Analysis Router

SkillDev tools

Use 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.

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 IntentSub-SkillKey Indicators
Gibbs free energy, ZPE, thermal correctionsgibbs/"free energy", "ZPE", "entropy", "thermal"
OER overpotentialoer/"OER", "oxygen evolution", "water splitting anode"
HER overpotentialher/"HER", "hydrogen evolution", "water splitting cathode"
CO2 reductionco2rr/"CO2RR", "CO2 reduction", "carbon dioxide"
Adsorption energyadsorption/"adsorption energy", "binding energy", "E_ads"
ENCUT/KPOINTS convergenceconvergence/"convergence", "ENCUT test", "k-point test"
DOS, d-band center, PDOSdos_analysis/"DOS", "d-band", "PDOS", "density of states"
Bader chargecharge/"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

  1. Always run geo_opt before freq -- frequencies on unrelaxed structures are meaningless.
  2. For surface calculations, always use freeze_mode="layers" in freq to avoid imaginary frequencies from slab bottom atoms.
  3. Gibbs energy needs both energy (from geo_opt) and frequencies (from freq) -- these come from separate tasks connected via output references.
  4. Convergence tests use single_point (not geo_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