orcaflex-specialist-1-model-organization
Sub-skill of orcaflex-specialist: 1. Model Organization (+2).
Best use case
orcaflex-specialist-1-model-organization is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of orcaflex-specialist: 1. Model Organization (+2).
Teams using orcaflex-specialist-1-model-organization 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/1-model-organization/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How orcaflex-specialist-1-model-organization Compares
| Feature / Agent | orcaflex-specialist-1-model-organization | 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-specialist: 1. Model Organization (+2).
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
# 1. Model Organization (+2)
## 1. Model Organization
```python
# Naming conventions
NAMING_CONVENTIONS = {
'vessels': 'VesselName', # e.g., 'FPSO', 'FSO_1'
'lines': 'Mooring_N' or 'Riser_N', # e.g., 'Mooring_1', 'Riser_2'
'buoys': 'Buoy_N' or 'Subsurface_Buoy_N',
'6d_buoys': '6DBuoy_N',
'winches': 'Winch_N',
'line_types': 'Descriptive_Name', # e.g., 'R4_Studless_Chain', '76mm_Wire'
}
# Model structure best practices
MODEL_STRUCTURE = {
'stages': [
'Build-up', # 100-200s
'Main simulation', # 3600-10800s
'Optional: Transient event'
],
'time_steps': {
'inner': 0.01, # 0.01-0.05s
'log_sample': 0.1 # 0.1-1.0s
}
}
```
## 2. Simulation Settings
```python
# Recommended simulation settings
SIMULATION_SETTINGS = {
'implicit': {
'use_variable_timestep': 'Yes',
'target_log_sample_interval': 0.1,
'inner_timestep': 0.01,
'max_iterations': 20,
'tolerance': 1e-6
},
'explicit': {
'timestep': 0.001, # Much smaller for explicit
'log_sample_interval': 0.1
}
}
```
## 3. Error Handling
```python
def safe_simulation_run(
model: OrcFxAPI.Model,
max_retries: int = 3
) -> bool:
"""
Run simulation with error handling and retries.
Args:
model: OrcaFlex model
max_retries: Maximum number of retry attempts
Returns:
True if successful, False otherwise
"""
for attempt in range(max_retries):
try:
model.RunSimulation()
return True
except OrcFxAPI.DynamicsError as e:
print(f"Dynamics error (attempt {attempt+1}): {e}")
# Try reducing time step
current_dt = model.general.InnerTimeStep
model.general.InnerTimeStep = current_dt * 0.5
print(f"Reducing time step to {model.general.InnerTimeStep}")
except Exception as e:
print(f"Unexpected error: {e}")
return False
return False
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