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 skills add SFETNI/Deep-Matter-Chem-Skills --skill dft-phononsgit clone --depth 1 https://github.com/SFETNI/Deep-Matter-Chem-SkillsWrote 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/sfetni/deep-matter-chem-skills/dft-phonons)<a href="https://agentmods.dev/skills/sfetni/deep-matter-chem-skills/dft-phonons"><img src="https://agentmods.dev/badge/skills/sfetni/deep-matter-chem-skills/dft-phonons/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sfetni/deep-matter-chem-skills/dft-phonons"><img src="https://agentmods.dev/badge/skills/sfetni/deep-matter-chem-skills/dft-phonons.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00005 | $0.14646 |
| Opus 5 | $0.00003 | $0.07323 |
| Sonnet 5 | $0.00001 | $0.02929 |
| Haiku 4.5 | $0.00001 | $0.01465 |
Grade A, and why
dft-phonons 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 12d 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 — 972 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DFT Phonon Calculations
Description
This skill covers lattice dynamics from first principles: computing phonon dispersion curves, phonon density of states (PDOS), and thermal properties using the finite-displacement method (Phonopy + VASP/QE) and density functional perturbation theory (DFPT via Quantum ESPRESSO ph.x or VASP IBRION=7/8). It covers the full workflow from supercell construction and displaced-supercell DFT calculations through force constant extraction, acoustic sum rule enforcement, non-analytical corrections for polar materials, and phonon band structure post-processing. Invoke this skill when computing harmonic phonon properties, diagnosing dynamical instabilities, validating ML interatomic potentials against DFT phonons, or generating phonon reference data for materials databases.
Domain Context
Phonons are the quantum of lattice vibration. They are essential for predicting thermodynamic stability, heat capacity, thermal conductivity, electron-phonon coupling, and phase transitions. Two formally equivalent but practically distinct methods are used in DFT practice:
Finite-displacement (supercell) method: Construct symmetry-inequivalent displaced supercells → run DFT single-point calculations → extract forces → build real-space force constants → Fourier transform to get the dynamical matrix D(q) at arbitrary q-points → diagonalize to get phonon frequencies ω(q). Implemented by Phonopy, which is DFT-code-agnostic.
DFPT (Density Functional Perturbation Theory): Compute the response of the charge density to an atomic displacement as a perturbation at a given wavevector q directly, without supercells. Gives the dynamical matrix at specified q-points directly from a single calculation. Native to Quantum ESPRESSO (ph.x) and also available in VASP (IBRION=7/8). More expensive per q-point than finite displacement for a single structure but avoids the supercell approximation entirely.
Dynamical matrix: D_αβ(q) = (1/√(m_α m_β)) Σ_R Φ_αβ(0,R) e^{iq·R}, where Φ_αβ are the interatomic force constants (second derivatives of the total energy). Eigenvalues of D(q) give ω²(q,s) for each phonon branch s. Negative eigenvalues (imaginary frequencies) signal dynamical instability at that q-point.
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.
- 12d ago First seen · 972 lines · 5 tokens per session scan A 05bd4a73cbbd
dft-phonons is a skill published in the GitHub repository SFETNI/Deep-Matter-Chem-Skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 5 tokens to every session and 14,646 once invoked, about $0.0000 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 2026-08-31.
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