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/mat-electrochemical-windownpx skills add learningmatter-mit/AtomisticSkills --skill mat-electrochemical-windowgit 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/mat-electrochemical-window)<a href="https://agentmods.dev/skills/learningmatter-mit/atomisticskills/mat-electrochemical-window"><img src="https://agentmods.dev/badge/skills/learningmatter-mit/atomisticskills/mat-electrochemical-window.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 | $0.00028 | $0.01339 |
| Opus 5 | $0.00014 | $0.00669 |
| Sonnet 5 | $0.00006 | $0.00268 |
| Haiku 4.5 | $0.00003 | $0.00134 |
Grade A, and why
mat-electrochemical-window scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Electrochemical Stability Window (ECW) Calculation
Goal
To determine the intrinsic electrochemical stability window (ECW) of a material, specifically bounding the reduction ($V_{\text{red}}$) and oxidation ($V_{\text{ox}}$) potentials against a mobile working ion (e.g., Li/Li+), using a standard zero-Kelvin phase diagram.
This explicitly implements the standard thermodynamic approach for solid electrolytes defined in: Zhu, Y., He, X. & Mo, Y. "Origin of Outstanding Stability in the Lithium Solid Electrolyte Materials: Insights from Thermodynamic Analyses Based on First-Principles Calculations". ACS Appl. Mater. Interfaces 7, 23685–23693 (2015).
[!TIP] Coupling with Stability: ECW calculation relies entirely on the same generic computed energies and
PhaseDiagramused for determining $E_{hull}$. You can uniquely combine this with the mat-stability skill to calculate both intrinsic thermodynamic stability and electrochemical stability in the same step using the same unified convex hull.
Methodology
The electrochemical stability window of a phase represents the voltage range over which it is thermodynamically stable against reduction by (e.g., lithiation) or oxidation (e.g., delithiation) of the target ion.
In pymatgen, this exact analytical bounding is extracted using PhaseDiagram.get_transition_chempots(mobile_element).
- Calculate Global Phase Diagram boundaries: For the composition of the target phase, identifying the critical chemical potentials ($\mu_{\text{Li}}$) where stable facets on the phase diagram intersect.
- Identify the stable Region: Evaluating an intermediary point in each discrete chemical potential band on the
GrandPotentialPhaseDiagramto check if the exact composition is structurally present on the extended hull. If the material is metastable (E_hull > 0), its intrinsic ECW is always exactly[0.0 V, 0.0 V]. - Reference Scale Conversion: The bounds are translated from absolute chemical potentials into voltages versus the pure standard state metal: $V = -(\mu_{\text{Li}} - \mu_{\text{Li, ref}})$.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- today First seen · 70 lines · 28 tokens per session scan A 486b0fb09d40
mat-electrochemical-window is a skill published in the GitHub repository learningmatter-mit/AtomisticSkills (158 stars, last pushed yesterday), licensed MIT. It adds 28 tokens to every session and 1,339 once invoked, about $0.0001 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 2026-09-03.
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