orcaflex-vessel-setup-data-import
Sub-skill of orcaflex-vessel-setup: Data Import (+2).
Best use case
orcaflex-vessel-setup-data-import is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of orcaflex-vessel-setup: Data Import (+2).
Teams using orcaflex-vessel-setup-data-import 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/data-import/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How orcaflex-vessel-setup-data-import Compares
| Feature / Agent | orcaflex-vessel-setup-data-import | 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-vessel-setup: Data Import (+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
# Data Import (+2) ## Data Import 1. **Verify AQWA output** - Check analysis completed successfully 2. **Check sign conventions** - AQWA vs OrcaFlex phase conventions 3. **Validate RAO magnitudes** - Compare with expected responses 4. **Test at single frequency** - Verify motion response ## Vessel Configuration 1. **Correct draught** - Match analysis loading condition 2. **Coordinate system** - Align with AQWA body axes 3. **Connection point** - Set appropriate attachment 4. **Calculation options** - Match analysis requirements ## Multi-Body Systems 1. **Body mapping** - Match AQWA body numbers 2. **Coupling terms** - Include hydrodynamic interaction 3. **Connection constraints** - Link vessels appropriately
Related Skills
data-validation-reporter
Generate interactive validation reports with quality scoring, missing data analysis, and type checking. Combines Pandas validation, Plotly visualization, and YAML configuration for comprehensive data quality reporting.
OrcaFlex Specialist Skill
```yaml
orcaflex-reporting-fixture-proof-pattern
Build and extend fixture-backed OrcaFlex reporting proof paths in digitalmodel using stable metadata baselines, normalized HTML snapshots, and reusable reporting test helpers.
digitalmodel-orcawave-orcaflex-proof-workflows
Class-level digitalmodel OrcaWave/OrcaFlex readiness, semantic-proof, fixture-proof, and closeout workflows.
worldenergydata-source-readiness
Route agents to the canonical worldenergydata source-readiness skill and summary script. Use when asked for worldenergydata data completeness, data locations, latest known data dates, scheduler freshness, source-readiness status, or acceptance-criteria inputs across the repo ecosystem.
sodir-data-extractor
Extract and process Norwegian Petroleum Directorate field and production data from SODIR
metocean-data-fetcher
Fetch real-time and historical metocean data from NDBC, CO-OPS, Open-Meteo, ERDDAP, and MET Norway. Use for buoy data retrieval, tidal observations, marine forecasts, and multi-source data fusion.
energy-data-visualizer
Interactive visualization for oil and gas production data analysis using Plotly dashboards
bsee-data-extractor
Extract and process BSEE (Bureau of Safety and Environmental Enforcement) data including production, WAR (Well Activity Reports), and APD (Application for Permit to Drill) data. Use for querying production data, well activities, drilling permits, completions, and workovers by API number, block, lease, or field with automatic data normalization and caching.
orcawave-orcaflex-readiness-audit
Audit the real readiness of digitalmodel OrcaWave/OrcaFlex spec-driven workflows by reconciling workspace-hub issues, source/tests, semantic-equivalence boundaries, and wiki synthesis gaps.
tax-return-data-capture-and-archival
Capture structured tax return summaries as YAML for year-over-year comparison, with fallback to manual PDF download and relocation when automation fails
tax-filing-session-setup-with-github-tracking
Structured workflow for preparing and tracking a tax filing session using prepared documents, task checklist, and GitHub issue cross-referencing