Install the "mat-dielectric-response" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-dielectric-response into .claude/skills/mat-dielectric-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-dielectric-response", 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-dielectric-response -a codex
Project install goes to .agents/skills/; add -g for ~/.codex/skills/.
Install the "mat-dielectric-response" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-dielectric-response into .agents/skills/mat-dielectric-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-dielectric-response", 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-dielectric-response -a cursor
Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.
Install the "mat-dielectric-response" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-dielectric-response into .cursor/skills/mat-dielectric-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-dielectric-response", 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-dielectric-response -a gemini-cli
Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.
Install the "mat-dielectric-response" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-dielectric-response into .gemini/skills/mat-dielectric-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-dielectric-response", 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-dielectric-response -a github-copilot
Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.
Install the "mat-dielectric-response" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-dielectric-response into .github/skills/mat-dielectric-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-dielectric-response", 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-dielectric-response -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-dielectric-response" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-dielectric-response into .opencode/skills/mat-dielectric-response/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-dielectric-response", 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-dielectric-response
GitHub stars
176
Token cost
~1.5k tokens
SKILL.md length
478 words
Files
4 (incl. scripts)
Skills in repo
129
Repo updated
First seen
Licence
MIT
At a glance
Calculate frequency-dependent dielectric response using atomate2 OpticsMaker and VASP.
Works in 4 steps: Obtain or Prepare the Input Structure → Run the Optics Workflow → Post-Process and Visualize Results → …
SKILL.md covers Goal, Instructions, Examples and Constraints
Runs Python scripts from its folder
What it does
Mat Dielectric Response is an agent skill from learningmatter-mit/AtomisticSkills. Calculate frequency-dependent dielectric response using atomate2 OpticsMaker and VASP.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts (for example `examples/README.md` and `scripts/plot_dielectric.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-dielectric-response”
Requirements
Python 3
Workflow steps
4 steps, taken from the step headings in SKILL.md.
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 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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 Dielectric Response loads about 1.5k tokens when it runs. Until then it costs about 28 tokens; SKILL.md has 478 words of instructions outside code blocks.
Always· name and description, kept in context so the agent knows when to use it
~28
When it runs· the whole SKILL.md, loaded when a task matches
~1.5k
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-dielectric-response/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
mat-dielectric-response
description
Calculate frequency-dependent dielectric response using atomate2 OpticsMaker and VASP.
metadata.category
materials
metadata.venv
cpu
Dielectric Response
<!-- mcp-tools-note -->
[!NOTE]
Steps written server.tool are MCP tool calls: base.search_materials_project_by_formula is the search_materials_project_by_formula
tool of the base server (mcp__base__search_materials_project_by_formula, or
mcp__plugin_atomistic-skills_base__search_materials_project_by_formula 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:
bash
${CLAUDE_SKILL_DIR}/../../venv/run cpu python -m src.mcp_server.cli base search_materials_project_by_formula key=value
${CLAUDE_SKILL_DIR}/../../venv/run cpu python -m src.mcp_server.cli atomate2 run_atomate2_vasp_calculation key=value
Goal
To calculate the frequency-dependent dielectric response of a crystalline material using atomate2's OpticsMaker and VASP. This includes:
The independent-particle real and imaginary dielectric functions
Optical spectra written by the VASP optics workflow
Post-processing and visualization of the dielectric response
This skill is based on atomate2's optics workflow, which is a flow maker analogous to the band structure workflow.
Instructions
1. Obtain or Prepare the Input Structure
Start with a well-relaxed crystalline structure in CIF or POSCAR format. You can:
[!IMPORTANT]
The optics workflow assumes a good relaxed bulk structure. Relax the structure first if needed; poor structures will give unreliable optical spectra.
