Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Zaoqu-Liu/ScienceClawnpx agentmods add skills/zaoqu-liu/scienceclaw/pymatgenWrote 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.
[](https://agentmods.dev/skills/zaoqu-liu/scienceclaw/pymatgen)<a href="https://agentmods.dev/skills/zaoqu-liu/scienceclaw/pymatgen"><img src="https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/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.
<a href="https://agentmods.dev/skills/zaoqu-liu/scienceclaw/pymatgen"><img src="https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/pymatgen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00038 | $0.05240 |
| Opus 5 | $0.00019 | $0.02620 |
| Sonnet 5 | $0.00008 | $0.01048 |
| Haiku 4.5 | $0.00004 | $0.00524 |
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 7d ago.
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.
This is a copy
91% identical to pymatgen — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 691 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")
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.
- 7d ago First seen · 691 lines · 38 tokens per session scan A bd866be0aac3
pymatgen is a skill published in the GitHub repository Zaoqu-Liu/ScienceClaw (60 stars, last pushed 5mo ago), licensed MIT. It adds 38 tokens to every session and 5,240 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to pymatgen, differing in 3 lines, and is treated as a copy.
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