Model Bank Metadata
lobehub/lobehub
Fills and maintains the knowledgeCutoff, family and generation fields on model cards in LobeHub's model bank, from a single new model up to repo-wide backfills.
Choose and troubleshoot OpenMM force fields, model-building workflows, parameterized input formats, and ForceField XML authoring.
MITAuto-check passed
Install Force Fields Modeling
$ npx skills add VectorSpaceLab/AREX-Skill --skill force-fields-modeling -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill force-fields-modeling --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/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling .claude/skills/force-fields-modeling && 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 "force-fields-modeling" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling into .claude/skills/force-fields-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "force-fields-modeling", 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/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/openmm/sub-skills/force-fields-modelingType 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 VectorSpaceLab/AREX-Skill --skill force-fields-modeling -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill force-fields-modeling --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling .agents/skills/force-fields-modeling && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "force-fields-modeling" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling into .agents/skills/force-fields-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "force-fields-modeling", 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 VectorSpaceLab/AREX-Skill --skill force-fields-modeling -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill force-fields-modeling --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling .cursor/skills/force-fields-modeling && 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 "force-fields-modeling" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling into .cursor/skills/force-fields-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "force-fields-modeling", 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/VectorSpaceLab/AREX-Skill.git --path skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling--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 VectorSpaceLab/AREX-Skill --skill force-fields-modeling -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill force-fields-modeling --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling .gemini/skills/force-fields-modeling && 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 "force-fields-modeling" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling into .gemini/skills/force-fields-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "force-fields-modeling", 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 VectorSpaceLab/AREX-Skill force-fields-modelingInstalls 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 VectorSpaceLab/AREX-Skill --skill force-fields-modeling -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling .github/skills/force-fields-modeling && 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 "force-fields-modeling" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling into .github/skills/force-fields-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "force-fields-modeling", 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 VectorSpaceLab/AREX-Skill --skill force-fields-modeling -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill force-fields-modeling --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling .opencode/skills/force-fields-modeling && 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 "force-fields-modeling" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling into .opencode/skills/force-fields-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "force-fields-modeling", 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
force-fields-modeling- GitHub stars
- 328
- Token cost
- ~988 tokens
- SKILL.md length
- 388 words
- Files
- 6 (incl. scripts, references)
- Skills in repo
- 159
- Repo updated
- First seen
- Licence
- MIT
At a glance
Choose and troubleshoot OpenMM force fields, model-building workflows, parameterized input formats, and ForceField XML authoring.
- Works in 6 steps: Identify whether the inputs are… → Choose force-field XML files as a… → Use Modeller before createSystem() when… → …
- Working with ForceField.createSystem
- SKILL.md covers Route Here For, Start With These References, Practical Workflow and Bundled Script, plus 1 more section
- Runs Python scripts from its folder; calls python
What it does
Force Fields Modeling is an agent skill from VectorSpaceLab/AREX-Skill. Choose and troubleshoot OpenMM force fields, model-building workflows, parameterized input formats, and ForceField XML authoring. Use when working with ForceField.createSystem, Modeller, bundled force-field XML files, residue template failures, solvation/hydrogenation/membranes, AMBER/CHARMM/GROMACS/Tinker inputs, or ffxml validation.
Its SKILL.md is about 990 tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `references/forcefield-api-and-data.md`, `references/forcefield-xml-authoring.md` and `references/model-building-recipes.md`).
The repository describes itself as: A Skill Library for Automated Machine Learning. The licence is MIT.
When your agent uses it
- Working with ForceField.createSystem
- Bundled force-field XML files
- Residue template failures
- Solvation/hydrogenation/membranes
Example prompts
- “/force-fields-modeling”
Requirements
- Python 3
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Identify whether the inputs are coordinates plus topology needing a ForceField, or already-parameterized files such as AMBER prmtop…
- Choose force-field XML files as a compatible set: main biopolymer file plus the matching water/ion or implicit-solvent file when needed.
- Use Modeller before createSystem() when the topology lacks hydrogens, solvent, membranes, or force-field-required extra particles.
