orcaflex-model-generator-from-specyml-file
Sub-skill of orcaflex-model-generator: From spec.yml file (+3).
Best use case
orcaflex-model-generator-from-specyml-file is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of orcaflex-model-generator: From spec.yml file (+3).
Teams using orcaflex-model-generator-from-specyml-file should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/from-specyml-file/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How orcaflex-model-generator-from-specyml-file Compares
| Feature / Agent | orcaflex-model-generator-from-specyml-file | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of orcaflex-model-generator: From spec.yml file (+3).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# From spec.yml file (+3)
## From spec.yml file
```python
from digitalmodel.solvers.orcaflex.modular_generator import ModularModelGenerator
gen = ModularModelGenerator(Path("spec.yml"))
gen.generate(Path("output/"))
```
## From in-memory spec
```python
spec = ProjectInputSpec(**spec_dict)
gen = ModularModelGenerator.from_spec(spec)
gen.generate(Path("output/"))
```
## From monolithic (extract + generate)
```python
from digitalmodel.solvers.orcaflex.modular_generator.extractor import MonolithicExtractor
ext = MonolithicExtractor(Path("model.yml"))
spec = ProjectInputSpec(**ext.extract())
gen = ModularModelGenerator.from_spec(spec)
gen.generate(Path("output/"))
```
## With section overrides
```python
result = gen.generate_with_overrides(
output_dir=Path("output/"),
sections=[override_section],
variables={"water_depth": 500},
)
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