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.
npx agentmods add skills/learningmatter-mit/atomisticskills/general-property-unitsnpx skills add learningmatter-mit/AtomisticSkills --skill general-property-unitsgit clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkillsWrote 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/learningmatter-mit/atomisticskills/general-property-units)<a href="https://agentmods.dev/skills/learningmatter-mit/atomisticskills/general-property-units"><img src="https://agentmods.dev/badge/skills/learningmatter-mit/atomisticskills/general-property-units.svg" alt="Measured on agentmods" 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 | $0.00030 | $0.02296 |
| Opus 5 | $0.00015 | $0.01148 |
| Sonnet 5 | $0.00006 | $0.00459 |
| Haiku 4.5 | $0.00003 | $0.00230 |
Grade A, and why
general-property-units 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Units Reference for Atomistic Simulations
Goal
Provide a single authoritative reference for units of energy, forces, and stress across all MLIPs, DFT codes, and simulation tools used in this project, including the conversions applied internally.
Project Standard
All internal representations follow the ASE (Atomic Simulation Environment) convention:
| Quantity | Standard Unit | Notes |
|---|---|---|
| Energy | eV | Total energy of the system |
| Energy per atom | eV/atom | Used for MAE reporting and training labels |
| Forces | eV/Å | Negative gradient of energy w.r.t. position |
| Stress | eV/ų | Voigt notation, 6-component (xx, yy, zz, yz, xz, xy) |
MLIP Model Units
Prediction (Inference)
The raw torch model and the ASE calculator do not return the same stress units. Most calculators apply a unit conversion on the way out; two do not. Read the stress column for the layer you are actually calling.
Energy is eV and forces are eV/Å everywhere, at both layers. Only stress varies:
| Model (calculator class) | raw model output | ASE calculator output | conversion in the ASE layer |
|---|---|---|---|
MACE (MACECalculator) |
eV/ų | eV/ų | none |
UMA / FairChem (FAIRChemCalculator) |
eV/ų | eV/ų | none |
CHGNet standalone (CHGNetCalculator) |
GPa | eV/ų | × stress_weight, default 1/160.21766208 |
CHGNet / M3GNet / TensorNet via MatGL (PESCalculator) |
GPa | GPa unless asked otherwise | none by default — pass stress_unit="eV/A3" |
Measured on one compressed Si cell (xx component), 2026-08-25:
| path | raw | calculator default | calculator eV/ų |
|---|---|---|---|
| MACE-MP small | -0.0762876 | -0.0762876 | — |
UMA uma-s-1p1 (omat) |
-0.0821809 | -0.0821810 | — |
| CHGNet standalone 0.4.2 | -13.906347 | -0.0867966 | — |
MatGL TensorNet-PES-MatPES-PBE-2025.2 |
-10.780773 | -10.780773 | -0.067288 |
MatGL CHGNet-PES-MatPES-PBE-2025.2.10 |
— | -15.229350 | -0.095054 |
MatGL M3GNet-PES-MatPES-2025.2 |
— | -20.293510 | -0.126662 |
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.
- 4d ago First seen · 160 lines · 30 tokens per session scan A 4a5dd9579786
general-property-units is a skill published in the GitHub repository learningmatter-mit/AtomisticSkills (158 stars, last pushed today), licensed MIT. It adds 30 tokens to every session and 2,296 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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