Agent skill

Mat Calphad Property Diagram

by learningmatter-mit in learningmatter-mit/AtomisticSkills

Calculate temperature-dependent thermodynamic properties like Equilibrium Phase Fractions for a specific alloy composition using CALPHAD models.

MITAuto-check passed

Install Mat Calphad Property Diagram

skills CLI
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-calphad-property-diagram -a claude-code

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

GitHub CLI
$ gh skill install learningmatter-mit/AtomisticSkills mat-calphad-property-diagram --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/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/mat-calphad-property-diagram .claude/skills/mat-calphad-property-diagram && 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
mat-calphad-property-diagram
GitHub stars
176
Token cost
~533 tokens
SKILL.md length
160 words
Files
4 (incl. scripts)
Skills in repo
129
Repo updated
First seen
Licence
MIT

At a glance

Calculate temperature-dependent thermodynamic properties like Equilibrium Phase Fractions for a specific alloy composition using CALPHAD models.

  • Works in 2 steps: Identify Thermodynamic Database → Plot Equilibrium Phase Fractions
  • SKILL.md covers Goal, Instructions, Examples and Constraints, plus 1 more section
  • Runs Python scripts from its folder

What it does

Mat Calphad Property Diagram is an agent skill from learningmatter-mit/AtomisticSkills. Calculate temperature-dependent thermodynamic properties like Equilibrium Phase Fractions for a specific alloy composition using CALPHAD models.

Its SKILL.md is about 530 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts (for example `examples/Al-Zn/README.md` and `scripts/plot_phase_fractions.py`).

The repository describes itself as: Integrating AtomisticSkills into Agentic IDEs (Cursor, Claude Code, Codex, Google Antigravity, Hermes Agent, etc). The licence is MIT.

Example prompts

  • “/mat-calphad-property-diagram”

Requirements

  • Python 3

Workflow steps

2 steps, taken from the step headings in SKILL.md.

  1. Identify Thermodynamic Database
  2. Plot Equilibrium Phase Fractions

What it can do on your machine

Read from SKILL.md and the folder at commit 6257444. 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

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    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

Mat Calphad Property Diagram loads about 533 tokens when it runs. Until then it costs about 43 tokens; SKILL.md has 160 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~43
When it runs · the whole SKILL.md, loaded when a task matches
~533

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); the scripts in this folder are not scanned.

SKILL.md

The full file from learningmatter-mit/AtomisticSkills at commit 6257444, republished under its MIT licence (© learningmatter-mit). 160 words, ~533 tokens.

Download SKILL.mdSave it as .claude/skills/mat-calphad-property-diagram/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
mat-calphad-property-diagram
description
Calculate temperature-dependent thermodynamic properties like Equilibrium Phase Fractions for a specific alloy composition using CALPHAD models.
metadata.category
materials
metadata.venv
cpu

mat-calphad-property-diagram

Goal

To predict the equilibrium phase stability, phase fractions, and other extensive thermodynamic properties for a fixed multi-component alloy at different temperatures using PyCalphad. Very useful for modeling solidification, heat treatment paths, and precipitation sequences.

Instructions

1. Identify Thermodynamic Database

You must obtain a legitimate .tdb (Thermodynamic Data Base) file for the chemical system.

2. Plot Equilibrium Phase Fractions

Calculate what phases are present, and their molar fractions, across a cooling/heating schedule for a fixed composition.

bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/plot_phase_fractions.py path/to/database.tdb --elements Element1 Element2 --composition Element2 0.3 --t-range 300 1000 10 --output research_dir/phase_fractions.png
  • --composition: The solute element and its molar fraction (e.g. Zn 0.3 means 30 mol% Zn).
  • --t-range: START STOP STEP in Kelvin. Ensure solving across liquidus and solidus.

