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-dft-mixing-functionalsnpx skills add learningmatter-mit/AtomisticSkills --skill mat-dft-mixing-functionalsgit 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-dft-mixing-functionals)<a href="https://agentmods.dev/skills/learningmatter-mit/atomisticskills/mat-dft-mixing-functionals"><img src="https://agentmods.dev/badge/skills/learningmatter-mit/atomisticskills/mat-dft-mixing-functionals.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 | $0.00025 | $0.01108 |
| Opus 5 | $0.00013 | $0.00554 |
| Sonnet 5 | $0.00005 | $0.00222 |
| Haiku 4.5 | $0.00003 | $0.00111 |
Grade A, and why
mat-dft-mixing-functionals 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MP2020 Compatibility
Goal
To apply Materials Project 2020 Compatibility schemes to MLIP-predicted energies. This is required for models trained on GGA/GGA+U mixed data (e.g., MPtrj data) when constructing convex hulls or phase diagrams to ensure compatibility with the Materials Project database.
[!IMPORTANT] Do NOT apply this to r2SCAN models. Only use this for models trained on GGA/GGA+U mixed data.
Scientific Context
Why is this needed?
The Materials Project (MP) database mixes calculations from two levels of theory: GGA (PBE) and GGA+U. Transition metals (e.g., Mn, Fe, Co, Ni) are calculated with a Hubbard U correction only when present in oxides or fluorides; otherwise, they use standard PBE. To construct a unified convex hull, MP applies the MP2020 Compatibility scheme (energy shifts) to align these distinct potential energy surfaces.
MLIPs trained on MP data (e.g., MACE-MP-0) typically learn these mixed energies. To accurately predict stability against the MP hull, one must apply the same MP2020 corrections to the MLIP outputs.
Potential Issues
Selective application of U introduces discontinuities in the Potential Energy Surface (PES) that are difficult for MLIPs to model physically.
- Artifacts: Models may exhibit spurious repulsion or underbinding between U-corrected metals and ligands, as they interpolate between incompatible GGA and GGA+U regimes.
References
- MP2020 Framework: Wang, A., Kingsbury, R., McDermott, M. et al. A framework for quantifying uncertainty in DFT energy corrections. Sci Rep 11, 15496 (2021). DOI
- Impact on MLIPs: Better without U: Impact of Selective Hubbard U Correction on Foundational MLIPs. arXiv:2601.21056 (2026). link
Compatible Models
This correction is REQUIRED for:
- MACE-MH-1
omat_pbehead (default) - MACE-MH-0
omat_pbehead - MACE-OMAT-0-small, MACE-OMAT-0-medium
- MACE-MP-small, MACE-MP-medium, MACE-MP-large
- M3GNet-MP-2021.2.8-PES
- M3GNet-MP-2021.2.8-DIRECT-PES
- uma-s-1, uma-s-1p1, uma-m-1p1 (with
omathead)
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 · 84 lines · 25 tokens per session scan A 211076551f14
mat-dft-mixing-functionals is a skill published in the GitHub repository learningmatter-mit/AtomisticSkills (158 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 1,108 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.
Other skills, from other repositories
cd-calculator
Python calculators for geometry analysis, structural checking, solar calculations, panel optimization, mesh analysis, material estimation, and fabrication cost estimation for AEC computational design.
cd-calculator
Python calculators for geometry analysis, structural checking, solar calculations, panel optimization, mesh analysis, material estimation, and fabrication cost estimation for AEC computational design.
prepared-environment-designer
Redesign a classroom as a prepared environment optimised for independent learning, calm transitions, and material access. Use when classroom layout hinders independence or self-directed work.
gamedev-shaders
Use when authoring or debugging a shader, material, VFX, or full-screen post-process in a game engine — Godot 4.x .gdshader, Unity 6 URP/HDRP, Unreal 5.x Materials, effect recipes, shader performance. NOT gameplay or engine-API code (that is godot/unity/unreal), NOT physics (gamedev-physics), NOT build variant…
technical-artist
!cat skills/shared/protocols/3d-spatial-foundations.md 2>/dev/null || echo "=== 3D Foundations not loaded ===".
unity-shader-artist
!cat skills/shared/game-visual-foundations.md 2>/dev/null || echo "=== Visual Foundations not loaded ===" !cat skills/shared/protocols/ux-protocol.md 2>/dev/null || true !cat skills/shared/protocols/game-test-protocol.md 2>/dev/null || true !cat skills/shared/protocols/quality-gate.md 2>/dev/null || true !cat…