Install the "mat-intercalation-voltage" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-intercalation-voltage into .claude/skills/mat-intercalation-voltage/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-intercalation-voltage", then confirm the skill loads.
Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
skills CLI
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-intercalation-voltage -a codex
Project install goes to .agents/skills/; add -g for ~/.codex/skills/.
Install the "mat-intercalation-voltage" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-intercalation-voltage into .agents/skills/mat-intercalation-voltage/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-intercalation-voltage", then confirm the skill loads.
Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-intercalation-voltage -a cursor
Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.
Install the "mat-intercalation-voltage" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-intercalation-voltage into .cursor/skills/mat-intercalation-voltage/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-intercalation-voltage", then confirm the skill loads.
Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
skills CLI
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-intercalation-voltage -a gemini-cli
Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.
Install the "mat-intercalation-voltage" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-intercalation-voltage into .gemini/skills/mat-intercalation-voltage/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-intercalation-voltage", then confirm the skill loads.
Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
skills CLI
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-intercalation-voltage -a github-copilot
Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.
Install the "mat-intercalation-voltage" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-intercalation-voltage into .github/skills/mat-intercalation-voltage/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-intercalation-voltage", then confirm the skill loads.
GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-intercalation-voltage -a opencode
OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
Install the "mat-intercalation-voltage" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-intercalation-voltage into .opencode/skills/mat-intercalation-voltage/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-intercalation-voltage", then confirm the skill loads.
OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
Skill name
mat-intercalation-voltage
GitHub stars
176
Token cost
~1.2k tokens
SKILL.md length
480 words
Files
11 (incl. scripts)
Skills in repo
129
Repo updated
First seen
Licence
MIT
At a glance
Calculate the average intercalation voltage of cathode materials using MLIPs.
Works in 5 steps: Prepare Structures → Select Foundation Potential → Relax Structures Using MCP Tools → …
SKILL.md covers Goal, Instructions, Available Metal Structures and Example, plus 1 more section
Runs Python scripts from its folder
What it does
Mat Intercalation Voltage is an agent skill from learningmatter-mit/AtomisticSkills. Calculate the average intercalation voltage of cathode materials using MLIPs.
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files, including scripts (for example `examples/LiFePO4/README.md`, `examples/LiFePO4/voltage_results.json` and `scripts/calculate_voltage.py`).
It works with Model Context Protocol. 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-intercalation-voltage”
Requirements
Python 3
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
1Prepare Structures
2Select Foundation Potential
3Relax Structures Using MCP Tools
4Extract Energies
5Calculate Voltage
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 2 files 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 Intercalation Voltage loads about 1.2k tokens when it runs. Until then it costs about 26 tokens; SKILL.md has 480 words of instructions outside code blocks.
Always· name and description, kept in context so the agent knows when to use it
~26
When it runs· the whole SKILL.md, loaded when a task matches
~1.2k
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.
Download SKILL.mdSave it as .claude/skills/mat-intercalation-voltage/SKILL.md (or your agent's skills folder). This skill also uses 10 other files; get the full folder from GitHub.
name
mat-intercalation-voltage
description
Calculate the average intercalation voltage of cathode materials using MLIPs.
metadata.category
materials
metadata.venv
cpu, mlip
Intercalation Voltage
<!-- mcp-tools-note -->
[!NOTE]
Steps written server.tool are MCP tool calls: mace.load_model is the load_model
tool of the mace server (mcp__mace__load_model, or
mcp__plugin_atomistic-skills_mace__load_model when installed as a plugin).
Without a connected server, run the same tools from the shell. Tools named in
one command share a process, so a model loaded by load_model stays loaded:
To calculate the average open-circuit voltage (OCV) of an intercalation cathode material (e.g., Li$_x$M$_y$O$_z$) by computing the energy difference between the fully intercalated (charged) and de-intercalated (discharged) states.
The average voltage $V$ is given by:
$$V = -\frac{E(\text{full}) - E(\text{empty}) - n \mu_{\text{metal}}}{n}$$
where $E$ is the total energy, $n$ is the number of intercalated ions, and $\mu_{\text{metal}}$ is the chemical potential per atom of the bulk metal.
