diff --git a/doc/agent-skills.md b/doc/agent-skills.md new file mode 100644 index 0000000000..a78631d445 --- /dev/null +++ b/doc/agent-skills.md @@ -0,0 +1,82 @@ +# Agent Skills + +DeePMD-kit provides official [Agent Skills](https://agentskills.io/what-are-skills) that help AI agents run +DeePMD-kit workflows in a reproducible way. These skills capture +project-specific operating knowledge—such as training inputs, model +deployment, LAMMPS integration, and Python inference patterns—so an agent can +turn a high-level request into concrete files, commands, and validation steps. + +The DeePMD-kit skills were initially developed in the +[Computational Chemistry Agent Skills](https://github.com/jinzhezenggroup/computational-chemistry-agent-skills) +project as part of the work described below. They are now maintained directly +in the DeePMD-kit repository under `skills/`. + +## List of skills + +- `deepmd-train-dpa3`: Train DeePMD-kit models with the DPA3 descriptor and the + PyTorch backend, including input generation, neighbor-selection choices, + training, freezing, and testing. +- `deepmd-finetune-dpa3`: Fine-tune DPA3 models from self-trained checkpoints, + multi-task pretrained models, or built-in models downloaded by `dp pretrained download`. +- `deepmd-train-se-e2-a`: Train classical Deep Potential models with the + `se_e2_a` descriptor, including preparation of training JSON files and + post-training validation. +- `deepmd-python-inference`: Run Python and CLI inference with trained or + frozen DeePMD-kit models, including energy, force, virial, descriptor, and + model-deviation workflows. +- `lammps-deepmd`: Prepare, explain, and run LAMMPS simulations with DeePMD-kit + potentials, including common NVE, NVT, and NPT setups. + +## Related reference + +The DeePMD-kit skills were originally developed as part of the following +paper: + +- Mingwei Ding, Chen Huang, Yibo Hu, Yifan Li, Zitian Lu, Xingtai Yu, Duo + Zhang, Wenxi Zhai, Tong Zhu, Qiangqiang Gu, and Jinzhe Zeng. [Automating + Computational Chemistry Workflows via OpenClaw and Domain-Specific + Skills](https://doi.org/10.1021/acs.jctc.6c00622). *Journal + of Chemical Theory and Computation*, 2026. + +## Install skills + +### If you are a user + +The easiest way is to send this page to your agent and ask it to install the +skills for you. Users usually do not need to perform manual installation. + +### If you are an agent + +If you already have a DeePMD-kit checkout, run this command from the repository +root: + +```bash +npx -y skills add ./skills -a openclaw -y +``` + +If you do not have a checkout, the same skills can also be installed directly +from GitHub: + +```bash +npx -y skills add https://github.com/deepmodeling/deepmd-kit/tree/master/skills \ + -a openclaw -y +``` + +The examples above require Node.js/npm so that `npx` is available, and they +install the skills for OpenClaw. Replace `openclaw` with the target agent name +when installing for another agent. The GitHub command lets the skill CLI fetch +the repository for you. For large repositories or slow networks, this can take +longer than installing from an existing local checkout. Refresh or restart the +session afterward so the installed skills are reloaded. + +## Minimal verification + +Ask the agent to perform a small task that exercises the installed skill +without launching an expensive calculation. For example: + +- “Use the `deepmd-python-inference` skill to write a minimal Python snippet + for loading a frozen DeePMD-kit model and evaluating one frame.” +- “Use the `deepmd-train-dpa3` skill to draft a small DPA3 training input for a + water dataset, but do not start training.” +- “Use the `lammps-deepmd` skill to prepare an NVT LAMMPS input file for a + DeePMD-kit model, and explain each command.” diff --git a/doc/index.rst b/doc/index.rst index 238dc0d25d..d914782247 100644 --- a/doc/index.rst +++ b/doc/index.rst @@ -45,6 +45,7 @@ DeePMD-kit is a package written in Python/C++, designed to minimize the effort r inference/index cli third-party/index + agent-skills nvnmd/index env troubleshooting/index