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This skill should be used when users ask to prepare MaxwellLink input files; it scaffolds a new `projects/YYYY-MM-DD-NAME/` folder from copy-ready templates and provides basic validation.
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Guide users through setting up and running scientific simulations with FermiLink after `pip install fermilink` and `fermilink init`. Covers package installation, provider setup, execution modes, HPC configuration, and workflow selection.
Generate a Sphinx-ready report bundle (plots, RST, contract, per-accepted-commit pages) from a completed `fermilink optimize` workspace. Use when the user asks to visualize, export, or publish optimization results from a `.fermilink-optimize` directory, or wants to prepare material for the Project Optimization website.
Write, review, or strengthen `goal.md` files for `fermilink optimize` across Python, C/C++, and Fortran packages. Use when defining target scope, scientific correctness constraints, representative workloads, build commands, or staged workload-input files for goal mode.
This skill should be used when users need the canonical MaxwellLink workflow, including socket vs embedded coupling, units/time handling, and MPI/HPC invariants.
This skill should be used when users ask to bootstrap or regenerate a `skills/` folder for a scientific software package (for example LAMMPS, PSI4, GROMACS, Q-Chem docs-only, MEEP, or similar) from docs/source/tests/tutorial layouts, with documentation-first routing and an abstract skill count capped around 30.
This skill should be used when users need to run MaxwellLink in SLURM/HPC environments, including dependent job patterns and robust socket host/port handoff.
| name | mxl-project-scaffold |
| description | This skill should be used when users ask to prepare MaxwellLink input files; it scaffolds a new `projects/YYYY-MM-DD-NAME/` folder from copy-ready templates and provides basic validation. |
YYYY-MM-DD-NAME under projects/.skills/mxl-project-scaffold/assets/templates/ into the new project directory.python skills/mxl-project-scaffold/scripts/mxl_scaffold_project.py --listpython skills/mxl-project-scaffold/scripts/mxl_scaffold_project.py --template meep-tls-embedded --name tls-coherent-meep-2d-vacuumconfig.json and README.md before running.python skills/mxl-project-scaffold/scripts/mxl_validate_project.py projects/YYYY-MM-DD-NAMEmeep-tls-embedded: Meep FDTD + embedded TLS, writes tls_history.csvmeep-tls-socket-unix: Meep FDTD + TLS driver over UNIX socket (local multi-process)singlemode-tls-socket-tcp: SingleModeSimulation + TLS over TCP (fast socket workflow)laser-tls-embedded: LaserDrivenSimulation + embedded TLS (prescribed field)slurm-meep-tls-tcp: SLURM two-step main+driver jobs over TCP (multi-node pattern), writes tcp_host_port_info.txtslurm-meep-lammps-tcp: SLURM two-step Meep+LAMMPS (fix mxl) jobs over TCP, patches in_mxl.lmp and runs lmp_mxlslurm-meep-plasmon-rteh-tcp: SLURM two-step 3D plasmonic Meep + multi-molecule Psi4 RT-Ehrenfest drivers over TCP (adapted from meep_plasmon_HCN_excitation_rteh_strong)