astropy (zLanqing/codex-claude-academic-skills, 4.7k stars), Pymatgen (zLanqing/codex-claude-academic-skills, 4.7k stars), Cantera Ignition Delay (K-Dense-AI/scientific-agent-skills, 48k stars) and Weather (trpc-group/trpc-agent-go, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
InternScience (a GitHub organization) maintains it in InternScience/scp, which has 170 GitHub stars. The repository holds 73 skills in this directory. The repository was last updated on June 3, 2026.
Source: InternScience/scp on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.