orcaflex-installation-analysis-integration-with-universal-runner
Sub-skill of orcaflex-installation-analysis: Integration with Universal Runner.
Best use case
orcaflex-installation-analysis-integration-with-universal-runner is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of orcaflex-installation-analysis: Integration with Universal Runner.
Teams using orcaflex-installation-analysis-integration-with-universal-runner 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/integration-with-universal-runner/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How orcaflex-installation-analysis-integration-with-universal-runner Compares
| Feature / Agent | orcaflex-installation-analysis-integration-with-universal-runner | 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-installation-analysis: Integration with Universal Runner.
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
# Integration with Universal Runner
## Integration with Universal Runner
After generating installation models, run batch simulations:
```python
from digitalmodel.orcaflex.universal import UniversalOrcaFlexRunner
# Initialize runner
runner = UniversalOrcaFlexRunner(
input_directory="results/installation/",
output_directory="results/installation/.sim/",
mock_mode=False
)
# Run all installation models
results = runner.run_batch(
pattern="el_*.yml",
parallel=True,
max_workers=4
)
# Check results
for file_name, status in results.items():
print(f"{file_name}: {'SUCCESS' if status['success'] else 'FAILED'}")
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