2. Run the Optics Workflow
Use the atomate2 MCP tool with calculation_type="optics":
If you want to inspect the raw VASP outputs directly, check:
vasprun.xml or vasprun.xml.gz
OUTCAR
Search OUTCAR for:
frequency dependent IMAGINARY DIELECTRIC FUNCTION
frequency dependent REAL DIELECTRIC FUNCTION
MACROSCOPIC STATIC DIELECTRIC TENSOR
If you need the static dielectric tensor rather than the frequency-dependent spectrum, search OUTCAR for MACROSCOPIC STATIC DIELECTRIC TENSOR.
Examples
Silicon Carbide Optical Dielectric Response
python
# 1. Prepare a relaxed SiC structure
# 2. Run optics workflow
atomate2.run_atomate2_vasp_calculation(
structures_path="SiC.cif",
output_dir="./SiC_optics",
calculation_type="optics",
preset_type="omat",
config={
"NBANDS": 64,
"NEDOS": 2000,
"CSHIFT": 0.1,
},
execution_mode="local"
)
# 3. Plot results
${CLAUDE_SKILL_DIR}/../../venv/run cpu python ${CLAUDE_SKILL_DIR}/scripts/plot_dielectric.py \
SiC_optics \
--output SiC_dielectric.png \
--mode average
See examples/ for a SiC dielectric-response tutorial and example plot.
Constraints
Structure Requirements: Input must be a well-relaxed crystalline structure.
Workflow Scope: This skill covers atomate2's OpticsMaker workflow for the frequency-dependent dielectric function.
Local-Field Effects: Advanced manual ALGO=CHI local-field corrections are not part of the atomate2 optics workflow documented here.
VASP Setup: Requires properly configured VASP and pseudopotentials.
Atomate2 Setup: Requires atomate2, jobflow, and either local or remote execution configuration.
Environments:
Optics calculation: cpu
Post-processing scripts: cpu
Convergence:
Increase NBANDS until the optical spectrum is converged over the energy range of interest
Check sensitivity to NEDOS, CSHIFT, and k-point density
Band-Gap Limitation: Semi-local DFT typically underestimates the absorption onset; use hybrid functionals or beyond-DFT methods for quantitative spectra.
Mat Dielectric Response 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 Dielectric Response compared with similar skills
Skill
Stars
Used in
Tokens
Auto-check
Licence
Repo updated
Mat Dielectric Response 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 frequency-dependent dielectric response using atomate2 OpticsMaker and VASP. Mat Dielectric Response is an agent skill from learningmatter-mit/AtomisticSkills. Calculate frequency-dependent dielectric response using atomate2 OpticsMaker and VASP.
How do I install Mat Dielectric Response in Claude Code?
Run `npx skills add learningmatter-mit/AtomisticSkills --skill mat-dielectric-response -a claude-code`. Or copy the skill folder (skills/mat-dielectric-response in learningmatter-mit/AtomisticSkills) into .claude/skills/mat-dielectric-response in your project. Claude Code loads it when a task matches its description.
How do I install Mat Dielectric Response in Codex?
Run `npx skills add learningmatter-mit/AtomisticSkills --skill mat-dielectric-response -a codex`. Or copy the skill folder (skills/mat-dielectric-response in learningmatter-mit/AtomisticSkills) into .agents/skills/mat-dielectric-response in your project. Codex loads it when a task matches its description.
Can I use Mat Dielectric Response 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-dielectric-response -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-dielectric-response, .gemini/skills/mat-dielectric-response, .github/skills/mat-dielectric-response and .opencode/skills/mat-dielectric-response in your project.
What does Mat Dielectric Response need to run?
Going by SKILL.md and its folder, Mat Dielectric Response needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Mat Dielectric Response access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Mat Dielectric Response 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 Dielectric Response use?
Mat Dielectric Response 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 Dielectric Response use?
About 1.5k tokens (SKILL.md is roughly 6.2k 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 Dielectric Response?
Skills that share tags, products or a category with Mat Dielectric Response: 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 Dielectric Response?
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.
