orcaflex-monolithic-to-modular
Convert monolithic OrcaFlex models (.dat/.yml) to spec-driven modular format with semantic validation for round-trip fidelity.
Best use case
orcaflex-monolithic-to-modular is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Convert monolithic OrcaFlex models (.dat/.yml) to spec-driven modular format with semantic validation for round-trip fidelity.
Teams using orcaflex-monolithic-to-modular 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/monolithic-to-modular/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How orcaflex-monolithic-to-modular Compares
| Feature / Agent | orcaflex-monolithic-to-modular | 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?
Convert monolithic OrcaFlex models (.dat/.yml) to spec-driven modular format with semantic validation for round-trip fidelity.
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
# Orcaflex Monolithic To Modular ## When to Use - Converting `.dat` / `.yml` OrcaFlex models to portable `spec.yml` format - Creating reusable component libraries from existing models - Validating that modular output is semantically equivalent to monolithic source - Preparing models for parametric studies or automated benchmarking - Building a spec.yml foundation for any new OrcaFlex model ## Related Skills - [orcaflex-model-generator](../orcaflex-model-generator/SKILL.md) - Builder registry and generation architecture - [orcaflex-yaml-gotchas](../orcaflex-yaml-gotchas/SKILL.md) - Production OrcaFlex YAML traps - [orcaflex-environment-config](../orcaflex-environment-config/SKILL.md) - Environment configuration ## References - Extractor: `src/digitalmodel/solvers/orcaflex/modular_generator/extractor.py` - Schema: `src/digitalmodel/solvers/orcaflex/modular_generator/schema/generic.py` - Semantic validator: `scripts/semantic_validate.py` - Benchmark: `scripts/benchmark_model_library.py` - Spec library: `docs/modules/orcaflex/library/tier2_fast/` --- ## Version History - **2.0.0** (2026-02-10): Complete rewrite. Documents actual MonolithicExtractor pipeline, section name aliases, semantic validation, Pydantic integration, and benchmark results. - **1.0.0** (2026-01-21): Initial release with manual splitting approach. ## Sub-Skills - [Architecture](architecture/SKILL.md) - [Step 1: Convert .dat to .yml (if needed) (+4)](step-1-convert-dat-to-yml-if-needed/SKILL.md) - [Section Mapping (+2)](section-mapping/SKILL.md) - [Significance Levels (+2)](significance-levels/SKILL.md) - [Output Structure](output-structure/SKILL.md) - [Common Issues and Fixes](common-issues-and-fixes/SKILL.md) - [Benchmark Results (2026-02-10)](benchmark-results-2026-02-10/SKILL.md)
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