JSON Output Reference

mlmm provides machine-readable JSON output for programmatic consumption by AI agents, scripts, and downstream tools.

--out-json flag

Every MLIP-based subcommand supports --out-json / --no-out-json (default: off). When enabled, a result.json file is written to the output directory alongside the normal outputs.

mlmm opt -i r_complex_layered.pdb --max-cycles 5 --out-json --out-dir result_opt
cat result_opt/result.json | python -m json.tool

The all and path-search commands always write summary.json (no --out-json flag needed).

Common envelope

Every result.json automatically includes:

Field

Type

Description

command

string

Subcommand name (e.g. "opt")

mlmm_version

string

Package version

elapsed_seconds

float

Wall-clock time (seconds)

environment

object

Hardware info (see below)

environment:

Field

Type

Example

device

string

"cuda" or "cpu"

gpu_name

string

"NVIDIA GeForce RTX 5080"

gpu_vram_gb

float

16.6

cuda_version

string

"12.9"

cpu

string

"AMD Ryzen 9 7950X 16-Core Processor"

n_cpus

int

32

ram_gb

float

133.7

Subcommand schemas

opt

Field

Type

Description

status

string

"converged" or "not_converged"

energy_hartree

float

Final ONIOM energy (Hartree)

n_opt_cycles

int

Optimization cycles completed

opt_mode

string

"grad" (LBFGS) or "hess" (RFO)

backend

string

ML backend ("uma", "orb", "mace", "aimnet2")

charge

int

Model-region charge

spin

int

Model-region multiplicity

n_atoms

int

Total atoms (all layers)

n_freeze_atoms

int

Frozen atoms

thresh

string

Convergence threshold preset

max_cycles

int

Maximum allowed cycles

input_file

string

Input filename

final_max_force

float

Last max gradient (Hartree/Bohr)

final_rms_force

float

Last RMS gradient

final_max_step

float

Last max displacement (Bohr)

final_rms_step

float

Last RMS displacement

convergence_thresholds

object

Numeric thresholds for the named preset

files

object

Output file map

tsopt

Field

Type

Description

status

string

"completed"

energy_hartree

float

TS energy (Hartree)

n_imaginary_modes

int

Number of imaginary frequencies

imaginary_frequencies_cm

float[]

Imaginary frequencies (cm$^{-1}$, negative)

opt_mode

string

"grad" (PHG-Dimer) or "hess" (RS-I-RFO)

n_atoms

int

Total atoms

n_opt_cycles

int

Optimization cycles

backend

string

ML backend

charge

int

Model-region charge

spin

int

Model-region multiplicity

files

object

Final geometry + vib mode files

freq

Field

Type

Description

status

string

"completed"

n_modes

int

Total normal modes

n_imaginary

int

Imaginary frequency count

frequencies_cm

float[]

All frequencies (cm$^{-1}$)

imaginary_frequencies_cm

float[]

Negative frequencies only

thermochemistry

object|null

Thermodynamic data (see below)

backend

string

ML backend

charge

int

Model-region charge

spin

int

Model-region multiplicity

n_atoms

int

Total atoms

n_freeze_atoms

int

Frozen atoms

files

object

{"frequencies_txt": "frequencies_cm-1.txt"}

thermochemistry (null if thermoanalysis unavailable):

Field

Type

Unit

temperature_K

float

K

pressure_atm

float

atm

zpe_ha

float

Hartree

thermal_correction_energy_ha

float

Hartree

thermal_correction_enthalpy_ha

float

Hartree

thermal_correction_free_energy_ha

float

Hartree

sum_EE_and_ZPE_ha

float

Hartree

sum_EE_and_thermal_energy_ha

float

Hartree

sum_EE_and_thermal_free_energy_ha

float

Hartree

E_thermal_cal_per_mol

float

cal/mol

Cv_cal_per_mol_K

float

cal/(mol K)