- Run forcefield.getUnmatchedResidues(topology) or forcefield.getMatchingTemplates(topology) before debugging a full simulation when…
- Build the System with createSystem() using nonbonded settings that match the topology: periodic boxes generally pair with PME/cutoffs…
- Keep production dynamics, integrator choice, reporter setup, and platform precision decisions in sibling sub-skills unless they directly…
What it can do on your machine
Read from SKILL.md and the folder at commit ac3fe1a. 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.
Shell commands in SKILL.md call:
python
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
Force Fields Modeling loads about 988 tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 90 tokens; SKILL.md has 388 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 VectorSpaceLab/AREX-Skill at commit ac3fe1a, republished under its MIT licence (© VectorSpaceLab). 388 words, ~988 tokens.
Download SKILL.mdSave it as
.claude/skills/force-fields-modeling/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.- name
- force-fields-modeling
- description
- Choose and troubleshoot OpenMM force fields, model-building workflows, parameterized input formats, and ForceField XML authoring. Use when working with ForceField.createSystem, Modeller, bundled force-field XML files, residue template failures, solvation/hydrogenation/membranes, AMBER/CHARMM/GROMACS/Tinker inputs, or ffxml validation.
- disable-model-invocation
- true
- metadata.disco-role
- operating
- license
- MIT, GPL, LGPL
Force Fields and Modeling
Use this sub-skill when a task is about preparing a molecular model or parameterizing it before a simulation in OpenMM.
Route Here For
- Selecting bundled OpenMM
ForceFieldXML files, compatible water/ion files, implicit solvent files, or polarizable force fields. - Calling
ForceField.createSystem()with correctnonbondedMethod, cutoff, constraints,rigidWater,hydrogenMass, residue template, and external-bond options. - Editing structures with
Modeller: add missing hydrogens, solvent, ions, membranes, extra particles, or remove incompatible water. - Diagnosing
No template found for residueand related residue-template, terminal variant, water-model, bond, or extra-particle mismatches. - Loading parameterized inputs from AMBER, CHARMM, GROMACS, or Tinker instead of using
ForceFieldXML directly. - Authoring or validating practical OpenMM force-field XML (
ffxml) files and residue template generators.
Start With These References
references/forcefield-api-and-data.mdforForceField, bundled XML families,createSystem()options, and AMBER/CHARMM/GROMACS/Tinker input routes.references/model-building-recipes.mdforModellerworkflows: hydrogens, solvent, ions, water conversion, membranes, and extra particles.references/forcefield-xml-authoring.mdfor ffxml structure, residue templates, patches, standard force tags, custom force wiring, and template generators.references/troubleshooting.mdfor template mismatch diagnosis, water/ion compatibility, periodic-box and include-path problems.
Practical Workflow
- Identify whether the inputs are coordinates plus topology needing a
ForceField, or already-parameterized files such as AMBERprmtop, CHARMMpsf, GROMACStop, or Tinkerxyz/key/prm. - Choose force-field XML files as a compatible set: main biopolymer file plus the matching water/ion or implicit-solvent file when needed.
- Use
ModellerbeforecreateSystem()when the topology lacks hydrogens, solvent, membranes, or force-field-required extra particles. - Run
forcefield.getUnmatchedResidues(topology)orforcefield.getMatchingTemplates(topology)before debugging a full simulation when template matching is uncertain. - Build the
SystemwithcreateSystem()using nonbonded settings that match the topology: periodic boxes generally pair withPME/cutoffs; implicit solvent supports only non-periodic or limited cutoff choices. - Keep production dynamics, integrator choice, reporter setup, and platform precision decisions in sibling sub-skills unless they directly affect model parameterization.
Show full SKILL.md (86 more words)Show less
Bundled Script
Use scripts/forcefield_modeling_check.py as a lightweight smoke check for an OpenMM installation and a minimal force-field/model-building path. It builds a tiny in-memory water topology, verifies template matching, creates a System, and prints a JSON summary without requiring source checkout files.
python scripts/forcefield_modeling_check.pyBoundaries
- For running or restarting complete simulations, use
simulation-workflows. - For custom mathematical force expressions or custom integrator algorithms beyond ffxml wiring, use
custom-forces-integrators. - For CUDA/OpenCL/HIP/CPU platform selection, precision, and performance tuning, use
platforms-performance. - For modifying OpenMM internals, plugins, C++ extension development, or tests, use
development-extensions.
