ORCA Geometry Optimization Skill
SkillAI & modelsORCA geometry optimization. Handles method/basis selection, dispersion corrections, solvent models, and convergence settings.
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Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the ORCA Geometry Optimization Skill skill
What this skill tells your AI
The instructions your AI receives, as published by hello-qm/catgo-lrg in .claude/skills/orca-opt/SKILL.md and read by ahel’s review.
When to Use
Use this skill when the user wants to:
- Optimize a molecular geometry with ORCA
- Find the minimum energy structure of a molecule
- Relax a molecular cluster or complex
Do NOT use for periodic systems (use VASP or CP2K instead).
Node Parameters (canonical names — these are what the engine actually reads)
| Parameter | Default | Description |
|---|---|---|
method | B3LYP | DFT functional (e.g. B3LYP, PBE0, wB97X-D4, r2SCAN-3c) |
basis | def2-SVP | Basis set (omit for composite methods like r2SCAN-3c) |
charge | 0 | Total charge |
multiplicity | 1 | Spin multiplicity (2S+1) |
dispersion | (none) | D4 | D3BJ | D3 | none. Put D4/D3BJ HERE, not in method. |
three_body_dispersion | false | Adds ABC term (D3-class only; ignored for D4) |
grid | DefGrid2 | DefGrid1/2/3 — emitted only when ≠ default |
wavefunction | (none) | e.g. UKS for unrestricted |
uno, uco | false | Unrestricted natural / corresponding orbital tweaks |
num_cores | 4 | %pal nprocs |
max_core_mb | 4000 | %maxcore |
opt_convergence | (none) | e.g. TightOpt, VeryTightOpt |
⚠️
extra_keywordsandextra_blocksare NOT read by the ORCA workflow engine. Earlier versions of this skill recommended them; anything passed via those keys is silently dropped. Use the dedicated fields above. CPCM solvation,SlowConv/SOSCF, andNumFreqcurrently have no first-class field on the opt/freq/neb_ts/irc nodes — that is a node-def gap, not a usage problem.
MCP Tool Examples — proven Expanse submission flow
Use
catgo_workflow(graph-based), NOTcatgo_workflow_engine(task-based). The graph-based tool auto-captures the viewer structure oncreate. The task-based tool'sadd_taskdoes not, so jobs fail with "No input structure provided". Param keys differ too: graph-based usesmethod/basis, task-based usesorca_method/orca_basis.
1. Confirm structure is loaded
catgo_view(action: "get_state")
2. Find the Expanse session_id
Session IDs are volatile — they change on every reconnect. Discover the current one:
curl -s http://localhost:8000/api/hpc/connections
Look for the entry with host: login.expanse.sdsc.edu and copy its session_id.
3. Create the workflow (auto-captures viewer structure)
catgo_workflow(action: "create", name: "Benzene optimization")
Returns a workflow with one structure_input node containing the current viewer
structure. Note its node ID (e.g., n1777012885-iode).
4. Add the geo_opt node and connect it
Inject extra_blocks: "%output jsongbwfile True jsonpropfile True end" so ORCA
emits the JSON files OPI parses on the way back. Without this, OPI parsing
falls back to grepping ORCA.out (still works, just less rich).
catgo_workflow(action: "batch", workflow_id: "<wf_id>", operations: [
{"op": "add_node", "node_type": "geo_opt", "label": "opt",
"params": {
"software": "orca",
"method": "B3LYP",
"basis": "def2-SVP",
"charge": 0,
"multiplicity": 1,
"extra_blocks": "%output jsongbwfile True jsonpropfile True end"
}},
{"op": "connect", "from_id": "<structure_input_id>", "to_id": "opt",
"from_handle": "structure", "to_handle": "structure"}
])
5. Run with the full HPC run_config
Real opt jobs on non-trivial molecules can run for hours — default to
partition: "shared" with a generous walltime. Use debug only for tiny
sanity checks (≤ a couple of heavy atoms, single-point or quick test). Read
server/templates/orca_generic.sh and pass its contents as default_template.
catgo_workflow(action: "run", workflow_id: "<wf_id>", run_config: {
"execution_mode": "hpc",
"default_session_id": "<expanse_session_id>",
"base_work_dir": "/expanse/lustre/projects/sdp126/jyang25/ORCA/catgo",
"default_job_params": {
"nodes": 1, "ntasks": 8, "cpus_per_task": 1,
"walltime": "04:00:00", "partition": "shared"
},
"cluster_configs": {
"<expanse_session_id>": {
"account": "sdp126",
"partition": "shared",
"module_loads": "module load cpu/0.17.3b\nmodule load gcc/10.2.0/npcyll4\nexport PATH=$HOME/openmpi-4.1.8/bin:$PATH\nexport LD_LIBRARY_PATH=$HOME/openmpi-4.1.8/lib:$LD_LIBRARY_PATH",
"orca_dir": "/home/jyang25/orca_6_1_1_RRP8",
"default_template": "<contents of server/templates/orca_generic.sh>",
"default_job_params": {
"nodes": 1, "ntasks": 8, "cpus_per_task": 1,
"walltime": "04:00:00", "partition": "shared"
}
}
}
})
For a quick sanity check (e.g., H2O / methane / single small molecule),
override to partition: "debug", walltime: "00:30:00", ntasks: 4. The
debug partition caps at 30 min — anything bigger will be rejected after the
limit.
The local-scratch template stages I/O to $TMPDIR/orca_$SLURM_JOB_ID and copies
results back to the Lustre work_dir. Required on Expanse — Lustre is bad for
ORCA's many small temp files.