S_cal_per_mol_K

float

cal/(mol K)

irc

Field

Type

Description

status

string

"completed"

n_frames_forward / backward / total

int

IRC frames

energy_reactant_hartree

float

Reactant energy

energy_ts_hartree

float

TS energy

energy_product_hartree

float

Product energy

forward_converged / backward_converged

bool

IRC convergence

backend

string

ML backend

bond_changes

object

{formed: [...], broken: [...]}

files

object

Trajectory files (xyz + pdb)

scan

Field

Type

Description

status

string

"completed"

n_stages

int

Number of scan stages

stages

object[]

Per-stage data

backend

string

ML backend

charge

int

Model-region charge

spin

int

Model-region multiplicity

files

object

Output files

stages[]: n_steps, converged, pairs_1based, energies_hartree, final_energy_hartree, bond_changes

scan2d / scan3d

Field

Type

Description

n_grid_points

int

Total grid points

pair1, pair2 (,pair3)

object

{i, j, low, high}

min_energy_hartree

float

Surface minimum energy

backend

string

ML backend

charge

int

Model-region charge

spin

int

Model-region multiplicity

files

object

CSV + plot files

path-opt

Field

Type

Description

converged

bool

Convergence flag

mep_mode

string

"dmf" or "gsm"

backend

string

ML backend

image_energies_hartree

float[]

All image energies

n_images

int

Image count

hei_index

int

Highest-energy image index

barrier_kcal

float

Forward barrier (kcal/mol)

delta_kcal

float

Reaction energy (kcal/mol)

files

object

Trajectory + HEI files

dft

Field

Type

Description

converged

bool

SCF converged?

energy_hartree

float

DFT energy

xc_functional

string

XC functional

basis_set

string

Basis set

used_gpu

bool

GPU acceleration used?

backend

string

ML backend for ONIOM high-level region

charges

object

{mulliken, lowdin, iao} per-atom arrays

spin_densities

object

{mulliken, lowdin, iao} per-atom arrays

n_atoms

int

QM-region atom count

grid_level

int

DFT grid level

conv_tol

float

SCF convergence tolerance

files

object

{"result_yaml": "result.yaml"}

extract

Field

Type

Description

status

string

"ok"

n_atoms_extracted

int

Atoms after extraction

total_charge

float

Computed total charge

protein_charge

float

Protein charge

ligand_total_charge

float

Ligand charge sum

ion_total_charge

float

Ion charge sum

unknown_residue_charges

object

{resname: charge}

center

string

Center residue

radius

float

Extraction radius (angstrom)

input_files

string[]

Input PDB paths

summary.json (path-search / all)

The all and path-search commands write summary.json:

Field

Type

Description

status

string

"success" / "partial"

n_segments

int

Segment count

segments

object[]

Per-segment barrier, delta, bond changes

energy_diagrams

object[]

Energy profiles with labels and kcal/mol values

mlip_backend

string

Model identifier

charge

int

Model-region charge

spin

int

Model-region multiplicity

environment

object

Hardware info

The all command additionally includes:

Field

Type

Description

rate_limiting_step

object

RLS segment index and barrier

overall_reaction_energy_kcal

float

Overall reaction energy

post_segments

list

Per-segment TS/IRC/freq/DFT results

Usage examples

Python

import json

with open("result_opt/result.json") as f:
    result = json.load(f)

if result["status"] == "converged":
    print(f"Energy: {result['energy_hartree']:.6f} Hartree")
else:
    print(f"Not converged after {result['n_opt_cycles']} cycles")
    print(f"Max force: {result['final_max_force']:.6f}")

jq

# Check convergence
jq '.status' result.json

# Get barrier from path-opt
jq '.barrier_kcal' result.json

# List imaginary frequencies from tsopt
jq '.imaginary_frequencies_cm' result.json

# Get thermochemistry from freq
jq '.thermochemistry.sum_EE_and_thermal_free_energy_ha' result.json