Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add SteadfastAsArt/geoscience-skills --skill pyvistagit clone --depth 1 https://github.com/SteadfastAsArt/geoscience-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/steadfastasart/geoscience-skills/pyvista)<a href="https://agentmods.dev/skills/steadfastasart/geoscience-skills/pyvista"><img src="https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/pyvista/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/steadfastasart/geoscience-skills/pyvista"><img src="https://agentmods.dev/badge/skills/steadfastasart/geoscience-skills/pyvista.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00114 | $0.01518 |
| Opus 5.5 | $0.00046 | $0.00607 |
| Sonnet 5.5 | $0.00023 | $0.00304 |
| Haiku 4.5 | $0.00011 | $0.00152 |
Grade A, and why
pyvista scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PyVista - 3D Visualization
Quick Reference
import pyvista as pv
mesh = pv.read('model.vtk')
plotter = pv.Plotter()
plotter.add_mesh(mesh, scalars='property', cmap='viridis')
plotter.show()
Key Classes
| Class | Purpose |
|---|---|
pv.Plotter |
Main visualization window |
pv.PolyData |
Surface meshes, point clouds |
pv.StructuredGrid |
Regular 3D grids |
pv.UnstructuredGrid |
Irregular meshes |
pv.ImageData |
3D voxel data (seismic) |
Essential Operations
Load and Display Mesh
mesh = pv.read('model.vtk')
plotter = pv.Plotter()
plotter.add_mesh(mesh, scalars='lithology', cmap='Set1')
plotter.show()
Create Structured Grid (Surface)
x, y = np.meshgrid(np.arange(-10, 10, 0.5), np.arange(-10, 10, 0.5))
z = np.sin(np.sqrt(x**2 + y**2))
grid = pv.StructuredGrid(x, y, z)
pv.Plotter().add_mesh(grid, scalars=z.ravel(), cmap='terrain').show()
Visualize Point Cloud
cloud = pv.PolyData(np.random.rand(1000, 3) * 100)
cloud['depth'] = cloud.points[:, 2]
pv.Plotter().add_mesh(cloud, scalars='depth', point_size=5,
render_points_as_spheres=True).show()
Volume Rendering (Seismic)
grid = pv.ImageData(dimensions=(nx+1, ny+1, nz+1), spacing=(25, 25, 10))
grid.cell_data['amplitude'] = data.ravel(order='F')
pv.Plotter().add_volume(grid, cmap='seismic', opacity='sigmoid').show()
Slice Through Volume
volume = pv.read('seismic.vti')
slice_x = volume.slice(normal='x', origin=volume.center)
pv.Plotter().add_mesh(slice_x, cmap='seismic').show()
Well Path Visualization
points = np.column_stack([x, y, z]) # Well trajectory
tube = pv.Spline(points, 500).tube(radius=5)
pv.Plotter().add_mesh(tube, color='brown', label='Well').add_legend().show()
Combine Multiple Surfaces
plotter = pv.Plotter()
plotter.add_mesh(horizon1, color='gold', opacity=0.7, label='Top')
plotter.add_mesh(horizon2, color='blue', opacity=0.7, label='Base')
plotter.add_mesh(fault, color='red', opacity=0.5, label='Fault')
plotter.add_legend().show()
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed · +2 lines · +1 tokens per session 5ce3a6fa7385
- 2mo ago First seen · 161 lines · 113 tokens per session scan A 395644a76b88
pyvista is a skill published in the GitHub repository SteadfastAsArt/geoscience-skills (73 stars, last pushed 1mo ago), licensed MIT. It adds 114 tokens to every session and 1,518 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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