New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Material Density Volume Calculation

by InternScience in InternScience/scp

Calculate material density and volume from mass and geometric dimensions for materials mechanics analysis.

MITAuto-check passed

Install Material Density Volume Calculation

skills CLI
$ npx skills add InternScience/scp --skill material-density-volume-calculation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install InternScience/scp material-density-volume-calculation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/InternScience/scp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/material-density-volume-calculation .claude/skills/material-density-volume-calculation && rm -rf skills-src

Use ~/.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/

Facts

Skill name
material-density-volume-calculation
GitHub stars
169
Used in
1 other repo
Token cost
~497 tokens
SKILL.md length
15 words
Files
1
Skills in repo
73
Repo updated
First seen
Licence
MIT

At a glance

Calculate material density and volume from mass and geometric dimensions for materials mechanics analysis.

  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Material Density Volume Calculation is an agent skill from InternScience/scp. Calculate material density and volume from mass and geometric dimensions for materials mechanics analysis.

Its SKILL.md is about 500 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The licence is MIT.

Example prompts

  • “/material-density-volume-calculation”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit cea5398. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    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.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Material Density Volume Calculation loads about 497 tokens when it runs. Until then it costs about 36 tokens; SKILL.md has 15 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~36
When it runs · the whole SKILL.md, loaded when a task matches
~497

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from InternScience/scp at commit cea5398, republished under its MIT licence (© InternScience). 15 words, ~497 tokens.

Download SKILL.mdSave it as .claude/skills/material-density-volume-calculation/SKILL.md (or your agent's skills folder).
name
material-density-volume-calculation
description
Calculate material density and volume from mass and geometric dimensions for materials mechanics analysis.
license
MIT license
metadata.skill-author
PJLab

Material Density and Volume Calculation

Usage

python
import asyncio
import json
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession

class PhysicsClient:
    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:
            return False

    async def disconnect(self):
        if self.session:
            await self.session_ctx.__aexit__(None, None, None)
        if hasattr(self, 'transport'):
            await self.transport.__aexit__(None, None, None)

    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 = PhysicsClient("https://scp.intern-ai.org.cn/api/v1/mcp/20/Materials_Mechanics_and_Fracture_Analysis", "<your-api-key>")
await client.connect()

# Calculate density from mass and volume
mass = 100  # kg
volume = 0.05  # m³
density = mass / volume
print(f"Density: {density} kg/m³")

await client.disconnect()
Use Cases
  • Material property characterization, structural engineering, quality control

© InternScience, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/material-density-volume-calculation of InternScience/scp.

Open the folder on GitHubat commit cea5398

Used in 2 other repositories

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.

Compare with similar skills

Material Density Volume Calculation 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.

Material Density Volume Calculation compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Material Density Volume Calculation this skillInternScience/scp1691 repos~497Automated safety check: PassMIT
Dimensionsthedaviddias/Front-End-Checklist74k—~926Automated safety check: PassMIT
Investor Materialsaffaan-m/ECC275k3 repos~268Automated safety check: PassMIT
Material Designsickn33/agentic-awesome-skills47k1 repos~2.6kAutomated safety check: PassMIT
Torch GeometricK-Dense-AI/scientific-agent-skills48k1 repos~5.6kAutomated safety check: PassMIT
Materialbergside/awesome-design-skills3.1k1 repos~919Automated safety check: PassMIT

Similar skills

  • Dimensions

    thedaviddias/Front-End-Checklist

    A skill your agent uses when reviewing image assets, markup, and CDN or build transforms related to Set explicit width and height on images.

    74k GitHub stars~926 tokensUpdated 2 days ago
    Frontend & DesignAuto-check passed

  • Investor Materials

    affaan-m/ECC

    创建和更新宣传文稿、一页简介、投资者备忘录、加速器申请、财务模型和融资材料。当用户需要面向投资者的文件、预测、资金用途表、里程碑计划或必须在多个融资资产中保持内部一致性的材料时使用。

    275k GitHub starsUsed in 3 repos~268 tokens
    Auto-check passed

  • Material Design

    sickn33/agentic-awesome-skills

    Web and App implementation guide for Material Design. An agent skill from sickn33/agentic-awesome-skills.

    47k GitHub starsUsed in 1 repo~2.6k tokens
    MobileAuto-check passed

  • Torch Geometric

    K-Dense-AI/scientific-agent-skills

    Supports PyTorch Geometric (PyG) graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor sampling, and custom datasets.

