pymatgen

pymatgen is a skill for Claude Code, Codex from zLanqing/codex-claude-academic-skills. It costs 38 tokens per session (5,080 once invoked), scanned A, original, MIT.

A Python toolkit for computational materials science, including analysis of crystal structures, molecules, phase diagrams, and electronic properties. It also works with materials data and many file formats used by scientific software.

In plain words
What is it for?
Use it to read and convert files such as CIF and POSCAR, study symmetry and stability, analyze band structures or density of states, create surfaces, and access Materials Project data.
Why use it?
It avoids building separate code for common materials calculations, structure conversions, and database access.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to read and convert files such as CIF and POSCAR, study symmetry and stability, analyze band structures or density of states, create surfaces, and access Materials Project data.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zlanqing/codex-claude-academic-skills/pymatgen
About the project

zLanqing/codex-claude-academic-skills is a collection of three skills for academic writing, editable Word and PowerPoint documents, and scientific computing with MATLAB and Python. Chinese-speaking researchers use it for literature reports, papers, presentations, data analysis, simulations, and publication figures in Claude Code or Codex. The catalogue contains the project's academic workflow skills.

zLanqing/codex-claude-academic-skills · 3,735 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add zLanqing/codex-claude-academic-skills --skill pymatgen
Clone the repo
git clone --depth 1 https://github.com/zLanqing/codex-claude-academic-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for pymatgen

README.md
[![agentmods](https://agentmods.dev/badge/skills/zlanqing/codex-claude-academic-skills/pymatgen/github.svg)](https://agentmods.dev/skills/zlanqing/codex-claude-academic-skills/pymatgen)
Your own site
<a href="https://agentmods.dev/skills/zlanqing/codex-claude-academic-skills/pymatgen"><img src="https://agentmods.dev/badge/skills/zlanqing/codex-claude-academic-skills/pymatgen/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for pymatgen

Your own site · 80×15
<a href="https://agentmods.dev/skills/zlanqing/codex-claude-academic-skills/pymatgen"><img src="https://agentmods.dev/badge/skills/zlanqing/codex-claude-academic-skills/pymatgen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,080 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Privilege Escalation · line 370
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • medium analysis-evasion · line 1
    Suspicious Unicode normalization or mixed-script content
    Fix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00038 $0.05080
Opus 5 $0.00019 $0.02540
Sonnet 5 $0.00008 $0.01016
Haiku 4.5 $0.00004 $0.00508

Measured 11d ago against content hash 4f3a96dc5a5d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

pymatgen scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/phase_diagram_generator.py, scripts/structure_analyzer.py, scripts/structure_converter.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

8 near-identical copies found in the catalogue:

  • pymatgen — 100% identical, 1 lines differ
  • pymatgen — 100% identical, 0 lines differ
  • pymatgen — 98% identical, 2 lines differ
  • pymatgen — 97% identical, 6 lines differ
  • pymatgen — 97% identical, 2 lines differ
  • pymatgen — 94% identical, 3 lines differ
  • pymatgen — 92% identical, 4 lines differ
  • pymatgen — 91% identical, 2 lines differ
scientific-toolkit-skill/references/scientific-skills/pymatgen/SKILL.md · 690 lines

How it starts

The opening of the file, as written. The whole thing — 690 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Pymatgen - Python Materials Genomics

Overview

Pymatgen is a comprehensive Python library for materials analysis that powers the Materials Project. Create, analyze, and manipulate crystal structures and molecules, compute phase diagrams and thermodynamic properties, analyze electronic structure (band structures, DOS), generate surfaces and interfaces, and access Materials Project's database of computed materials. Supports 100+ file formats from various computational codes.

When to Use This Skill

This skill should be used when:

  • Working with crystal structures or molecular systems in materials science
  • Converting between structure file formats (CIF, POSCAR, XYZ, etc.)
  • Analyzing symmetry, space groups, or coordination environments
  • Computing phase diagrams or assessing thermodynamic stability
  • Analyzing electronic structure data (band gaps, DOS, band structures)
  • Generating surfaces, slabs, or studying interfaces
  • Accessing the Materials Project database programmatically
  • Setting up high-throughput computational workflows
  • Analyzing diffusion, magnetism, or mechanical properties
  • Working with VASP, Gaussian, Quantum ESPRESSO, or other computational codes

Quick Start Guide

Installation

# Core pymatgen
uv pip install pymatgen

# With Materials Project API access
uv pip install pymatgen mp-api

# Optional dependencies for extended functionality
uv pip install pymatgen[analysis]  # Additional analysis tools
uv pip install pymatgen[vis]       # Visualization tools

Basic Structure Operations

from pymatgen.core import Structure, Lattice

# Read structure from file (automatic format detection)
struct = Structure.from_file("POSCAR")

# Create structure from scratch
lattice = Lattice.cubic(3.84)
struct = Structure(lattice, ["Si", "Si"], [[0,0,0], [0.25,0.25,0.25]])

# Write to different format
struct.to(filename="structure.cif")

# Basic properties
print(f"Formula: {struct.composition.reduced_formula}")
print(f"Space group: {struct.get_space_group_info()}")
print(f"Density: {struct.density:.2f} g/cm³")

Read the full file on GitHub · 690 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 690 lines · 38 tokens per session scan A 4f3a96dc5a5d

Subscribe to this mod's changes

pymatgen is a skill published in the GitHub repository zLanqing/codex-claude-academic-skills (3,735 stars, last pushed 3mo ago), licensed MIT. It adds 38 tokens to every session and 5,080 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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