Energy Calculator
benchflow-ai/skillsbench
Calculate per-second RMS energy from audio files. An agent skill from benchflow-ai/skillsbench.
Calculate absolute solid Helmholtz free energy, and optional Gibbs free energy, with Frenkel-Ladd switching using portable MLIP wrappers on a pre-equilibrated periodic structure.
MITAuto-check passed
Install Mat Solid Free Energy
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-solid-free-energy -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills mat-solid-free-energy --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/mat-solid-free-energy .claude/skills/mat-solid-free-energy && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "mat-solid-free-energy" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-solid-free-energy into .claude/skills/mat-solid-free-energy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-solid-free-energy", 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.
$skill-installer install https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-solid-free-energyType 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.
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-solid-free-energy -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills mat-solid-free-energy --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/mat-solid-free-energy .agents/skills/mat-solid-free-energy && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "mat-solid-free-energy" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-solid-free-energy into .agents/skills/mat-solid-free-energy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-solid-free-energy", 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.
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-solid-free-energy -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills mat-solid-free-energy --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/mat-solid-free-energy .cursor/skills/mat-solid-free-energy && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "mat-solid-free-energy" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-solid-free-energy into .cursor/skills/mat-solid-free-energy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-solid-free-energy", 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.
$ gemini skills install https://github.com/learningmatter-mit/AtomisticSkills.git --path skills/mat-solid-free-energy--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-solid-free-energy -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills mat-solid-free-energy --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/mat-solid-free-energy .gemini/skills/mat-solid-free-energy && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "mat-solid-free-energy" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-solid-free-energy into .gemini/skills/mat-solid-free-energy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-solid-free-energy", 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.
$ gh skill install learningmatter-mit/AtomisticSkills mat-solid-free-energyInstalls 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).
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-solid-free-energy -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/mat-solid-free-energy .github/skills/mat-solid-free-energy && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "mat-solid-free-energy" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-solid-free-energy into .github/skills/mat-solid-free-energy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-solid-free-energy", 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.
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-solid-free-energy -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install learningmatter-mit/AtomisticSkills mat-solid-free-energy --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/mat-solid-free-energy .opencode/skills/mat-solid-free-energy && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "mat-solid-free-energy" agent skill from https://github.com/learningmatter-mit/AtomisticSkills/tree/main/skills/mat-solid-free-energy into .opencode/skills/mat-solid-free-energy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mat-solid-free-energy", 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-solid-free-energy- GitHub stars
- 175
- Token cost
- ~1.7k tokens
- SKILL.md length
- 644 words
- Files
- 4 (incl. scripts)
- Skills in repo
- 129
- Repo updated
- First seen
- Licence
- MIT
At a glance
Calculate absolute solid Helmholtz free energy, and optional Gibbs free energy, with Frenkel-Ladd switching using portable MLIP wrappers on a pre-equilibrated periodic structure.
- SKILL.md covers Goal, Prerequisites, Choosing a Foundation Potential and Preparing Inputs, plus 4 more sections
- Runs Python scripts from its folder
What it does
Mat Solid Free Energy is an agent skill from learningmatter-mit/AtomisticSkills. Calculate absolute solid Helmholtz free energy, and optional Gibbs free energy, with Frenkel-Ladd switching using portable MLIP wrappers on a pre-equilibrated periodic structure.
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts (for example `examples/Si_MACE/README.md` and `scripts/run_frenkel_ladd.py`).
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-solid-free-energy”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit 7f2d86d. 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
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 Solid Free Energy loads about 1.7k tokens when it runs. Until then it costs about 50 tokens; SKILL.md has 644 words of instructions outside code blocks.
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.
SKILL.md
The full file from learningmatter-mit/AtomisticSkills at commit 7f2d86d, republished under its MIT licence (© learningmatter-mit). 644 words, ~1,712 tokens.
Download SKILL.mdSave it as
.claude/skills/mat-solid-free-energy/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- mat-solid-free-energy
- description
- Calculate absolute solid Helmholtz free energy, and optional Gibbs free energy, with Frenkel-Ladd switching using portable MLIP wrappers on a pre-equilibrated periodic structure.
- metadata.category
- materials
- metadata.venv
- mlip
Solid Free Energy
This skill calculates the absolute free energy of a crystalline solid using Frenkel-Ladd switching, which is a specific form of Thermodynamic Integration (TI).
Thermodynamic integration computes the free energy difference between two states by integrating the derivative of the Hamiltonian along a continuous coupling path. In this skill, the path interpolates between a physical MLIP Hamiltonian (the target state) and a harmonic Einstein-crystal reference (where the exact absolute free energy is analytically known).
