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-electronic-structurenpx skills add learningmatter-mit/AtomisticSkills --skill mat-electronic-structuregit 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-electronic-structure)<a href="https://agentmods.dev/skills/learningmatter-mit/atomisticskills/mat-electronic-structure"><img src="https://agentmods.dev/badge/skills/learningmatter-mit/atomisticskills/mat-electronic-structure.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 | $0.00022 | $0.01824 |
| Opus 5 | $0.00011 | $0.00912 |
| Sonnet 5 | $0.00004 | $0.00365 |
| Haiku 4.5 | $0.00002 | $0.00182 |
Grade A, and why
mat-electronic-structure scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Electronic Structure
Goal
To calculate the electronic band structure of a crystalline material, revealing the energy-momentum relationship for electrons and determining whether the material is metallic, semiconducting, or insulating. This includes computing the band gap ($E_g$), identifying direct vs. indirect transitions, and visualizing the dispersion along high-symmetry k-paths.
Instructions
1. Obtain or Prepare the Input Structure
Start with a relaxed crystalline structure in CIF or POSCAR format. You can:
- Search Materials Project using the
mcp_base_search_materials_project_by_formulatool - Use a structure from previous calculations
- Create a structure manually using pymatgen or ASE
2. Run Band Structure Calculation
Use the atomate2 MCP tool with calculation_type="band_structure":
mcp_atomate2_run_atomate2_vasp_calculation(
structures_path="structure.cif", # Input structure file
output_dir="./band_structure_results", # Output directory
calculation_type="band_structure", # Band structure calculation
bandstructure_mode="line", # Options: "line", "uniform", "both"
preset_type="omat", # VASP preset (omat, mp, matpes-pbe, matpes-r2scan)
execution_mode="remote", # "local" or "remote"
remote_settings={ # Required for remote execution
"project": "remote_perlmutter",
"worker": "perlmutter_worker"
}
)
Band structure modes:
"line": Calculate along high-symmetry k-paths (for band structure plots)"uniform": Calculate on a uniform k-mesh (for density of states)"both": Perform both line and uniform calculations
The workflow automatically:
- Runs a static SCF calculation to obtain the charge density
- Runs a non-SCF calculation to compute band structure eigenvalues
Alternative: Retrieve Pre-Computed Data from Materials Project
What ships with it
6 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 · 208 lines · 22 tokens per session scan A e4055c868b76
mat-electronic-structure is a skill published in the GitHub repository learningmatter-mit/AtomisticSkills (158 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 1,824 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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