Agent skill
orcaflex-monolithic-to-modular-step-1-convert-dat-yml
Sub-skill of orcaflex-monolithic-to-modular: Step 1: Convert .dat to .yml (if needed) (+4).
Install this agent skill to your Project
npx add-skill https://github.com/vamseeachanta/workspace-hub/tree/main/.claude/skills/_archive/engineering/marine-offshore/orcaflex-monolithic-to-modular/step-1-convert-dat-to-yml-if-needed
SKILL.md
Step 1: Convert .dat to .yml (if needed) (+4)
Step 1: Convert .dat to .yml (if needed)
import OrcFxAPI
model = OrcFxAPI.Model("model.dat")
model.SaveData("model.yml") # OrcaFlex YAML export
Step 2: Extract spec from monolithic YAML
from digitalmodel.solvers.orcaflex.modular_generator.extractor import MonolithicExtractor
ext = MonolithicExtractor(Path("model.yml"))
spec_dict = ext.extract()
# Returns: {"metadata": {...}, "environment": {...}, "simulation": {...}, "generic": {...}}
The extractor:
- Reads multi-document YAML (handles
---separators) - Maps OrcaFlex keys to spec schema (typed fields + properties bag)
- Handles section name aliases (Groups/BrowserGroups, FrictionCoefficients/SolidFrictionCoefficients)
- Extracts current profiles from multi-column keys
- Captures
raw_propertiesfor diagnostic use
Step 3: Validate and create spec
from digitalmodel.solvers.orcaflex.modular_generator.schema.root import ProjectInputSpec
spec = ProjectInputSpec(**spec_dict)
# Pydantic validates all fields, applies defaults
Step 4: Generate modular output
from digitalmodel.solvers.orcaflex.modular_generator import ModularModelGenerator
gen = ModularModelGenerator.from_spec(spec)
gen.generate(Path("output/modular"))
Step 5: Semantic validation
from scripts.semantic_validate import load_monolithic, load_modular, validate, summarize
mono = load_monolithic(Path("model.yml"))
mod = load_modular(Path("output/modular"))
results = validate(mono, mod)
summary = summarize(results)
print(f"Match: {summary['total_sections'] - summary['sections_with_diffs']}/{summary['total_sections']}")
print(f"Significant diffs: {summary['significant_diffs']}")
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