solver-benchmark-programmatic-usage

Sub-skill of solver-benchmark: Programmatic Usage.

5 stars

Best use case

solver-benchmark-programmatic-usage is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Sub-skill of solver-benchmark: Programmatic Usage.

Teams using solver-benchmark-programmatic-usage 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

$curl -o ~/.claude/skills/programmatic-usage/SKILL.md --create-dirs "https://raw.githubusercontent.com/vamseeachanta/workspace-hub/main/.agents/skills/_archive/engineering/marine-offshore/solver-benchmark/programmatic-usage/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/programmatic-usage/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How solver-benchmark-programmatic-usage Compares

Feature / Agent	solver-benchmark-programmatic-usage	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 solver-benchmark: Programmatic Usage.

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

# Programmatic Usage

## Programmatic Usage


```python
from pathlib import Path
from scripts.benchmark.run_3way_benchmark import run_benchmark

# Run benchmark
result = run_benchmark(
    spec_path=Path("specs/modules/benchmark/unit_box_spec.yml"),
    output_dir=Path("benchmark_output/unit_box"),
    solvers=["orcawave", "aqwa", "bemrosetta"],
    dry_run=False,
)

# Check results
print(f"Success: {result.success}")
for name, sr in result.solver_results.items():
    print(f"  {name}: {sr.status}")

if result.benchmark_result and result.benchmark_result.report:
    print(f"Consensus: {result.benchmark_result.report.overall_consensus}")
```

Related Skills

engineering-solver-domain-recon

from vamseeachanta/workspace-hub

Deep reconnaissance of an engineering solver domain (OrcaWave, OrcaFlex, CalculiX, OpenFOAM, etc.) across a multi-repo ecosystem — map infrastructure, issues, skills, data artifacts, machine constraints, and solver queue state before planning work.

orcawave-aqwa-benchmark

from vamseeachanta/workspace-hub

Cross-validation specialist for comparing OrcaWave and AQWA diffraction analysis results. Provides statistical comparison, peak value validation, and automated benchmark reporting for hydrodynamic coefficient verification.