    48k GitHub starsUsed in 1 repo~5.6k tokens
    AI & LLM EngineeringAuto-check passed

  • Material

    bergside/awesome-design-skills

    Google's Material Design with layered surfaces, dynamic theming, built-in motion, and responsive cross-platform patterns.

    3.1k GitHub starsUsed in 1 repo~919 tokens
    Frontend & DesignAuto-check passed

  • Geometric

    bergside/awesome-design-skills

    Geometric, structured design with clean typography, neutral colors, precise shapes, and intuitive layouts that stay out of the way.

    3.1k GitHub stars~850 tokensUpdated 3 mo ago
    Frontend & DesignAuto-check passed

More from InternScience/scp

All 73 skills in this repo

  • Comprehensive Variant Annotation

    InternScience/scp

    Given an rsID, query multiple databases (dbSNP, FAVOR, GWAS Catalog, ClinVar, gnomAD, PharmGKB, ClinGen) for comprehensive annotation.

    169 GitHub starsUsed in 1 repo~2.2k tokens
    Auto-check passed

  • Drugsda Esmfold

    InternScience/scp

    Use ESMFold model to predict 3D structure of the input protein sequence.

    169 GitHub starsUsed in 2 repos~721 tokens
    Auto-check passed

  • Drugsda Prosst

    InternScience/scp

    Given a protein sequence and its structure, employ ProSST model to predict mutation effects and obtain the top-k mutated sequences.

    169 GitHub starsUsed in 2 repos~949 tokens
    Auto-check passed

  • Atmospheric Science Calculations

    InternScience/scp

    Calculate atmospheric parameters including Coriolis parameter, geostrophic wind, heat index, potential temperature, and dewpoint for meteorology and climate science.

    169 GitHub starsUsed in 1 repo~2.1k tokens
    Auto-check passed

  • Biomedical Web Search

    InternScience/scp

    Search biomedical literature and web content using Tavily search engine for research and clinical information.

    169 GitHub starsUsed in 1 repo~598 tokens
    Auto-check passed

  • Buoyancy Acceleration Calculation

    InternScience/scp

    Calculate buoyancy forces and acceleration for fluid mechanics and hydrodynamics analysis.

    169 GitHub starsUsed in 1 repo~540 tokens
    Auto-check passed

Questions about Material Density Volume Calculation

What does Material Density Volume Calculation do?

Calculate material density and volume from mass and geometric dimensions for materials mechanics analysis. Material Density Volume Calculation is an agent skill from InternScience/scp. Calculate material density and volume from mass and geometric dimensions for materials mechanics analysis.

How do I install Material Density Volume Calculation in Claude Code?

Run `npx skills add InternScience/scp --skill material-density-volume-calculation -a claude-code`. Or copy the skill folder (skills/material-density-volume-calculation in InternScience/scp) into .claude/skills/material-density-volume-calculation in your project. Claude Code loads it when a task matches its description.

How do I install Material Density Volume Calculation in Codex?

Run `npx skills add InternScience/scp --skill material-density-volume-calculation -a codex`. Or copy the skill folder (skills/material-density-volume-calculation in InternScience/scp) into .agents/skills/material-density-volume-calculation in your project. Codex loads it when a task matches its description.

Can I use Material Density Volume Calculation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add InternScience/scp --skill material-density-volume-calculation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/material-density-volume-calculation, .gemini/skills/material-density-volume-calculation, .github/skills/material-density-volume-calculation and .opencode/skills/material-density-volume-calculation in your project.

What does Material Density Volume Calculation need to run?

SKILL.md names no scripts, command-line tools or credentials: Material Density Volume Calculation is instructions for the agent only. Our summary lists: Python 3.

Does Material Density Volume Calculation access the network?

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.

Is Material Density Volume Calculation safe to install?

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.

What licence does Material Density Volume Calculation use?

Material Density Volume Calculation is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Material Density Volume Calculation use?

About 497 tokens (SKILL.md is roughly 2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Material Density Volume Calculation?

Skills that share tags, products or a category with Material Density Volume Calculation: Dimensions (thedaviddias/Front-End-Checklist, 74k stars), Investor Materials (affaan-m/ECC, 275k stars), Material Design (sickn33/agentic-awesome-skills, 47k stars) and Torch Geometric (K-Dense-AI/scientific-agent-skills, 48k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Material Density Volume Calculation?

InternScience (a GitHub organization) maintains it in InternScience/scp, which has 169 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.