orcawave-aqwa-benchmark-common-causes-of-deviation
Sub-skill of orcawave-aqwa-benchmark: Common Causes of Deviation (+1).
Best use case
orcawave-aqwa-benchmark-common-causes-of-deviation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of orcawave-aqwa-benchmark: Common Causes of Deviation (+1).
Teams using orcawave-aqwa-benchmark-common-causes-of-deviation 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/common-causes-of-deviation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How orcawave-aqwa-benchmark-common-causes-of-deviation Compares
| Feature / Agent | orcawave-aqwa-benchmark-common-causes-of-deviation | 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 orcawave-aqwa-benchmark: Common Causes of Deviation (+1).
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
# Common Causes of Deviation (+1)
## Common Causes of Deviation
| Issue | Typical Deviation | Solution |
|-------|-------------------|----------|
| Mesh differences | 5-15% | Use similar panel counts |
| Coordinate systems | Phase shift | Verify origin/orientation |
| Frequency resolution | Variable | Interpolate to common frequencies |
| Irregular frequency removal | 10-20% at specific freqs | Check lid method settings |
| Viscous damping | Roll/pitch deviation | Ensure consistent settings |
## Diagnostic Workflow
```python
from digitalmodel.diffraction.comparison_framework import DiagnosticAnalyzer
# Initialize diagnostic analyzer
diagnostic = DiagnosticAnalyzer()
# Run diagnostics
issues = diagnostic.identify_issues(
aqwa_results=aqwa_data,
orcawave_results=orcawave_data,
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