© VectorSpaceLab, 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 5 other files (scripts, references) in skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling of VectorSpaceLab/AREX-Skill.
- SKILL.md
- references/forcefield-api-and-data.md
- references/forcefield-xml-authoring.md
- references/model-building-recipes.md
- references/troubleshooting.md
- scripts/forcefield_modeling_check.py
Open the folder on GitHubat commit ac3fe1a
Compare with similar skills
Force Fields Modeling 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 |
|---|---|---|---|---|---|---|
| Force Fields Modeling this skillVectorSpaceLab/AREX-Skill | 328 | — | ~988 | Automated safety check: Pass | MIT | |
| Model Bank Metadatalobehub/lobehub | 83k | — | ~2k | Automated safety check: Pass | Custom licence | |
| Choosing Openmed Modelsmaziyarpanahi/openmed | 5.5k | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| OmniRoute Model Catalogdiegosouzapw/OmniRoute | 74k | 1 repos | ~589 | Automated safety check: Pass | MIT | |
| Harness Threat Modelruvnet/ruflo | 74k | — | ~363 | Automated safety check: Notes | MIT | |
| OmniRoute Model Catalog CLIdiegosouzapw/OmniRoute | 74k | — | ~554 | Automated safety check: Pass | MIT |
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Looks up which AI models an OmniRoute gateway can reach, creates or updates model aliases and tests whether individual models respond.
Harness Threat Model
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OmniRoute Model Catalog CLI
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Threat Modeling
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Questions about Force Fields Modeling
What does Force Fields Modeling do?
Choose and troubleshoot OpenMM force fields, model-building workflows, parameterized input formats, and ForceField XML authoring. Force Fields Modeling is an agent skill from VectorSpaceLab/AREX-Skill. Choose and troubleshoot OpenMM force fields, model-building workflows, parameterized input formats, and ForceField XML authoring.
When should I use Force Fields Modeling?
Force Fields Modeling fits situations like: working with ForceField.createSystem; bundled force-field XML files; residue template failures; solvation/hydrogenation/membranes.
How do I install Force Fields Modeling in Claude Code?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill force-fields-modeling -a claude-code`. Or copy the skill folder (skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling in VectorSpaceLab/AREX-Skill) into .claude/skills/force-fields-modeling in your project. Claude Code loads it when a task matches its description.
How do I install Force Fields Modeling in Codex?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill force-fields-modeling -a codex`. Or copy the skill folder (skills/repositories/repo-skills/openmm/sub-skills/force-fields-modeling in VectorSpaceLab/AREX-Skill) into .agents/skills/force-fields-modeling in your project. Codex loads it when a task matches its description.
Can I use Force Fields Modeling 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 VectorSpaceLab/AREX-Skill --skill force-fields-modeling -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/force-fields-modeling, .gemini/skills/force-fields-modeling, .github/skills/force-fields-modeling and .opencode/skills/force-fields-modeling in your project.
What does Force Fields Modeling need to run?
Going by SKILL.md and its folder, Force Fields Modeling needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Force Fields Modeling 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 Force Fields Modeling 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 Force Fields Modeling use?
Force Fields Modeling is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Force Fields Modeling use?
About 988 tokens (SKILL.md is roughly 4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 9.7k tokens, read only when the agent opens those files.
What are the alternatives to Force Fields Modeling?
Skills that share tags, products or a category with Force Fields Modeling: Model Bank Metadata (lobehub/lobehub, 83k stars), Choosing Openmed Models (maziyarpanahi/openmed, 5.5k stars), OmniRoute Model Catalog (diegosouzapw/OmniRoute, 74k stars) and Harness Threat Model (ruvnet/ruflo, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Force Fields Modeling?
VectorSpaceLab (a GitHub organization) maintains it in VectorSpaceLab/AREX-Skill, which has 328 GitHub stars. The repository holds 159 skills in this directory. The repository was last updated on September 3, 2026.
Source: VectorSpaceLab/AREX-Skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.