Goal
Compute the Helmholtz free energy $F$ of a pre-equilibrated periodic solid at a target temperature, and optionally the Gibbs free energy $G = F + PV$ if pressure is supplied.
Prerequisites
- A pre-equilibrated periodic solid structure in an ASE-readable format such as CIF or POSCAR.
- The transferable MLIP wrapper stack must be available in the target repo via
src.utils.mlips.loader.load_wrapper(...). - ASE and pymatgen are included in the
mlipandfairchemenvironments.
[!IMPORTANT] This skill only performs the Frenkel-Ladd free-energy workflow. It does not relax the structure, build a supercell, equilibrate the volume, perform alchemical switching, or apply center-of-mass corrections.
Choosing a Foundation Potential
Frenkel-Ladd switching is an MD-based free-energy method, so both energy and force stability matter.
[!IMPORTANT]
- Prefer materials models intended for PES or MD use, such as
MACE-OMAT-0-small,MACE-MH-1,CHGNet-MatPES-*, orTensorNet-MatPES-*.- Use smaller or faster models for long switching trajectories when practical.
- Avoid changing model family between preparation and Frenkel-Ladd unless you intentionally want a different free-energy reference.
Refer to the foundation-potentials skill for model selection guidance.
Preparing Inputs
This skill assumes the input structure is already appropriate for the target thermodynamic state point. For production workflows, the most useful upstream skills are:
- mat-db-mp: Retrieve a starting bulk crystal structure from Materials Project.
- mat-equation-of-state: Estimate an equilibrium cell volume and generate a better-relaxed starting point before finite-temperature sampling.
- mat-lammps-md: Equilibrate a larger periodic cell at the target temperature or pressure using the same MLIP family.
- mat-md-monitors: Check MD stability, thermostat behavior, volume drift, and equilibration while preparing the input trajectory.
- mat-phonon: Screen for imaginary modes or other vibrational-instability warnings before running an expensive free-energy workflow.
Calculation Workflow
Run the standalone Frenkel-Ladd script:
${CLAUDE_SKILL_DIR}/../../venv/run mlip python ${CLAUDE_SKILL_DIR}/scripts/run_frenkel_ladd.py \
--structure path/to/pre_equilibrated_structure.cif \
--name my_solid \
--calculator mace \
--model-name MACE-OMAT-0-small \
--temperature 300 \
--pressure-gpa 0.0 \
--output-dir research/my_folder/frenkel_laddShow full SKILL.md (295 more words)Show less
Key Parameters
--structure: Pre-equilibrated periodic solid at the target state point.--calculator: MLIP backend:mace,fairchem, ormatgl.--model-name: Model name or checkpoint path.--task-name: Optional task head for multitask models.--temperature: Temperature in K.--pressure-gpa: Optional pressure in GPa. If provided, the script also reports Gibbs free energy.--msd-equilibration-steps: NVT equilibration before MSD collection.--msd-production-steps: NVT production used to estimate per-atom spring constants.--equilibration-steps: Harmonic-reference equilibration between forward and backward switching.--switching-steps: Number of MD steps in each switching direction.--switching-type:linearorpolynomial. Default is the smootherpolynomialschedule.--record-interval: Record every N MD steps.
Default Production Settings
The script defaults are:
timestep_fs = 1.0thermostat_damping_fs = 100.0msd_equilibration_steps = 1000msd_production_steps = 10000equilibration_steps = 5000switching_steps = 25000switching_type = polynomialrecord_interval = 1symmetrize_spring_constants = True
Output Files
frenkel_ladd_results.json: Summary including Helmholtz free energy, optional Gibbs free energy, dissipated energy, calculator metadata, and settings.frenkel_ladd_traces.npz: Raw recorded arrays:lambda_stepsforward_energy_contributionsbackward_energy_contributionsspring_constantsmean_squared_displacement
input_structure.cif: Copy of the starting structure.final_structure.cif: Final structure after backward switching.
Example
See examples/Si_MACE/ for a minimal silicon example using MACE with reduced step counts for demonstration.
${CLAUDE_SKILL_DIR}/../../venv/run mlip python ${CLAUDE_SKILL_DIR}/scripts/run_frenkel_ladd.py \
--structure ${CLAUDE_SKILL_DIR}/examples/Si_MACE/Si.cif \
--name Si_demo \
--calculator mace \
--model-name MACE-OMAT-0-small \
--temperature 300 \
--msd-equilibration-steps 50 \
--msd-production-steps 200 \
--equilibration-steps 100 \
--switching-steps 500 \
--record-interval 5 \
--output-dir research/frenkel_ladd/Si_demo[!NOTE] The example is a smoke-test style demonstration. For production free-energy work, start from a genuinely pre-equilibrated structure and use the heavier default settings or stricter settings appropriate for your system.