Instructions
Prepare Structures:
Obtain the fully intercalated structure (e.g., LiFePO$_4$)
Create the de-intercalated structure by removing intercalating ions:
bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/remove_atoms.py \
LiFePO4.cif \
--remove Li \
--output FePO4.cif
Get the bulk metal structure from resources/ (e.g., Li_metal.cif)
Select Foundation Potential:
Choose an appropriate MLIP based on the system (see foundation-potentials.md). For cathode materials, MACE-MH-1 with matpes_r2scan head or CHGNet-MatPES-r2SCAN are recommended.
Relax Structures Using MCP Tools:
Load the model and relax all three structures:
bash
# Load the model (example with MACE)
mace.load_model(model_name="MACE-MH-1", task_name="matpes_r2scan")
# Relax full structure
mace.relax_structure(
structure_data="LiFePO4.cif",
output_dir="voltage_calc/full_relax"
)
# Relax empty structure
mace.relax_structure(
structure_data="FePO4.cif",
output_dir="voltage_calc/empty_relax"
)
# Relax bulk metal
mace.relax_structure(
structure_data="${CLAUDE_SKILL_DIR}/resources/Li_metal.cif",
output_dir="voltage_calc/metal_relax"
)
Extract Energies:
From each relaxation output directory, extract:
E_full: Energy from full_relax/result.json
E_empty: Energy from empty_relax/result.json
E_metal: Energy from metal_relax/result.json
n_metal: Number of atoms in the relaxed metal structure
n_ions: Count difference of intercalating ions between full and empty structures
Mat Intercalation Voltage 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 Intercalation Voltage compared with similar skills
Skill
Stars
Used in
Tokens
Auto-check
Licence
Repo updated
Mat Intercalation Voltage this skilllearningmatter-mit/AtomisticSkills
Walks through building MCP servers in Python or TypeScript that expose tools, resources and prompts to Claude, with templates, registration and testing.
Explains how to bundle Model Context Protocol servers in a Claude Code plugin, covering config files, stdio, SSE, HTTP and WebSocket server types, and authentication.
Required groundwork before any use_figma call: the rules and reference files for running JavaScript in a Figma file through the Plugin API without common failures.
Define a docking search box (center coordinates + box dimensions in Angstroms) from a co-crystal ligand, binding-site residues, or a saved JSON specification.
Calculate the average intercalation voltage of cathode materials using MLIPs. Mat Intercalation Voltage is an agent skill from learningmatter-mit/AtomisticSkills. Calculate the average intercalation voltage of cathode materials using MLIPs.
How do I install Mat Intercalation Voltage in Claude Code?
Run `npx skills add learningmatter-mit/AtomisticSkills --skill mat-intercalation-voltage -a claude-code`. Or copy the skill folder (skills/mat-intercalation-voltage in learningmatter-mit/AtomisticSkills) into .claude/skills/mat-intercalation-voltage in your project. Claude Code loads it when a task matches its description.
How do I install Mat Intercalation Voltage in Codex?
Run `npx skills add learningmatter-mit/AtomisticSkills --skill mat-intercalation-voltage -a codex`. Or copy the skill folder (skills/mat-intercalation-voltage in learningmatter-mit/AtomisticSkills) into .agents/skills/mat-intercalation-voltage in your project. Codex loads it when a task matches its description.
Can I use Mat Intercalation Voltage 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-intercalation-voltage -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-intercalation-voltage, .gemini/skills/mat-intercalation-voltage, .github/skills/mat-intercalation-voltage and .opencode/skills/mat-intercalation-voltage in your project.
What does Mat Intercalation Voltage need to run?
Going by SKILL.md and its folder, Mat Intercalation Voltage needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Mat Intercalation Voltage 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 Intercalation Voltage 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 Intercalation Voltage use?
Mat Intercalation Voltage 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 Intercalation Voltage use?
About 1.2k tokens (SKILL.md is roughly 5k 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 Intercalation Voltage?
Skills that share tags, products or a category with Mat Intercalation Voltage: MCP Server Builder (anthropics/skills, 180k stars), MCP Server Builder (shareAI-lab/learn-claude-code, 78k stars), MCP Integration for Plugins (anthropics/claude-plugins-official, 38k stars) and Figma use_figma Plugin API Rules (warpdotdev/warp, 65k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Mat Intercalation Voltage?
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.