Examples

Evaluating phase fractions for an Al-40%Zn alloy as it cools:

bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/plot_phase_fractions.py ${CLAUDE_SKILL_DIR}/../mat-calphad-phase-diagram/examples/Al-Zn/alzn_mey.tdb --elements Al Zn --composition Zn 0.4 --t-range 300 900 10 --output phase_fractions.png

Constraints

  • Environments: Scripts require the cpu environment.
  • Only plots equilibrium step (lever-rule). For non-equilibrium fast solidification (Scheil), custom scripting is required.

References

  • Richard Otis and Zi-Kui Liu. "pycalphad: CALPHAD-based Computational Thermodynamics in Python." Journal of Open Research Software (2017).

Author: Bowen Deng Contact: GitHub @learningmatter-mit

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

Files

SKILL.md and 3 other files (scripts) in skills/mat-calphad-property-diagram of learningmatter-mit/AtomisticSkills.

  • SKILL.md
  • examples/Al-Zn/README.md
  • examples/Al-Zn/phase_fractions.png
  • scripts/plot_phase_fractions.py

Open the folder on GitHubat commit 6257444

Compare with similar skills

Mat Calphad Property Diagram 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.

Mat Calphad Property Diagram compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Mat Calphad Property Diagram this skilllearningmatter-mit/AtomisticSkills176—~533Automated safety check: PassMIT
Dependency Scanningsickn33/agentic-awesome-skills47k1 repos~2.4kAutomated safety check: PassMIT
Dependency Checkruvnet/ruflo74k—~258Automated safety check: PassMIT
Dependency Updatecodewhale-hq/Codewhale41k—~142Automated safety check: PassMIT
CSS At Propertythedaviddias/Front-End-Checklist74k—~602Automated safety check: PassMIT
Bump Sentry Dependencygetsentry/sentry46k—~815Automated safety check: PassCustom licence

Similar skills

  • Dependency Scanning

    sickn33/agentic-awesome-skills

    Scan package dependencies for known vulnerabilities using Snyk, Dependabot, and OWASP Dependency-Check.

    47k GitHub starsUsed in 1 repo~2.4k tokens
    SecurityAuto-check passed
  • Dependency Check

    ruvnet/ruflo

    Scan project dependencies for known vulnerabilities and CVEs.

    74k GitHub stars~258 tokensUpdated today
    SecurityAuto-check passed
  • Dependency Update

    codewhale-hq/Codewhale

    Read release notes/changelogs, update a defined dependency scope, handle breaking changes, and verify.

    41k GitHub stars~142 tokensUpdated today
    DevelopmentAuto-check passed
  • CSS At Property

    thedaviddias/Front-End-Checklist

    A skill your agent uses when implementing animated gradients, complex CSS transitions that involve custom property values, or building a typed design token system where custom property misuse should…

    74k GitHub stars~602 tokensUpdated 3 days ago
    Frontend & DesignAuto-check passed
  • Bump Sentry Dependency

    getsentry/sentry

    Official

    Bumps an existing Python dependency in getsentry/sentry through the repository's self-serve GitHub Actions workflow.

    46k GitHub stars~815 tokensUpdated today
    DevOps & CloudAuto-check passed
  • Audit, plan, and refresh dependency upgrades for the Logseq repository by scanning every non-gitignored package.json, deps.edn, bb.edn and nbb.edn manifest, checking latest upstream versions…

    45k GitHub stars~1.1k tokensUpdated today
    Knowledge ManagementAuto-check passed

More from learningmatter-mit/AtomisticSkills

All 129 skills in this repo
  • Drug Binding Site Definition

    learningmatter-mit/AtomisticSkills

    Define a docking search box (center coordinates + box dimensions in Angstroms) from a co-crystal ligand, binding-site residues, or a saved JSON specification.

    176 GitHub stars~2.9k tokensUpdated 2 days ago
    Auto-check passed
  • Drug Complex System Builder

    learningmatter-mit/AtomisticSkills

    Build a solvated, charge-neutralized protein-ligand complex for OpenMM molecular dynamics simulation.

