Analysis Router
SkillDev toolsUse when the user asks to analyze computational results: Gibbs free energy, OER/HER/CO2RR overpotentials, adsorption energy, convergence tests, DOS/d-band analysis, or Bader charge analysis.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Analysis Router skill
What this skill tells your AI
The instructions your AI receives, as published by hello-qm/catgo-lrg in server/catgo/workflow/skills/analysis/SKILL.md and read by ahel’s review.
This skill routes analysis requests to the correct sub-skill based on what the user is asking for.
Routing Table
| User Intent | Sub-Skill | Key Indicators |
|---|---|---|
| Gibbs free energy, ZPE, thermal corrections | gibbs/ | "free energy", "ZPE", "entropy", "thermal" |
| OER overpotential | oer/ | "OER", "oxygen evolution", "water splitting anode" |
| HER overpotential | her/ | "HER", "hydrogen evolution", "water splitting cathode" |
| CO2 reduction | co2rr/ | "CO2RR", "CO2 reduction", "carbon dioxide" |
| Adsorption energy | adsorption/ | "adsorption energy", "binding energy", "E_ads" |
| ENCUT/KPOINTS convergence | convergence/ | "convergence", "ENCUT test", "k-point test" |
| DOS, d-band center, PDOS | dos_analysis/ | "DOS", "d-band", "PDOS", "density of states" |
| Bader charge | charge/ | "Bader", "charge transfer", "charge analysis" |
| MACE Ni benchmark (Kreitz 2021) | mace_ni_benchmark/ | "Kreitz", "MACE Ni benchmark", "MLP vs DFT-D3 on Ni" |
MCP Tool: catgo_analyze
All analysis actions use the catgo_analyze tool with an action parameter.
{"tool": "catgo_analyze", "arguments": {"action": "convergence", ...}}
{"tool": "catgo_analyze", "arguments": {"action": "frequencies", ...}}
{"tool": "catgo_analyze", "arguments": {"action": "forces", ...}}
MCP Tool: catgo_workflow_engine
Most analysis workflows are built as DAGs using the workflow tool.
{"tool": "catgo_workflow_engine", "arguments": {"action": "create", "name": "Analysis WF"}}
{"tool": "catgo_workflow_engine", "arguments": {"action": "add_task", "workflow_id": "...", "task_type": "gibbs_energy", ...}}
Python API Pattern
All analysis workflows follow the same skeleton:
from catgo.workflow import Workflow
wf = Workflow("Analysis name")
# 1. Input structure
inp = wf.add_task("structure_input", structure=structure_json)
# 2. Compute (geo_opt, single_point, freq, etc.)
opt = wf.add_task("geo_opt", structure=inp.output.structure, software="vasp")
frq = wf.add_task("freq", structure=opt.output.structure, software="vasp",
freeze_mode="layers", freeze_layers=4)
# 3. Analyze (gibbs_energy, dos_analysis, charge_analysis, etc.)
gib = wf.add_task("gibbs_energy", energy=opt.output.energy,
frequencies=frq.output.frequencies, phase="adsorbed")
wf.submit()
Decision Guide
- Single intermediate (H*, OH) -->
her/,adsorption/ - Multiple intermediates in reaction pathway -->
oer/,co2rr/ - Parameter sweep, no reaction -->
convergence/ - Post-processing existing calculation -->
dos_analysis/,charge/ - Converting DFT energy to thermodynamic quantity -->
gibbs/
Common Pitfalls
- Always run
geo_optbeforefreq-- frequencies on unrelaxed structures are meaningless. - For surface calculations, always use
freeze_mode="layers"in freq to avoid imaginary frequencies from slab bottom atoms. - Gibbs energy needs both
energy(from geo_opt) andfrequencies(from freq) -- these come from separate tasks connected via output references. - Convergence tests use
single_point(notgeo_opt) to isolate the parameter effect.
Signals
- GitHub stars
- 196
- Forks
- 23
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
analysis-router- Source
- github.com/hello-qm/catgo-lrg