6. Common parameter variations
For dispersion (non-covalent systems, dimers, π-stacking, H-bonding):
"params": {"method": "B3LYP", "basis": "def2-TZVP", "dispersion": "D3BJ", "charge": 0, "multiplicity": 1}
For D4 (newer Grimme correction, slightly better for metals):
"params": {"method": "B3LYP", "basis": "def2-SVP", "dispersion": "D4", "charge": 0, "multiplicity": 1}
For implicit solvation:
CPCM is currently a node-def gap on opt/freq/neb_ts/irc — there's no first-class
solvation/solventfield, andextra_keywordsis not read. UV-Vis is the exception (it has dedicatedsolvation/solventfields). Until this is fixed, single-point CPCM on a gas-phase optimized geometry, or running on a non-CatGo input file, is the workaround.
For tight convergence (publication quality, pre-freq):
"params": {"method": "B3LYP", "basis": "def2-TZVP", "opt_convergence": "TightOpt", "dispersion": "D3BJ", "charge": 0, "multiplicity": 1}
For open-shell radicals:
"params": {"method": "UB3LYP", "basis": "def2-SVP", "charge": 0, "multiplicity": 2}
7. Monitor
catgo_workflow(action: "status", workflow_id: "<wf_id>")
Or query SLURM directly via the live session:
curl -s "http://localhost:8000/api/hpc/jobs/<job_id>?session_id=<expanse_session_id>"
8. Pull results when COMPLETED
Pull the ORCA outputs into a local directory, including the OPI JSON files
(*.property.json is the rich structured output OPI parses):
mkdir -p ./local_run
for f in ORCA.out ORCA.xyz ORCA.engrad ORCA.property.json ORCA.json; do
curl -s -X POST http://localhost:8000/api/hpc/files/read-content \
-H 'Content-Type: application/json' \
-d "{\"session_id\":\"<expanse_session_id>\",\"file_path\":\"<work_dir>/$f\"}" \
> ./local_run/$f
done
ORCA.json and ORCA.property.json only exist if the input had the
%output jsongbwfile True jsonpropfile True end block (step 4). If you
omitted it, OPI parsing falls back to grepping ORCA.out.
9. Parse with OPI
Replaces hand-walking ORCA.xyz / ORCA.engrad. Requires pip install orca-pi.
import sys
sys.path.insert(0, ".claude/skills") # for the _shared helper
from _shared.orca_opi import parse_local
out = parse_local("./local_run")
print("SCF converged: ", out.scf_converged())
print("Geometry converged: ", out.geometry_optimization_converged())
print("Final energy (Eh): ", out.get_final_energy())
print("Optimized XYZ:\n", out.get_structure().to_xyz_block())
# Per-step trajectory (energy curve)
for i, geom in enumerate(out.results_properties.geometries):
print(i, geom.single_point_data.finalenergy)
# Population analyses (any of these are one call now)
mulliken = out.get_mulliken()
print("HOMO/LUMO/gap (eV):", out.get_homo(), out.get_lumo(), out.get_hl_gap())
Viewing the optimization curve in the IDE
Use the shared helper to plot per-step energies and surface the PNG inline.
from _shared.orca_opi import quick_plot_opt_energy, show_png
png = quick_plot_opt_energy(out) # writes ./local_run/opt_energy.png
show_png(png, "Opt energy convergence") # prints ``
After running this, reply to the user with the markdown link the script printed (e.g. ) so Claude Code renders the figure inline in chat.
Submission gotchas (real failures we hit)
catgo_workflow_engine.add_taskdoesn't auto-attach the viewer structure → "No input structure provided".partition=workq(Shaheen default) is invalid on Expanse → usedebugorshared.- Missing
account=sdp126→ "Invalid account or account/partition combination". - Missing
module_loads+orca_dir→orcanot on PATH, job runs ORCA-not-found and silently produces nothing. - After re-connecting to Expanse, the session_id changes — re-discover via
/api/hpc/connectionsand updatedefault_session_id+cluster_configskey. - Engine doesn't regenerate
submit.shonretryalone — callrunwith the newrun_configto get a fresh script with updated SBATCH headers.
Dispersion Corrections
| Keyword | Method | When to use |
|---|---|---|
D3BJ | Grimme D3 with Becke-Johnson damping | Default choice for dispersion |
D3 | Grimme D3 with zero damping | Legacy, use D3BJ instead |
D4 | Grimme D4 | Newer, slightly better for metals |
Always include dispersion for: molecular dimers, adsorption complexes, conformational searches, anything with pi-stacking or H-bonding.
Basis Set Ladder
| Basis | Quality | Cost | Use |
|---|---|---|---|
| def2-SVP | Double-zeta | Low | Screening, initial opt |
| def2-TZVP | Triple-zeta | Medium | Production geometry |
| def2-TZVPP | Triple-zeta+pol | High | Accurate energetics |
| def2-QZVPP | Quadruple-zeta | Very high | Benchmark only |
Strategy: optimize with def2-SVP, then single-point with def2-TZVP for energy.
SCF Convergence Issues
ORCA SCF tweaks like SlowConv, VerySlowConv, SOSCF, SmearTemp 5000 are not exposed as first-class node params (gap in the engine). For now: pre-optimize with a smaller basis (def2-SVP) and feed that geometry to a larger-basis run, or run ORCA directly on a hand-edited input file outside the workflow engine.
Common Mistakes
- Forgetting dispersion for non-covalent systems (huge geometry errors)
- Using restricted (R) method for open-shell (use UB3LYP, not B3LYP)
- Basis set too large for optimization (optimize with SVP, refine energy with TZVP)
- Not checking for imaginary frequencies after optimization
Signals
- GitHub stars
- 196
- Forks
- 23
- Last commit
- Sep 2026
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orca-opt-hello-qm- Source
- github.com/hello-qm/catgo-lrg