xTB

Use this skill as the top-level xTB orchestration layer.

Scope

This skill should:

• identify whether the user wants direct xTB usage or a Python bridge workflow
• classify the task as static, optimization, or MD-style usage
• keep xTB as the primary method in the user-facing framing
• provide runnable examples for direct Python/ASE integration when appropriate
• document how to connect xTB to dpdata driver/minimizer flows

This skill should not:

• force the user into ASE if they asked for xTB itself
• hide xTB-specific scientific choices behind generic backend wording
• submit jobs directly; use dpdisp-submit if execution/submission is requested

Supported usage patterns

1. Direct xTB-oriented tasks

Use this skill when the user asks for:

• xTB single-point energy
• xTB forces / charges / dipole
• xTB geometry optimization
• xTB molecular dynamics
• xTB method choice such as GFN0-xTB, GFN1-xTB, or GFN2-xTB
• xTB solvent settings

2. xTB through the ASE bridge

If the user wants Python scripting, ASE integration, or ASE workflows, use:

from xtb.ase.calculator import XTB

Treat ASE as an integration layer, not the primary identity of the method.

3. xTB through dpdata

If the user wants labeled data or geometry minimization through dpdata, bridge via the ASE driver/minimizer while still presenting xTB as the force/energy method.

Practical installation notes

For one-off Python scripts, prefer uv run instead of uvx because this is a Python package used inside a Python script, not a standalone CLI tool.

Recommended pattern for the ASE bridge:

uv run --no-project --with ase --with xtb --with typing_extensions python your_script.py

Notes:

• The PyPI package name is xtb.
• The upstream docs/project are often referred to as xtb-python.
• If ModuleNotFoundError: typing_extensions appears, add --with typing_extensions explicitly.

Method selection guidance

• GFN2-xTB: default choice for most molecular single-point and force evaluations
• GFN1-xTB: use when there is a user or literature reason
• GFN0-xTB: use when the workflow specifically needs xTB-level stress through the ASE bridge

Detailed runnable examples

For copy-paste-ready command and script patterns, see:

• references/commands-and-workflow.md

Use that reference when the user specifically wants a minimal runnable example for:

• single-point energy / forces
• geometry optimization
• dpdata driver labeling
• dpdata minimization

ASE bridge example

from ase.build import molecule
from xtb.ase.calculator import XTB

atoms = molecule("H2O")
atoms.calc = XTB(method="GFN2-xTB")
print(atoms.get_potential_energy())
print(atoms.get_forces())
print(atoms.get_charges())

Common calculator arguments:

• method
• accuracy
• electronic_temperature
• max_iterations
• solvent
• cache_api

Property support through the ASE bridge includes:

• energy / free_energy
• forces
• dipole
• charges
• stress for GFN0-xTB only

dpdata driver bridge

If the user wants dpdata labeling:

from dpdata.system import System
from xtb.ase.calculator import XTB

sys = System("input.xyz", fmt="xyz")
ls = sys.predict(driver="ase", calculator=XTB(method="GFN2-xTB"))

This connects naturally to tools/dpdata-driver.

dpdata minimizer bridge

If the user wants dpdata geometry minimization:

from dpdata.driver import Driver
from dpdata.system import System
from xtb.ase.calculator import XTB

sys = System("input.xyz", fmt="xyz")
ase_driver = Driver.get_driver("ase")(calculator=XTB(method="GFN2-xTB"))
ls = sys.minimize(minimizer="ase", driver=ase_driver, fmax=0.05, max_steps=200)

This connects naturally to tools/dpdata-minimizer.

Output expectations

Provide:

1. the selected xTB usage mode
2. runnable command or script pattern
3. method/solvent/accuracy assumptions
4. unresolved scientific choices
5. handoff to dpdisp-submit if execution/submission is requested