    176 GitHub stars~2k tokensUpdated 2 days ago
    Auto-check passed
  • Drug Pocket Detection

    learningmatter-mit/AtomisticSkills

    Identify and rank ligandable pockets on a protein structure or model using geometry (fpocket) or an ML predictor (P2Rank).

    176 GitHub stars~4k tokensUpdated 2 days ago
    Auto-check passed
  • Chem Bond Dissociation

    learningmatter-mit/AtomisticSkills

    Calculate homolytic and heterolytic bond dissociation energies (BDEs) for all single bonds in a molecule using MLIPs with RDKit fragmentation.

    176 GitHub stars~2.5k tokensUpdated 2 days ago
    Auto-check passed
  • Chem Conformer Search

    learningmatter-mit/AtomisticSkills

    Generate molecular conformers with RDKit ETKDG, relax with MLIPs, and rank by energy with Boltzmann weighting.

    176 GitHub stars~1.3k tokensUpdated 2 days ago
    Auto-check passed
  • Chem DB Mof

    learningmatter-mit/AtomisticSkills

    Query multiple MOF databases (QMOF via MPContribs; ARC-MOF DB7/Majumdar et al.

    176 GitHub stars~1.9k tokensUpdated 2 days ago
    Auto-check passed

Questions about Mat Calphad Property Diagram

What does Mat Calphad Property Diagram do?

Calculate temperature-dependent thermodynamic properties like Equilibrium Phase Fractions for a specific alloy composition using CALPHAD models. Mat Calphad Property Diagram is an agent skill from learningmatter-mit/AtomisticSkills. Calculate temperature-dependent thermodynamic properties like Equilibrium Phase Fractions for a specific alloy composition using CALPHAD models.

How do I install Mat Calphad Property Diagram in Claude Code?

Run `npx skills add learningmatter-mit/AtomisticSkills --skill mat-calphad-property-diagram -a claude-code`. Or copy the skill folder (skills/mat-calphad-property-diagram in learningmatter-mit/AtomisticSkills) into .claude/skills/mat-calphad-property-diagram in your project. Claude Code loads it when a task matches its description.

How do I install Mat Calphad Property Diagram in Codex?

Run `npx skills add learningmatter-mit/AtomisticSkills --skill mat-calphad-property-diagram -a codex`. Or copy the skill folder (skills/mat-calphad-property-diagram in learningmatter-mit/AtomisticSkills) into .agents/skills/mat-calphad-property-diagram in your project. Codex loads it when a task matches its description.

Can I use Mat Calphad Property Diagram 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 learningmatter-mit/AtomisticSkills --skill mat-calphad-property-diagram -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mat-calphad-property-diagram, .gemini/skills/mat-calphad-property-diagram, .github/skills/mat-calphad-property-diagram and .opencode/skills/mat-calphad-property-diagram in your project.

What does Mat Calphad Property Diagram need to run?

Going by SKILL.md and its folder, Mat Calphad Property Diagram needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Mat Calphad Property Diagram access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Mat Calphad Property Diagram 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Mat Calphad Property Diagram use?

Mat Calphad Property Diagram is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Mat Calphad Property Diagram use?

About 533 tokens (SKILL.md is roughly 2.1k 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 Mat Calphad Property Diagram?

Skills that share tags, products or a category with Mat Calphad Property Diagram: Dependency Scanning (sickn33/agentic-awesome-skills, 47k stars), Dependency Check (ruvnet/ruflo, 74k stars), Dependency Update (codewhale-hq/Codewhale, 41k stars) and CSS At Property (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Mat Calphad Property Diagram?

learningmatter-mit (a GitHub organization) maintains it in learningmatter-mit/AtomisticSkills, which has 176 GitHub stars. The repository holds 129 skills in this directory. The repository was last updated on October 7, 2026.

Source: learningmatter-mit/AtomisticSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.