Constraints
- Environment:
mlipfor MACE and MatGL/CHGNet modelsfairchemfor FairChem/UMA models
- Periodic solids only: This method is intended for bulk crystalline solids, not molecules or non-periodic clusters.
- Pre-equilibrated input required: The script assumes the supplied structure already represents the desired thermodynamic state point.
- Quality control: Inspect
abs(dissipated_energy) / num_atoms. Values much larger than about0.05 eV/atomsuggest poor switching reversibility and should be treated with caution. - Cost: Frenkel-Ladd calculations are expensive because they require long MD trajectories in both switching directions.
Author: Juno Nam Contact: GitHub @recisic
© learningmatter-mit, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (scripts) in skills/mat-solid-free-energy of learningmatter-mit/AtomisticSkills.
- SKILL.md
- examples/Si_MACE/README.md
- examples/Si_MACE/Si.cif
- scripts/run_frenkel_ladd.py
Open the folder on GitHubat commit 7f2d86d
Compare with similar skills
Mat Solid Free Energy 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Mat Solid Free Energy this skilllearningmatter-mit/AtomisticSkills | 175 | — | ~1.7k | Automated safety check: Pass | MIT | |
| Energy Calculatorbenchflow-ai/skillsbench | 1.8k | — | ~437 | Automated safety check: Pass | Apache-2.0 | |
| Optionsasgeirtj/system_prompts_leaks | 69k | — | ~918 | Automated safety check: Pass | CC0-1.0 | |
| Bio Free Energy CalculationsGPTomics/bioSkills | 1.2k | 1 repos | ~4.5k | Automated safety check: Pass | MIT | |
| Options PayoffHKUDS/Vibe-Trading | 35k | — | ~6.8k | Automated safety check: Pass | MIT | |
| Energy Procurementaffaan-m/ECC | 274k | 4 repos | ~7.4k | Automated safety check: Pass | Apache-2.0 |
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Questions about Mat Solid Free Energy
What does Mat Solid Free Energy do?
Calculate absolute solid Helmholtz free energy, and optional Gibbs free energy, with Frenkel-Ladd switching using portable MLIP wrappers on a pre-equilibrated periodic structure. Mat Solid Free Energy is an agent skill from learningmatter-mit/AtomisticSkills. Calculate absolute solid Helmholtz free energy, and optional Gibbs free energy, with Frenkel-Ladd switching using portable MLIP wrappers on a pre-equilibrated periodic structure.
How do I install Mat Solid Free Energy in Claude Code?
Run `npx skills add learningmatter-mit/AtomisticSkills --skill mat-solid-free-energy -a claude-code`. Or copy the skill folder (skills/mat-solid-free-energy in learningmatter-mit/AtomisticSkills) into .claude/skills/mat-solid-free-energy in your project. Claude Code loads it when a task matches its description.
How do I install Mat Solid Free Energy in Codex?
Run `npx skills add learningmatter-mit/AtomisticSkills --skill mat-solid-free-energy -a codex`. Or copy the skill folder (skills/mat-solid-free-energy in learningmatter-mit/AtomisticSkills) into .agents/skills/mat-solid-free-energy in your project. Codex loads it when a task matches its description.
Can I use Mat Solid Free Energy 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-solid-free-energy -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-solid-free-energy, .gemini/skills/mat-solid-free-energy, .github/skills/mat-solid-free-energy and .opencode/skills/mat-solid-free-energy in your project.
What does Mat Solid Free Energy need to run?
Going by SKILL.md and its folder, Mat Solid Free Energy needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Mat Solid Free Energy 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 Solid Free Energy 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 Solid Free Energy use?
Mat Solid Free Energy 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 Solid Free Energy use?
About 1.7k tokens (SKILL.md is roughly 6.8k 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 Solid Free Energy?
Skills that share tags, products or a category with Mat Solid Free Energy: Energy Calculator (benchflow-ai/skillsbench, 1.8k stars), Options (asgeirtj/system_prompts_leaks, 69k stars), Bio Free Energy Calculations (GPTomics/bioSkills, 1.2k stars) and Options Payoff (HKUDS/Vibe-Trading, 35k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Mat Solid Free Energy?
learningmatter-mit (a GitHub organization) maintains it in learningmatter-mit/AtomisticSkills, which has 175 GitHub stars. The repository holds 129 skills in this directory. The repository was last updated on October 6, 2026.
Source: learningmatter-mit/AtomisticSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.