Install
openclaw skills install input-file-skillThis skill should be used when generating CP2K input drafts (.inp) for quantum chemistry calculations from local structure inputs. It is a documentation-driven skill that uses reference files to interpret requests, apply conservative defaults, and explain assumptions. The current documented workflow supports local .xyz structures.
openclaw skills install input-file-skillThis skill helps the user generate a CP2K input draft from:
The uploaded skill package is intentionally scoped to a local-only, documentation-driven workflow. It does not perform automatic retrieval from external structure databases such as PubChem or Materials Project, and it does not include Python runtime helper scripts in the uploaded version.
This skill should:
Use this skill when the user:
Do not use this skill to claim that a structure has been automatically retrieved from an online source. In the current uploaded package, external databases may be mentioned only as manual suggestions for where the user could obtain a structure.
Apply defaults silently when safe:
The skill should use the following reference files during decision-making:
references/cp2k-task-map.md
references/cp2k-kinds.md
references/cp2k-defaults.md
references/ambiguity-policy.md
These reference files are used as decision support within the skill instructions. In the uploaded skill package, they are not executed by local helper scripts.
Do NOT silently invent:
If such information is missing, either:
When handling a user request, the skill should follow this order:
Determine the request type:
Determine the system type:
Normalize the request into the standard CP2K job contract.
Use references/cp2k-task-map.md to map the request to:
Use references/cp2k-kinds.md to assign element-dependent basis/potential defaults.
Use references/cp2k-defaults.md to fill in remaining conservative defaults.
If ambiguity remains, apply references/ambiguity-policy.md.
Produce:
Every successful run should produce, at minimum:
The report should always include:
If a normalized intermediate representation is used during reasoning, it should be treated as an internal contract for the skill logic rather than a required user-facing artifact in the uploaded package.
When internal normalization is needed, use a JSON object with the following keys:
{
"task_type": "geometry_optimization",
"run_type": "GEO_OPT",
"system_type": "molecule",
"structure_file": "uploaded.xyz",
"periodicity": "NONE",
"charge": 0,
"multiplicity": 1,
"priority": "balanced",
"xc_functional": "PBE",
"basis_family": "DZVP-MOLOPT-GTH",
"potential_family": "GTH-PBE",
"scf_mode": "OT",
"kpoints_scheme": "GAMMA",
"cell_handling": "auto_vacuum_box",
"cutoff": 500,
"rel_cutoff": 60,
"eps_scf": 1.0e-6,
"max_scf": 100,
"optimizer": "BFGS",
"hardware": {
"type": "unknown",
"cores": null,
"memory_gb": null
},
"notes": [],
"defaults_applied": [
"task_type=geometry_optimization",
"run_type=GEO_OPT",
"periodicity=NONE",
"xc_functional=PBE",
"basis_family=DZVP-MOLOPT-GTH",
"potential_family=GTH-PBE",
"scf_mode=OT",
"kpoints_scheme=GAMMA",
"cell_handling=auto_vacuum_box",
"cutoff=500",
"rel_cutoff=60",
"eps_scf=1.0e-6",
"max_scf=100",
"optimizer=BFGS"
],
"review_required": []
}